Research on Implementation and Evaluation of Highway Green Construction

This article analyzes how to implement green construction in highway construction around six aspects of highway green construction management, construction material saving, water saving, energy saving, land saving and environmental protection. According to the control and non-control work, this article studies how to evaluate the implementation effect of highway green construction from the aspects of sub-elements, sub-batches, sub-project categories and sub-stages. The proposed implementation plan, evaluation method and evaluation organization of highway green construction can provide technical reference for the implementation of highway green construction.

Introduction
The construction and development of modern transportation must be integrated with the sustainable ecological environment. In the course of construction, highway projects will occupy land, consume resources, and affect and destroy the environment to a certain extent. How to achieve the minimum resource consumption, the minimum energy consumption and the minimum negative impact on the environment in highway construction, and how to achieve the green goal of resource conservation, environmental friendliness, energy conservation and high efficiency during the construction process are the new requirements of modern engineering construction. The implementation of green construction will be an effective means to meet the new requirements of highway construction. This article will analyze how to implement green construction and how to carry out green construction evaluation in highway construction.

Implementation analysis of highway green construction
In the course of the construction of highway project, the green construction should be carried out from the aspects of construction environment protection, material, energy and water resources saving and recycling, and land resources saving and protection.Through the implementation of material saving, water saving, energy saving, land saving and environmental protection and other technical measures, strengthen system construction and site management, make the highway construction meet the requirements of green ecology.

Green construction management:
• Establish green construction management system and implement management by objectives. Promoting green construction of highway construction requires the establishment of a sound green construction management system and management system. In the management system, the organizational structure should be determined, the management responsibilities of relevant personnel should be clarified, and the supervision responsibilities should be implemented to people. Management systems and emergency plans should be established for material saving, water saving, energy saving, land saving, environmental protection and occupational health and safety of construction personnel. The implementation of management by objectives requires clear environmental protection goals, and the conservation, recycling and protection objectives of materials, water, energy and land for the project construction.
• Perfect drawing design and construction plan. In the review stage of the design drawings, the impact of the project construction on the surrounding environment should be reviewed, especially the setting of structures, protection forms and drainage design, to further improve the drawings design. According to the requirements of green construction, special green construction chapters shall be added to the construction organization design and construction plan, which shall cover the specific engineering measures and technical requirements of green construction management and material saving, water saving, energy saving, land saving and environmental protection • Implement green construction management. The main tasks are as follows: incorporating the relevant content of green construction into the engineering and technical submission of design and construction; setting up a green construction expert committee to conduct full-process technical consultation on green construction schemes and implementation; regularly carrying out green construction self-inspection and evaluation, and conducting file management of green construction process management data; according to the requirements of green construction, carry out regular green construction inspection, and formulate continuous improvement measures to implement.

Highway construction environment protection:
During highway construction, there are many sources of environmental pollution and damage, including: dust pollution, water pollution, engineering waste pollution, and noise source pollution. Firstly, environmental protection targets for different types of pollution should be established, such as control targets for dust, water pollution and noise, and targets for the production and recycling rate of project garbage. Then, targeted protection and protection measures should be taken for various types of pollution and the proposed targets.
• Construction dust control. Sprinkling, covering and other dust suppression measures shall be taken for construction roads, exposed soil and centralized earthwork; to take sealing or covering measures for vehicles prone to dust; combined with the sewage recycling facilities of the construction site, set up a car wash tank at the site entrance and exit to clean the engineering vehicles; closed storage of construction materials that are easy to fly and fine particles; take shelter and dust removal measures for construction work that is easy to produce dust; dust blasting technology and dust removal measures are adopted in blasting operation of tunnel and rock slope; establish the system of cleaning dust by drying water, equip with relevant equipment and use scientifically. • Sewage discharge control. Drainage ditches are set up around roads and material storage sites at the construction site to collect rainwater for centralized drainage. Sewage sedimentation tanks are set up in the steel reinforcement processing plant, concrete mixing station, bridge beam and slab prefabrication plant, etc., so that construction sewage can be discharged after precipitation treatment. In the construction site to achieve construction sewage and rainwater diversion discharge. Site kitchen set grease trap, construction site toilet set septic tank, and regular professional cleaning. • Engineering waste disposal. Construction waste such as construction muck and silt shall be discharged in compliance with the premise of obtaining the discharge license. The engineering waste shall be collected by classification and stacked in a concentrated manner. Materials such as crushed stones and earthwork should be used as backfill material for foundation and subgrade, and the recycling rate of engineering waste should be above 50%. • Construction noise control. In the selection of construction equipment, low-noise equipment and technology should be used for construction. Noise monitoring points should be set up on the construction site for dynamic monitoring.
During the construction process, the construction machinery that generates noise should be far away from the office area, living area and surrounding residential areas, and effective noise reduction and sound insulation measures shall be adopted. The emission of construction noise shall comply with the provisions on prohibited construction time and noise intensity.

Highway construction material saving and utilization:
In the construction organization design and construction plan, it is necessary to make clear the material procurement and turnover plan, material saving and utilization plan, make clear the material loss rate and recycling utilization rate, and ensure the reasonable use of materials.
• Material selection. Green and environmentally friendly construction materials should be selected in priority, and local construction materials should be mainly used to reduce the transportation distance of materials. Detachable and recyclable materials shall be used for temporary facilities and temporary protective facilities. Reduce material usage by using high strength materials. Adopt standard, assembly and standardized construction materials and processes to improve the yield of materials and construction efficiency. • Material saving. Highway structures and small components should be standardized and assembled, and mechanical and electrical installations should be integrated pipeline optimization design to reduce material consumption and wastage. During the construction process, especially in the construction links such as reinforcement processing, concrete mixing, and bridge beam and slab prefabrication, new technologies should be fully applied, and information technology should be used to improve the efficiency of material use and reduce material consumption. • Material recycling. During the construction process, the surplus materials of construction materials and equipment should be used reasonably, the packaging materials of construction materials and equipment should all be recycled, the road topsoil should be collected for afforestation and planting, and the existing buildings and municipal facilities should be fully utilized in the construction of construction facilities. For the pavement overhaul and road reconstruction project, the original pavement materials and guardrail facilities should be used scientifically and rationally.

Highway construction water saving and utilization:
The water saving goal of the entire construction process should be clarified, and water saving measures and water resource utilization plans for each construction link should be formulated, which should be strictly implemented during the construction process.
• Construction water saving. The construction water saving management system should be established, and the water supply network on the construction site should be designed rationally, and water saving construction technology and measures should be adopted during the construction process. All domestic water used at the construction site shall be equipped with water-saving appliances, and the domestic water and production water shall be measured and assessed respectively. Strengthen the daily management and maintenance of water equipment to prevent leakage of pipe network and water appliances. Carry out the propaganda of water saving in construction and improve the consciousness of water saving of construction personnel. • Water resource utilization. Natural water such as construction water and rainwater should be collected and used. Natural water should be used as far as possible and tap water should be reduced. The system of water resources reuse collection and treatment shall be established, and the equipment of sewage purification and reuse shall be equipped to realize the recycling of production and domestic sewage after treatment. During the construction process, concrete mixing and health maintenance, road spraying, greening irrigation, washing construction vehicles and equipment and other construction links should use natural water or recycling water instead of tap water.

Highway construction energy saving and utilization:
It is necessary to make clear the energy-saving target of highway project construction, and strictly control the allocation rate of electricity, fuel, gas and energy-saving equipment in office, living and construction area by setting the target.
• Energy saving of electric facilities. Establish a temporary electricity management system to measure and assess electricity consumption in office, living and construction areas. Energysaving lighting lamps should be adopted and automatic lighting control such as voice control and light control should be adopted. During the construction process, temporary power facilities shall be reasonably equipped, energy-saving products shall be adopted and automatic control devices shall be equipped. The lighting design of the construction site should meet the requirements of relevant codes, and try to use renewable energy such as solar energy and wind energy. • Energy saving of mechanical equipment.
Establish construction equipment management system, establish equipment technical files, implement equipment regular maintenance. During the construction process, the construction equipment with high energy efficiency should be selected, the construction sequence should be reasonably arranged, and the resource sharing of construction equipment should be implemented to reduce the number of equipment in the operation area. After the completion of the construction should be turned off in time to reduce energy consumption of equipment. • Energy saving of temporary facilities.
Temporarily arrange temporary facilities in office, living and construction areas, and use natural light as far as possible to ensure good ventilation and reduce electricity consumption. Temporary facilities should use composite wall and roof panels that meet thermal performance standards. Sun protection measures such as curtains and sunshades should be used to reduce temperature control energy consumption. • Energy saving in site construction. During the construction process, the construction process and progress should be reasonably arranged, the construction technology and process with low energy consumption should be adopted, and the transportation distance of building materials should be shortened by selecting local materials, so as to reduce the time of night operation and the energy consumption of lighting. Measures should be taken to reduce secondary material handling in the field.

Highway construction land saving and protection:
Before the organization of construction, the construction site should be combined with the situation of the construction site, the area of the construction site and the land protection during the construction process should be subject to objective control, and strict control management should be implemented.
• Land saving.Reducing land occupation as the first principle of construction site layout, compact layout of the construction site and implementation of dynamic management. Reasonable design of the site road, the maximum implementation of the combination of permanent and temporary, make the temporary road layout of construction combined with the original road and permanent road, and combine the temporary construction facilities with the original building and permanent building. The temporary construction facilities that need to be built should adopt reusable assembled structures. • Land protection. Before organizing the construction, the construction unit should fully understand the protection requirements of the construction site and adjacent areas of cultural landscape and the distribution of infrastructure pipelines, and formulate detailed construction protection measures. During the construction process, the removal and abandonment of soil shall be carried out at the specified sites, and effective measures shall be taken to prevent soil erosion and protect the original vegetation within the construction site. Damaged vegetation shall be restored as soon as possible after construction.

Evaluation method:
The implementation of green construction in highway construction projects mainly focuses on the six elements of green construction management, material saving, water saving, energy saving, land saving and environmental protection.
To evaluate the implementation of green construction of highway construction project, we should first combine the construction characteristics and requirements of the project and divide the specific work of the above six elements into control work and non-control work. The control work is defined as the control work. If it is not implemented during the construction process, the green construction of the project will be rejected. The noncontrol work is graded, and the scoring criteria for each work are shown in Table 1. The total score of noncontrol work of each factor is calculated by a percentage system, and the formula is as follows: Where Si is the total score of non-control work of each element, i is 6 elements, j is non-control work of each element, n is the total number of non-control work of each element, Aj is the score of non-control work. The highway construction could be divide into four sub-project including subgrade engineering, bridge and tunnel engineering, pavement engineering and traffic safety engineering. Batch evaluation and phase evaluation could be adopted to estimate the green construction of each sub-project. The weight coefficients of the six elements in each sub-project are shown in table 2. The calculation formula of batch evaluation is as follows: The total score of non-control work of each factor is calculated by a percentage system, and the formula is as follows: Where E is the score of each sub-project's batch evaluation, Si, i are the same as above, k is the weight coefficient which are shown in table 2.
The calculation formula of phase evaluation is as follows: Where G is the score of each sub-project's phase evaluation, Ex is the score of each sub project's batch evaluation, and m is the number of batch evaluation. The green construction evaluation of highway construction projects is calculated according to the following formula, and the weight coefficients of each sub-project in the green construction evaluation are shown in Table 3.
Where W is the green construction evaluation score of highway construction project, t is the evaluation score of four sub-projects, Gt is the evaluation score of each sub-project stage, and p is the weight coefficient of subproject, as shown in table 3. The green construction grade of highway construction project is determined according to the following conditions. The green construction evaluation score W<60 is unqualified, 60≤W<85 is qualified, W≥85 is excellent.

Evaluation implementation
Highway construction projects implement green construction. During the construction process, batch evaluation of each sub-project should be carried out every 2 months, and batch evaluation of each sub-project should not be less than 2 times. Batch evaluation shall be organized by the construction unit, the project construction unit and the supervision unit. The stage evaluation of the green construction of each sub-project shall be conducted after the completion of the sub-project, and shall be organized by the supervision unit, the project construction unit and the construction unit. The green construction evaluation of the project shall be conducted after the completion of the project, and shall be organized by the construction unit, the project supervision unit and the construction unit. The evaluation results of the 3 types of evaluation shall be signed by the construction, supervision and construction units. After each batch evaluation, the construction unit shall, together with the construction unit and the supervision unit, formulate improvement measures according to the evaluation results and the green construction of the project, and implement them in the follow-up construction.
In order to ensure the green construction quality of the project, the construction unit may entrust the technical consulting institution to formulate the green construction plan of the project, carry out regular green construction inspection and provide technical services for the 3 types of evaluation.

Conclusions
Green construction refers to the construction activities to save resources and reduce the negative impact on the environment to the maximum extent through scientific management and technical application under the basic requirements of quality and safety. The premise of implementing green construction in highway construction is to establish a management system and implement green construction management. At the same time, it is necessary to formulate implementation plans for material saving, water saving, energy saving, land saving and environmental protection, define control objectives, apply technical means and implement construction requirements. In response to the implementation of highway green construction, scientific evaluation should be conducted according to factors, batches, project categories and stages, so as to determine the implementation effect of green construction. The implementation scheme and evaluation method of green construction proposed in this paper will provide reference for highway construction projects to carry out green construction.


Effect of discipline on employee performance through total quality management as mediation variables

Article history: Received: February 10, 2020 Received in revised format: March 2

Introduction
In today's global competition, people talk about quality, especially those who discuss the work that produces products or services. A product is made because of a need, and that need develops along with the quality of its users, as well as improvements for the environment from local to global changes that cause changes in all sectors of life. There is a global need to adjust, making managers not only discuss at the local, national or regional level, but must compete. There is only one company to overcome this, namely to improve, both to improve the quality of the resources that are owned. The quality of human resources can increase competition in improving business towards the progress of a company (Yasin et al., 2019). By using a good management system through management, it is important to improve company performance through the performance of its employees. To achieve organizational goals one of the most important things is associated with work discipline. Employee discipline is the nature of an employee who consciously complies with certain organizational rules and regulations. Discipline can be seen as a form of judgment for employees in implementing organizational rules. The higher the discipline, the higher employee work productivity and organizational performance. One of the commonly used quality management tools is Total Quality Management (TQM). Organizations that implement TQM aim to meet customer satisfaction and expectations, the demands of changing environments and the demands of the organization itself. The effective implementation of TQM has a positive influence which will ultimately benefit the organization. TQM focuses on services and workforce involvement and it is expected to affect the performance of the company. Related to employee performance, basically the implementation of TQM carried out in a planned and directed manner is expected to help in increasing employee productivity and performance (Poernomo et al., 2006). Therefore, companies need to create an appropriate performance measurement system to determine the characteristics and quality of performance and identify actions that can be taken in an effort to increase employee productivity. The more often a company measures employee performance, the more company will improve the performance of its employees, and the increase in performance will have an impact on improving quality. Empirically, the results of a study on the impact of implementing TQM on employee performance are shown by Therese (2007) who found a strong positive relationship between the level of implementation of TQM practices and organizational performance. Then Al-Shobaki, et al. (2010) also found evidence that implementing TQM can improve organizational performance as reflected in efficiency and productivity. In contrast, the findings of Enny (2015) show that TQM does not have a positive and significant effect on employee performance. From the research findings, it is known that the application of TQM can affect employee performance, although the influence may be different in each company (Ismunawan, 2010). In improving the performance of the Ambon State Polytechnic educational staff, employees are required to do their jobs properly. In Ambon State Poblytechnic, there are several people who are excellent in completing their tasks not on time, the lack of responsibility and commitment in carrying out the task, the lack of trained personnel that can be seen from the presence of employees who are waiting for orders to do the work and often delayed work. From this phenomenon there was a decrease in the level of work discipline, making the education staff not eager to work, the sense of responsibility is reduced, and inconsistent in doing the work.

Research Problem
1. What is the effect of discipline on the performance of the Ambon State Polytechnic educational staff? 2. What is the effect of discipline on performance through total quality management on the Ambon State Polytechnic educational staff?

Objectives of the Research
1. Analyze and assess the effect of discipline on the performance of the Ambon State Polytechnic educational staff, 2. Analyze and assess the effect of discipline on performance through TQM of Ambon State Polytechnic education staff.

Discipline
Discipline comes from Latin, namely discipline which is defined as training or education, character development, and politeness. One aspect of the strength of Human Resources (HR) can be reflected in the attitude and behavior of the discipline, because discipline has a strong impact on an organization to achieve success in pursuing planned goals. Discipline is the most important operative function of human resource management since the better employee discipline is, the higher the achievement or performance is achieved and will create quality employees. Discipline is very important for organizational growth, especially for employees to discipline themselves in carrying out work both individually and in groups. Keith Davis in Mangkunegara and Prabu (2013), stated that "discipline is management action to enforce organization standards". Based on the opinion of Keith Davis, work discipline can be interpreted as the implementation of management to reinforce organizational guidelines. Then according to Sulistyani and Rosidah (2003), discipline is a procedure that corrects or punishes subordinates for violating rules or procedures, discipline is a form of employee self-control and regular implementation and shows the level of sincerity of work teams in an organization. According to Siagian (2006), discipline is training, specifically training mind and attitude to produce self-control, self-habits to comply with applicable regulations. So, someone will be willing to obey all the rules and carry out their duties, both voluntary and forced. Discipline means that employees always come and go home on time, do all their work well, comply with all applicable rules and social norms. According to Mangkunegara and Prabu (2013), there are 2 forms of work discipline, namely preventive discipline and corrective discipline. 1). Preventive Discipline, Preventive Discipline is a must to move employees to follow and approve work, the rules that the company has outlined, 2). Corrective Discipline, Corrective Discipline is an effort to move employees in uniting a regulation and directing it to keep abiding by the rules in accordance with the guidelines that apply to the company. Discipline is an HRM function that is a benchmark to measure or find out whether other HR functions as a whole have been implemented properly or not. Good employee discipline, reflect that other HRM functions have been carried out according to plan. Conversely, if employee discipline is not good, it means that the application of HRM functions is not good.

Total Quality Management
Total Quality Management consists of several instruments and quality techniques, in addition to the various values and beliefs held by all staff in the same organization (Gharakhani et al., 2013). TQM can be defined as a strategy that aims to produce and transfer services that are more efficient and superior, through achieving collaboration between members of the organization (Lakhal et al., 2006). Various things are done to improve the quality that is applied to the company's products, services and management. Along with the development of science, an innovation is known as TQM. According to Tjiptono and Diana (2003), TQM is an approach in increasing organizational productivity (quantitative performance), improving quality (reducing errors and damage levels), increasing the effectiveness of all activities, increasing efficiency (reducing resources through increasing productivity), and doing everything correct in the right way. The definition of Total Quality Management according to Handoko, (2008) is as follows: 1. Total : Total Quality Management is a comprehensive organizational strategy that involves all levels of management and employees, not only end users and external buyers, but also internal customers, suppliers, and even support personnel. 2. Quality: TQM places more emphasis on quality service, not just defect-free products. Quality is defined by the customer, customer expectations are individual, depending on socioeconomic background and demographic characteristics 3. Management: TQM is a management approach, not a narrow quality control technical approach.
From the understanding of the experts above, Total Quality Management can be broadly interpreted as a strategy and management philosophy that tries to integrate all organizational functions that involve all managers and employees to work together in improving products, services, people, processes, and the environment so as to optimize the performance of employees of the company. The rationale for the need for TQM is very simple, namely that the best way to compete and excel in global competition is to produce the best quality. To produce the best quality, continuous improvement efforts are needed for human capabilities, processes and the environment. The best way to continually improve component capabilities named TQM. The application of TQM in a company can provide several key benefits which in turn increase the profit and competitiveness of the company concerned.

Employees Performance
According to Hasibuan (2008) "Performance is the result of work achieved by a person in carrying out the tasks assigned to him based on skill, experience, sincerity and time". Meanwhile, according to Suyadi Prawirosentono (2008) "Performance is work results that can be achieved by a person or group of people in an organization, in accordance with their respective authorities and responsibilities in an effort to achieve the objectives of the organization concerned legally , does not violate the law and in accordance with morals and ethics. Hasibuan (2008) revealed that "Performance is a combination of three important factors, namely the ability and interest of a worker, the ability and acceptance of the delegation's assignment and role and the level of motivation of workers". If the performance of each individual or employee is good, then company performance is expected to be good too. Performance is the result of quality and quantity of work achieved by an employee in carrying out their duties in accordance with the responsibilities given to him (Mangkunegara & Prabu, 2006). Performance opportunities need to be further strengthened even though an employee may be willing and able. According to Wirawan (2009) "Performance standards are targets, targets, goals of work effort of employees within a certain period of time. In carrying out its work, employees must direct all energy, thoughts, skills, knowledge, and work time to achieve what is determined by performance standards". There are three basic types of performance criteria, namely: a) Criteria based on nature (focusing on personal characteristics of an employee), b) Criteria based on behavior (criteria that are important for jobs that require interpersonal relationships), c) Criteria based on results (criteria that focus on what has been achieved or produced).
To achieve employee performance objectives, we may need different things, including: appraisal must have a relationship with work, the existence of work performance standards, practical (easily understood or understood by employees or appraisers). Employees want feedback regarding their achievements. If performance does not meet the standards, then the assessment provides an opportunity to review employee progress and develop performance improvement plans. According to Bohlander et al. (2004) performance variables are summarized as follows, 1. Overall quality is the employee's perception of the overall quality of work. Quality perception is an overall picture of the perception of inputs and outputs in a process. Input in the form of all the resources is used to carry out a process while the output is the result (outcome) of a process. 2. Reliability is the employee's perception of the quality of work that has been obtained by the employee is accurate / in accordance with existing information and can be trusted. Reliability is the consistency of the results of input to output comparison. The more stable the results obtained, the more consistent. 3. Employee quality is the perception of the quality of the workforce concerning the suitability of capabilities and capabilities after carrying out their work. The quality of workers is the level of ability, capacity and capability of employees in completing their work.
Based on the brief discussion, the proposed study of this paper is summarized as Fig. 1

Research sites
This research was conducted at Ambon State Polytechnic.

Population and Samples
The population used in this study included all 100 educational staff in the Ambon State Polytechnic.

Data analysis method
This research was conducted at Ambon Polytechnic which was involved with 100 educational staff. Quantitative data were analyzed using descriptive and structural analysis Equation Modeling (SEM). In the analysis according to Ghozali (2006), path analysis the model of all latent variables in Partial least square (PLS) consists of three sets relationship. First, the model determines the relationship between latent variables (structural model). Second, the outer model determines the relationship between latent variables and measurement model. Third, the weight relationship is where the value of the latent variable case can be estimated..

Inner Model
The inner model, also called inner relations and substantive theory, describes the relationship between latent variables based on the substance of the theory. The equation model is as follows: The above formula describes the endogenous (dependent) vector of latent variables. The simbol of  is a vector of exogenous latent variables. The symbol of  is associated with unexplained variance. PLS is disigned for recursive models. Therefore, there is a relationship between latent variables, each dependet latent variable, or often called the causal chain system of latent variables.

Outer Model
An Outer model is also called outer relation or measurement model, it defines how each indicator block is related to its of latent variables. The Outer models of a block with a reflexive indicators can be indicated by the following eguation : x = x  + x (2) y = y  + y x and y are indicators or manifest variables for exogenous  and endogenous latent variables. Meanwhile, x and y are loading matrix that describe a simple regression coefficients that connects latent variables to the indicator. Residuals measured by x and y can be interpreted as measurement errors or noise .

Weight Relation
Inner and outer models provide the specifications followed in the estimation of the PLS algorithm. We need to define the relationship weights with weight relations. The values of the case latent variable is estimated in PLS as follows : wkb and wki are k weights used to form estimated of latent variables b and i. Estimation of Latent variable are linear aggregate of indicators whose weight values are obtained from PLS estimation procedures such as specified by the inner and outer models where is an endogenous (dependent) and  is an exogenous (independent) vector of latent variables. The symbol  represent residuals vector and  and  arethe path coefficients matrix. Fig. 2 shows the results of SEM implementation.

Assessing the Outer Model or Measurement Model
The construct of Discipline, Total Quality Management and performance are analyzed by looking at the convergent validity and reliability of each indicator. The output in Table 1 and Fig. 2 shows the loading factor for the three constructs above the required 0.5, with a statistical T value above 1.96 (for a significance level of 0.05) which indicates that the construct has a good discriminant validity.

Testing the Structure Model (Inner Model)
Discriminant reliability (AVE), Cronbach alpha (CA), and composite reliability (CR) were measured. The criteria stated that if discriminant reliability (AVE) is greater than 0.5, Cronbach alpha is greater than 0.6 and composite reliability is greater than 0.7, the construct is declared reliable. The reliability test shows ( Table 2) that all latent constructs have AVE values greater than 0.5, CA values greater than 0.6, and CR values greater than 0.7. Hence, based on reliability criteria, all items can be declared reliable in measuring latent variables. The measurement model of R-square discipline on total quality management is 0.275 or 27.5% and discipline on performance through total quality management gives an R-square value of 0.748 which can be interpreted that the discipline variable on performance through total quality management is 74.8%.  Next is the hypothesis test and determines the significance of the influence of exogenous variables on endogenous variables, both directly and indirectly path. Table 3 illustrates that all relationships of the variables are meaningful when the level of significance is five percent, and from the results of data analysis it is found that the magnitude of the parameter coefficient between discipline to performance is 0.206 or 20.6% and the magnitude of the discipline parameters to performance through Total Quality Management is (0.524 × 0.739) = 0.387. Based on the above results, hypotheses 1 and 2 are accepted

Effect of work discipline on the performance of the Ambon State Polytechnic educational staff
The results showed the effect of discipline on the performance of the Ambon State Polytechnic educational staff by 20.6%. This shows that the higher the level of discipline, the better the performance of the educational staff. Work discipline basically has a high role in improving employee performance. High work discipline must always be maintained, even better. Employees who have good work discipline are expected to be able to try as much as possible to complete their work and to produce optimal performance for the organization. Disciplined employees tend to be punctual in carrying out established procedures and have high responsibilities. This relates to the theory of work discipline according to Soejono (1986) which states that good discipline reflects the magnitude of one's sense of responsibility for the tasks assigned to him. This can encourage increased performance and the achievement of objectives, employees, and the community. In other words, work discipline is the main capital that determines the level of employee performance. Indicators of work discipline in this study are carrying out duties and obligations, adherence to regulations and timeliness. Carry out the duties and obligations by looking at the responsibilities on the results of the work, working with established procedures, ready to improve the work if something goes wrong. Obeying the rules that have been established shows that education staff have good work discipline. In this study, measured by not delaying work time, receiving sanctions if violating the rules and obeying the leadership. Furthermore, punctuality includes arriving before working hours, leaving the office with the leader's permission, and using appropriate breaks. Punctuality is a form of employee work discipline by coming on time, and regularly. Carry out the duties and obligations by looking at the responsibilities on the results of the work, working with established procedures, ready to improve the work if something goes wrong. Obeying the rules that have been established shows that education staff have good work discipline. In this study, measured by not delaying work time, receiving sanctions if violating the rules and obeying the leadership. Furthermore, punctuality includes arriving before working hours, leaving the office with the leader's permission, and using appropriate breaks. Punctuality is a form of employee work discipline by coming on time, and regularly. From this explanation it can be concluded that the existence of good work discipline will produce good employee performance, on the contrary if the work discipline is not good it will produce poor employee performance too. This research was also supported by research conducted by Suprayitno and Sukir (2007) which shows that work discipline has a significant positive effect on employee performance. When compared with the value of indirect effects, discipline to performance through Total Quality Management has a smaller value of only 20.6%. The results showed the lowest score of the disciplinary variable on the indicator of timeliness in question is adherence to the use of effective hours of work in accordance with Presidential Decree No. 68 of 1995 which is 37 hours 30 minutes per week or ≥7.5 hours per day. Based on the results of the study we need to note the lack of discipline of education personnel, especially adherence to work standards due to the absence of strict sanctions for employees who lack discipline. The use of hours of rest that is less effective, since it is often misused for personal purposes makes the time to re-enter work becomes delayed. It makes their work hours cut off, so that the results of their work are not optimal, work that should be able to be completed in one day, can be completed in 2 or 3 days. When working hours can be optimally implemented it can improve the performance of the Ambon State Polytechnic education staff. Based on research, discipline can improve the performance of Ambon State Polytechnic education staff. This is supported by the results of research by Setiawan et al. (2006) which states that discipline has a positive and significant influence and contributes to improving employee performance, the effect of discipline as measured by indicators compliant with regulations, effective at work (employees finish work quickly), and corrective actions (taking notes on all work).

The influence of discipline on performance through total quality management on Ambon State Polytechnic education staff
Basically Total Quality Management (TQM) is a management science theory that involves everyone in the organization to carry out continuous quality improvement programs for the organization's products, services, processes and environments. Ambon State Polytechnic in an effort to improve employee performance began to implement a Total Quality Management system within the campus environment by involving all existing lines by prioritizing cooperation. The results of the study found that work discipline could improve the performance of the education center through Total Quality Management efforts by 38.7%. The discipline of their work must be directed first in the effort to improve the quality of services, administrative processes and lectures by involving all lines in the Ambon State Polytechnic environment. The relationship between work discipline and Total Quality Management is very close because with the discipline that implements the Total Quality Management system, employee performance will be easy to improve. The results showed that discipline had an important impact on the performance of educational staff through the satisfaction of the practice of Total Quality Management in Ambon State Polytechnic. From this, it can be said that Total Quality Management can bridge the effect of discipline on the performance of the educational staff, however, in the absence of Total Quality Management basically effective work discipline also has a strong influence in improving the performance of the educational staff. In implementing Total Quality Management, teamwork is an aspect that is considered quite important by employees in encouraging the achievement of their performance. here the education staff need to build a good relationship with fellow colleagues. These needs must be able to be grown and developed by education staff, so there is no gap between them and there is a sense of security at work. From the overall research findings, it can be concluded that the effectiveness of teamwork (as an important part in the implementation of Total Quality Management practices) will create a good relationship among the education staff so that it could encourage the feeling of satisfaction of the education staff and ultimately improve the quality of their performance, therefore the education staff needs a tool to build the effectiveness of team work in the implementation of each work. In addition, another aspect that is also considered quite important by education personnel is the culture of the organization. As expressed by Parncharoen et al. (2005) the implementation of organizational quality management is essentially a program of organizational change that requires transformation of organizational culture, processes, and beliefs, So, if the implementation of a quality management system can change the orientation of an organizational culture towards a quality culture, according to the opinion of Hardjosoedarmo (2005) this will improve employee performance and ultimately improve the performance of this organization.
In line with the research of Hendricks and Singhal (1999); Ittner and Larcker (1996) that when an organization implements Total Quality Management in an effective way, its performance will be greatly improved from several aspects. In a literature review that discusses the impact of total quality management on organizational performance, Saizarbitoria (2006) shows that there is a positive direct relationship between Total Quality Management and organizational performance.

Conclusion
Work discipline directly influences the performance of educational staff by 20.6% and when viewed from the indirect effect of work discipline has a positive effect on performance through total quality management of 38.7%. This means that in improving the performance of educational staff, work discipline should be directed in the total quality management process so that the work process is more focused and focused. But even without a total quality management system, the performance of the teaching staff can still be improved through discipline. So discipline is the main key in improving the performance of education staff, and total quality management is a planned system that is proven to be able to improve performance better. By implementing a total quality management system there will be an increase in the quality of performance and improvement of management in all lines.


“Sharia corporate governance and financial reporting timeliness: Evidence of the implementation of banking regulations in Indonesia”

ARTICLE INFO Zulfikar Zulfikar, Andy Dwi Bayu Bawono, Mujiyati Mujiyati and Sri Wahyuni (2020). Sharia corporate governance and financial reporting timeliness: Evidence of the implementation of banking regulations in Indonesia. Banks and Bank Systems, 15(4), 179-192. doi:10.21511/bbs.15(4).2020.15 DOI http://dx.doi.org/10.21511/bbs.15(4).2020.15 RELEASED ON Tuesday, 22 December 2020 RECEIVED ON Wednesday, 11 November 2020 ACCEPTED ON Saturday, 12 December 2020

INTRODUCTION
The main function of SSB in the Sharia corporate governance (SCG) structure is to certify and control compliance with Sharia on financial contract activities carried out by shareholders, stakeholders and clients (Alkhamees, 2013;Alman, 2012).
In general, SCG is the same as a conventional corporate governance mechanism, which consists of several main proxies, namely the board of commissioners and directors (BOC and BOD) and the audit committee (AC). Previous SCG studies were widely used in the financial literature, for example, those related to a number proxies of quality of financial reporting in Islamic financial institutions. These proxies include accountability for financial information (Aribi et al., 2019;Jabbar, 2010), financial performance (Aribi et al., 2019;Buallay, 2019), dimensions of financial reporting quality (Rini, 2014), earnings management (Mersni & Ben Othman, 2016), financial reporting effectiveness (Hamza, 2013), and the level of disclosure (Darmadi, 2013). However, there is no literature that proves SCG as a determinant of FRTL of Islamic banks. The expectation regarding the relationship between SCG and timeliness assumes that Islamic financial reports represent cooperation between management and SSB as a guarantor of compliance with Sharia rules.
The Institute of Indonesian Chartered Accountants (Ikatan Akuntan Indonesia, abbreviated as IAI) defines timeliness as one of the qualitative characteristics aimed at increasing the usefulness of information, which simultaneously provides a faithful representation of what it is intended to represent and is relevant (IAI, 2017). The International Accounting Standard Board (2018) states that timeliness means that the available information can influence users to make decisions in a timely manner, so the older the information, the less useful it is. In Islamic banks, timeliness is useful for users of financial reports that include current and potential investors; qard fund owners; owners of temporary syirkah investment funds; owners of deposited funds; payers and recipients of zakah, infaq, alms and waqf; employees; suppliers and other business partners; customers; government and its institutions; and society. They use financial reports to meet several different information needs. To evaluate the gap between their importance and the availability of timely financial reports, this study focuses on SCG as the determinants of FRLT for IBs.
The implementation of Islamic banking regulations in Indonesia relating to corporate governance and FRTL are two different mechanisms. This raises a research question, namely whether the implementation of corporate governance regulations affects banks' compliance with the timeliness of financial reports.

LITERATURE REVIEW AND HYPOTHESES
Since 2007, IAI (2017), through The Indonesian Sharia Accounting Standards Board, has published a basic framework of Islamic financial reports for their preparation and presentation. One of the objectives of this framework is to use it as a reference for users to interpret the information provided in the financial reporting prepared in accordance with Sharia financial accounting standards (IAI, 2017). To achieve these objectives, an understanding of the qualitative characteristics of financial statements is required, including constraints on relevant and reliable information. The relevance and reliability of information depends on providing the information in a timely manner.
The basic framework states that if there are undue delays in reporting until all aspects are known, then the information generated may be very reliable but will lose relevance or be of little use to decision makers (IAI, 2017). This suggests that the timely consideration of information is a way to strike a balance between relevance and reliability.
The timeliness of issuing company reports in Indonesia refers to the regulations of the Otoritas Jasa Keuangan (OJK, 2016). In this regulation, OJK requires companies to submit annual reports at least at the end of the fourth month after the financial year ends. Furthermore, if the annual report is available to shareholders before the end of the annual report submission period, OJK must also receive the annual report on the same date that the annual report is available to shareholders.  (Jensen & Mecling, 1976). Meanwhile, the agent's opportunistic behavior (motivation to maximize self-interest) cannot be fully detected by the principal. If these two things are combined, it will be a major problem for the principal. Related to agency theory, Indonesia adheres to a two-layered system governance structure, each of which performs a different function (as principals and agents). The first function is controlled by the BOC, which represents shareholders in supervising the management of the company (principals), and the other function is performed by the BOD as a firm policy maker (agents). The existence of BOC is part of a protection mechanism to reduce agency cost (Fama & Jensen, 1983). The higher the level of agency problems, the greater the BOC's efforts to mitigate this problem (Aslam & Haron, 2020 Kusumawati and Hermawan (2013) found evidence that the presence of BOCs had no effect on preventing financial reporting fraud. Wiralestari (2015) identifies the characteristics of BOC, including competence, independence, and meeting frequency associated with the financial reporting quality. Wiralestari (2015) concluded that investigations of financial reporting quality in a sample of 82 non-financial companies were hampered by the condition of BOCs that did not understand the conditions of the company, worked part time, were in a minority and were unable to solve problems. The results of these studies indicate that the existence of BOC is not effective in supervising financial reporting. The failure of BOC in supervising the financial reporting preparation process implies that it takes longer time to produce quality financial reporting (Rini, 2014 Christensen et al. (2010) stated that the relationship between the independence of BOD and the reporting timeline is related to the hypothesis that the greater the proportion of independent BOD, the faster the time required for reporting verification. Bliss (2011) argues that independent BOD plays a more significant role in monitoring and supporting external auditors.
Sharia principles are among the fundamental features that distinguish Islamic banks from conventional banks. All interested parties, either directly or indirectly, hope to get benefits from bank activities in accordance with Sharia principles. To meet the expectations of these stakeholders, an agency that supervises the operation of the business is needed according to the right mechanism to solve Sharia problems (Kaaroud et al., 2020).
The role of SSB in improving the quality of financial reporting has not been widely discussed in the scientific literature. The purpose of this study is to examine the influence of the board of commissioners (BOC), the board of directors (BOD), the Sharia supervisory board (SSB) and the audit committee (ACE) on the financial reporting timeliness (FRTL). Based on prior research that has been previously discussed, this study has formulated the following hypotheses: H1: The board of commissioners has a negative influence on financial reporting timeliness.
H2: The board of directors has a negative influence on financial reporting timeliness.
H3: The Sharia supervisory board has a negative influence on financial reporting timeliness.
H4: The effectiveness of the audit committee has a negative influence on financial reporting timeliness. This study uses a two-stage approach. In the first stage, the study identifies the attributes of BOC, BOD, SSB, and ACE to determine the measure of these variables. The variables in this study are measured using the corporate governance compliance disclosure index (CGCDI), which is a comprehensive checklist of items of bank compliance with CG implementation regulations (see Appendix). Content analysis is carried out by reading the entire annual report before assessing the regulatory compliance index of each bank (Amalina Wan Abdullah et al., 2013; Darmadi, 2013). The score for each bank is determined by the item disclosed in a dichotomous way, if disclosed, is given the value of '1', '0' otherwise if the penalty if the item is not disclosed. The formula used to assign each index is as follows:

RESEARCH METHOD
In the second stage, this study designed a model to test whether BOC, BOD, SSB and AC had a relationship with the financial reporting timeliness of IBs. The study uses a regulation issued by the OJK Number 29/POJK.04/2016, which states that the annual report must be submitted to the OJK no later than the end of the fourth month after the financial year ends by the issuer or public company (OJK, 2016). Based on these provisions, Table  2 shows the pattern of companies in the sample submitting the publications of the audited annual financial reports.
In addition to the main variables, this study includes control variables, such as company size, asset quality, efficiency, financial condition, and capital adequacy. Baatwah et al. (2019) explained that the inclusion of control variables in the study is aimed at ensuring that the model used has better predictive ability, and the omitted variables do not This study is consistent with other studies that generally include firm characteristics as control variables. Company size is one of the control variables that is probably the most widely used in research on determinants of reporting timeliness. The results have also been widely verified by many authors (

CAPITAL -
The ratio of total equity to total assets

TYPE -/+
Type is a dummy variable if the bank is Islamic commercial bank taking 1, and 0 otherwise Note: a -regulatory deadline, f -frequency, fx -frequency in percent, and Cf -cumulative frequency in percent.  Tables 4 and 5 show descriptive statistics for the dependent and independent variables. FRTL is the number of days between the financial year-end and the date OJK received a company's audited financial statement. The greater the mean value of FRTL, the longer the time for the announcement of the audited financial report. The mean value of FRTL on ICb is shorter than SBu. This is evidenced by the results of the ANOVA test that the values at a different mean are significant at the 1 percent level. Meanwhile, there is no difference between ICb and CBs.  Table 5 presents the correlation matrix between independent variables. The correlation matrix aims to test whether there is multicollinearity or not between independent variables (Gujarati, 2004). It is expected that the correlation between variables is not > 0.80, and the variance inflation factor is no more than two (Gujarati, 2004). It is evident that the correlation between independent variables presented in Table 5 is less than 0.80, and the VIF value is no more than two for each variable. Thus, it can be concluded that the model used does not have multicollinearity problems.  Table 6 reports the results of the first and second regression equations aimed at analyzing each bank

DISCUSSION
H1 and H2 state that the boards of commissioners and directors are negatively associated with FRTL.
The negative sign implies that the higher the level of bank compliance with regulations regarding the existence of BOC and BOD, the more effective it is in complying with OJK regulations, which is marked by the short time to submit financial reports. H1 statement is supported in the findings of this study, which is indicated by the negative direction of the BOC coefficient, namely -5.15 for ICb, -3.98 for SBu, and -6.36 for CBs (each significant at the 1 percent level). These results support the findings of Robin and Amran (2016) that the presence of BOC is effective as control against the risk of timeliness. Meanwhile, the findings of this study also support the direction of H2 as indicated by the magnitude of the BOD coefficient, namely -7.27 for ICb, -4.87 for SBu, and -6.36 for CBs (each significant at the 5 percent level). This result is different from those of Kaaroud et al. (2020) that failed to prove the relationship between BOD and the extent of the audit report lag.
H3 predicts SSB to be negatively associated with FRTL. The findings of this study support the H3 direction, especially in the IBs group (ICb and SBu). In ICb, it was found that the SSB coefficient statistic was -3.82, significant at the 10 percent level. The study of SSB related to timeliness was carried out by Kaaroud et al. (2020). The results of this study do not support their investigation, which concluded that SSB had a weak association with timeliness. This is probably due to the different models and measurements of SSB they use. Their investigations focus on the skills that SSB members should possess while the current investigation is broader on the activities of SSB members in accordance with regulations. The more active the SSB members are, in addition to ensuring that operations are in compliance with Sharia, the shorter the audited financial reporting process. The investigation into the SBu group, although in a negative direction, had a weak association. This is made possible by the relationship between SBu and its parent company, CBs, which focuses more on conventional CG.
This study finds evidence for the H4 statement, which states that the audit committee effectiveness has a negative association with FRTL. The ACE coefficient statistical values for all bank Despite the use of a different ACE model and the measurement from previous research, it was concluded that the higher the level of compliance with banking regulations regarding audit committee activities, the more effective it will be to comply with OJK regulations related to shorter financial reporting submission times.
Furthermore, this study investigates the control variable. However, the evidence for the relationship between these variables is weak, as shown in Table 6 on the control variable group. This study did not find any significant evidence of a relationship between firm size, profitability, asset quality and financial condition and FRTL. Most of the previous literature was inconsistent with this research for two reasons. First, most of the literature reviewed excluded banks as the object of analysis due to different regulations between a bank and non-banking industries. This has led to a limited amount of literature on timeliness research in banks. Second, in relation to the regulations that apply to the banking industry, it is believed that there is no banking regulation in Indonesia that regulates the functions and obligations to meet the requirements of company size, profitability, asset quality, and financial condition.
Meanwhile, evidence of the relationship between capital adequacy and FRTL is shown by the significance of the coefficient at the 5 percent level for each bank group, namely -3.08 (ICb), -1.41 (SBu), and -4.60 (CBs). This is in line with the opinion that capital adequacy is one of the characteristics required for bank sustainability as The study extends the analysis in the form of additional discussion with testing impact type banks (ICb, SBu and CBs) on FRTL (see Table 7).
The regression model in Table 7 shows that the relationship of the type to FRTL is significant at the 5 percent level for the specification of the first model (panel A). As previously explained, panel A was used to analyze the comparison of FRTL variations on ICb and SBu. The direction of the relationship between the type and FRTL is negative, which means that ICb requires a shorter time to issue audited financial reports than SBU. This finding is consistent with the statement that banking regulations are generally aimed at their parent companies (Muneeza, 2014). This state-ment is supported by additional findings reported in Table 7 for the next two model specifications (panels B and C), which show that the relationship between the type and FRTL is not significant. These indicates that there is no difference in FRTL between IBs and CBs.

CONCLUSION
Previous authors have done extensive research on the relationship between CG and FRTL, but typically with non-financial firms. In this study, financial companies, especially banks, are used as research objects. The novelty of this paper is, firstly the construction of the SCG based on the IBs regulation to determine FRTL, and secondly, the comparison of the variation in FRTL between the IBs and CBs groups.
This study is based on Islamic banking regulations in Indonesia. The objective is to investigate the implementation of SCG (consisting of BOC, BOD, SSB, and AC) associated with FRTL. Each main variable is reviewed using content analysis on the disclosure of SCG and the implementation of FRTL regulation. The samples collected included 14 ICb, 20 SBu, and 20 CBs with the 2016-2019 observation period, so that during that period, 218 sample data were obtained. Based on the availability of unbalanced panel data, the panel regression model estimation method is used. The panel regression model is designed to analyze the variation in FRTL, as determined by BOC, BOD, SSB, and ACE for each bank specification. This paper finds evidence that the variation of FRTL for IBs is determined by the SCG mechanism (consisting of BOC, BOD, SSB, and AC). These findings indicate that the higher the level of compliance with SCG implementation, the shorter the time for issuing audited financial reports as a form of compliance with OJK regulations. As for SBu and CBs, the variation in FRTL is determined by the corporate governance mechanism (without SSB). SBu, although the operation uses Sharia principles, is actually an integral part of CBs, since SBu is generally part of the office channeling owned by the CB. Overall, the comparative study between IBs and CBs yields the same conclusions as the previous panel regression model analysis, namely that the FRTL variation in IBs is explained by the SCG mechanism (consisting of BOC, BOD, SSB, and AC), and CBs is explained by the CG mechanism (without SSB). Recent findings from this study concluded that the higher the capital adequacy, the shorter the FRTL.
Overall, the results of this study are useful for financial service authorities, auditors and investors. They can help OJK in overseeing the implementation of banking regulations based on information disclosed in annual reports. Based on these findings, OJK can find reasons why banks are late in issuing financial reports. The auditor may consider that the stronger the SCG and CG, the lower the audit risk presented to the audited bank. These findings can also be explored when making investment decisions in banks, especially with regard to better control over managers in the presence of SCG and CG. This study complements the FRTL literature, especially regarding SCG as a determinant that is being introduced for the first time in Islamic banking.


extfieldsofstudy: Geography Medicine

text:
Rare and extreme events: the case of COVID-19 pandemic

Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.

Introduction
Many complex systems generate outputs that are characterized by a frequency-size power law behavior over several orders of magnitude [1,2]. The power laws have been associated with scale-invariance, self-similarity, and fractality and are consistent with self-organized criticallity, that is a process in which a system, by itself, converges to a state characterized by a coherent global pattern, created by local interactions between low-level elements [3,4].
The power laws are characterized by heavy-tails, giving non-negligible probability to large events. However, some extreme events, labeled 'dragon kings', while predictable, cannot be foreseen by the extrapolation of power law distributions [5,6]. 'Dragon kings' may be associated with positive feedback, bifurcations, and regime changes in out-of-equilibrium complex systems. 'Dragon kings' are often discussed in contrast with 'black swans', which denote unpredictable catastrophic rare events [7]. These outliers are pervasive in many areas, namely economy, finance, earth sciences, and biology.
The recent Coronavirus disease 2019 (COVID-19) outbreak is an example of an extreme event. We must highlight that the occurrence of a rare event and the actual description of its evolution are, however, distinct matters. This paper attempts to understand the dynamics of the spreading across different countries of COVID-19, but not the prediction of its outbreak or conclusion.
The first case of COVID-19 [8][9][10] was officially reported in China on December 31, 2019, in Wuhan of Hubei province. At an early stage, the Chinese authorities seemed not to give importance to the problem. However, with the rapid emergence of new cases, the attitude changed dramatically. The Chinese government took a series of strong measures to contain the disease and gave the world an example of commitment and effectiveness. The growth rate of new cases of COVID-19 in China has slowed significantly, and the situation appears to be under control at the moment of writing this paper [11,12].
In the meantime, new cases have been emerging in many countries. In particular, the rapid evolution in Iran, South Korea, Italy and Spain became the most dramatic cases. COVID-19 was gradually reaching all continents, with cases confirmed all over the world, while having 'alarming levels of inaction' by some countries, in the words of the director of the World Health Organization (WHO).
More recently, by March 11, 2020, WHO officially declared the COVID-19 a global pandemic, just when the number of known cases reached approximately 121,000 and caused 4300 deaths, and after the cases outside of China spread by a factor of 13 and the number of countries affected tripled in just two weeks.
Panic begins to spread in some populations [13], fueled by the massive and speculative news broadcast by the media and social networks. World governments have taken drastic measures, such as closing schools, entertainment venues and restaurants, and the movement of people has slowed dramatically, in parallel with thousands of canceled flights [14]. The tourism sector and commercial flights are the most affected and the world seems to be heading towards an economic recession, with the GDP of some countries being able to drop double-digit figures.
No one can say whether the measures being taken are sufficient [15], or what the evolution of the pandemic will be, but this appears to be the public health crisis of a generation. However, we cannot forget that, for example, the H1N1 flu of 2009 caused between 151,000 and 575,000 deaths worldwide [16]. The COVID-19 has still a long way to go to reach the H1N1 levels. The world faced other flu pandemic crises in the past [17] and the scientific knowledge has never been so well prepared as today to give appropriate answers to health crises.
The analysis of the evolution of the confirmed cases versus time has considerable interest from the point of view of delivering good information to health organizations and to the general public. Several statistics have been presented, adopting different forms for organizing and visualizing the data. However, a comprehensive representation of the COVID-19 spreading dynamics across different countries is still missing.
In epidemiology, mathematical modeling plays an important role in understanding the mechanisms that govern the transmission of contagious diseases. The work by Kermack and McKendrick [18] formulated the general theory of susceptible-infected-recovered (SIR). A SIR model involves a system of coupled equations relating the numbers of susceptible, infected and recovered people over time, and computes the theoretical number of infected people in a closed population. Many variations of the original SIR model were proposed, such as the susceptible-infectious-susceptible (SIS) and the susceptible-exposed-infectious-recovered (SEIR), based on ordinary [19], stochastic [20] and fractional order [21,22] differential equations. These recent versions were adopted for studying the spread of distinct infectious diseases [23,24], including the COVID-19 [25]. However, the main concern of such approach is the model validation, since it requires to compare the results with real data. Contrary to modeldriven, data-driven approaches rely on data series for deriving adequate fitting functions. These heuristic models describe well one stage of the epidemic, but fail when the disease evolves toward a different phase. We must also note that the heuristic model is useless in the initial epidemic phase, due to insufficient data [26,27].
The paper addresses the statistical comparison and visualization of COVID-19 country reported cases in the period December 31, 2019, up to April 12, 2020. The study does not aim to be a contribution tailored for medical treatment or prevention of the disease. Therefore, in a first phase, we adopt a nonlinear least-squares technique to determine possible candidate heuristic models for describing the data regarding COVID-19 infections. In a second phase, we use distinct metrics for processing the data both in the time and frequency domains. The information is visualized using hierarchical clustering (HC) and multidimensional scaling (MDS) for comparing the COVID-19 evolution in the different countries. The HC and MDS generate loci of Fig. 1 Geographic map of the COVID-19 spread for 165 countries. The color map is proportional to the number of days elapsed since the occurrence of the first case for each country for the period of time τ points in 2-and 3-dimensional spaces representing the number of infections for each country. The positioning and the patterns formed by the points lead to direct interpretations of the results. The study is data-driven, and the models are applicable only at some stages of the outbreak and when enough data points are available.
In this line of thought, the paper is organized as follows. In Sect. 2 we introduce the dataset adopted in the follow-up. In Sect. 3 we analyze the data by means of regression modeling. In Sect. 4 we compare and visualize the COVID-19 spreading data in various countries. In Sect. 5, we discuss the possibility of foreseeing the future evolution. Finally, in Sect. 6 we discuss the results and summarize the main conclusions.

The dataset
The COVID-19 data are made available by the European Centre for Disease Prevention and Control (https:// www.ecdc.europa.eu/en). The dataset is provided in Excel format, containing the number of infected and the number of deaths for each country, on a daily basis. Data for the period from December 31, 2019, up to April 12, 2020, were collected for analysis. This period of time will be denoted as τ henceforth. Figure 1 depicts a geographic map where the colormap is proportional to the number of days elapsed since the occurrence of the first case in each country. We verify that the COVID-19 is particularly severe in the northern hemisphere and, thus, seems not to follow the same pattern of other serious diseases that affected mainly the underdeveloped countries. Therefore, some possible synchronization between countries, or, even, the emergence of new waves of spread in the future are still unclear and techniques such as the Kuramoto model [28] for assessing that hypothesis should be considered.
Let x i (t) denote the time series of confirmed COVID-19 daily infections for the ith country, i = 1, . . . , M, where t = 1, . . . , T represents time with one day resolution, within the time interval τ . Therefore, the signals x i (t) evolve in discrete times, t, and can be interpreted as one manifestation of a complex system.
For the sake of statistical significance and accuracy of the mathematical tools used for processing the data, we just consider the countries with time and we approximate the histogram of r i (t) by a symmetric α-stable distribution [29]. We recall that a probability distribution (PD) (and the corresponding random variable ξ ) is said to be 'stable' if a linear combination of 2 independent random variables with such PD has also an identi-cal PD, up to the scale and location parameters, c and μ, respectively [29,30]. A given family of stable distributions is often called Lévy alpha-stable distribution, after Paul Lévy [31]. The Lévy, Gaussian and Cauchy PD of a random variable ξ are particular cases of the α-stable distribution family with the parameter value α = 1 2 , 1 and 2, respectively [32]. The α-stable distribution is a four parameter family of distributions and is (usually) denoted by S(α, β, c, μ). The first parameter α is of particular relevance and describes the tail of the distribution. We have α ∈ (0, 2] for the stability (or characteristic exponent), β ∈ [−1, 1] representing the skewness, c ∈ (0, ∞) standing for the scale, and μ ∈ (−∞, +∞) for location parameters. With exception  Fig. 2 The histogram of the the log returns r i , i = 14, and αstable approximation, with tail characteristic exponent α = 0.26, for China during the period τ of the cases when α ≤ 1 and β = ±1, we have that for α < 2 the asymptotic behavior is described by [33,34]: where Γ denotes the Gamma function. We verify the presence of the so-called heavy or fat tails that cause the variance to be infinite for α < 2. Figure 2 depicts the histogram and the α-stable approximation for China, r 14 , in the period τ . Twelve bins were considered for having statistical significance. In this case, we have approximately f (r ) ∼ 1/|r | 1.26 , that is, α = 0.26 corresponding to an extremely small value, which entails a huge probability for extreme values of the return. The alternative of an asymmetrical PD was tested, but the resulting improvement was minor and by consequence merely the symmetrical version is depicted for the sake of simplifying.

Regression models for describing the spread of COVID-19
Let y i (t) represent the time series of cumulative number of infections of x i (t), that is y i (t) = t n=1 x i (n). We adopt the nonlinear least-squares [35,36] to examine the behavior of y i (t) for a variety of functions. We selected the 'Logistic' and 'Richards' models: for approximating the data of China (i = 14) and Italy (i = 36), respectively, where a, b, c, d ∈ R are parameters adjusted by means of a nonlinear least square fit numerical algorithm. These models were selected from a large number of heuristic functions simply because they (i) adjust adequately to real data, and (ii) involve a limited number of parameters. Therefore, no special biological meaning was intended when using such functions. Figure 3 illustrates the data time series, y 14 (t) and y 36 (t) and the corresponding approximationsŷ 14 We verify a good fit in both cases, with coefficient of determination R 2 = 0.99, but a single model with limited number of parameters is not able to fit well the time seriesŷ i (t) for all countries. Obviously, we can adopt other models involving a larger number of parameters for achieving a better fitting to a givenŷ i (t). Nonetheless, only analytical expressions requiring a limited set of parameters are of relevance [37]; otherwise, their comparison and interpretation becomes unclear. On the other hand, the use of distinct models for different countries lack generality when comparing results.

Global comparison of the COVID-19 spreading
We now analyze the COVID-19 spreading data of M = 79 countries both in the time and frequency domains. In the time domain, we compare the pair (i, j) of countries by the corresponding time series of the cumulative In the frequency domain, the pairs of countries are compared by the daily number of infec- . . , ω K , F{·} denotes the Fourier transform, ω represents the angular frequency and ı = √ −1. We adopt the Canberra distance to measure the dissimilarity between pairs (i, j) for the time and frequency domains: Real data Fitting model that is, distances based on the variables y i (t) = t n=1 x i (n) and X i (ıω), respectively, where Re{·} and Im{·} denote the real and imaginary parts. The Canberra distance has the relevant property of being relatively insensitive to the simultaneous presence of large and small values.
Obviously, other distances are possible [38] and several of them were also tested. However, further distances are not included herein for sake of parsimony, since d t,y C i j and d f,X C i j illustrate adequately the proposed concepts.

Hierarchichal clustering and visualization of COVID-19
For visualizing the relationships between the 79 countries, we first adopt the HC computational approach. The HC is a technique that groups similar objects [39]. Given M objects in a q-dimensional real-valued space and a dissimilarity metric, . . , M, of object to object dissimilarities is determined [40]. The HC generates a structure of object clusters, using Δ as input, that is represented graphically either by a hierarchical tree or a dendrogram. We have two alternatives to generate a hierarchy of clusters, namely the agglomerative and divisive clustering iterative techniques. In the first, each object starts in its own cluster and the successive iterations merge the pair of most similar clusters until there is a single cluster. In the second technique all objects start in one cluster and, during the iterations, the 'outsiders' are removed from the least cohesive cluster, until each object is in a separate cluster. In both cases the HC requires a linkage criterion, that is a function of the distances between pairs of items, for quantifying the dissimilarity between clusters. Metrics such as the maximum, minimum and average linkages are often used. The distance d (x R , x S ) between two objects x R ∈ R and x S ∈ S, in the clusters R and S, respectively, can be assessed by means of several metrics such as the average-linkage given by [41]: For assessing the clustering quality, the index cc is mostly used [42]. Let us consider that the original object X i is described by a HC representation T i . Additionally, let x(i, j) and t (i, j) stand for the the distances between the X i and X j original observations and the HC points T i and T j , respectively. If we havex = av (x (i, j)) andt = av (t (i, j)), where av(·) denotes average, then cc is given by: The closer the value of cc is to 1, the better the clustering reflects the original data. The results are represented in a Shepard chart that compares the original and the cophenetic distances. The closer to the 45 degree line the points, the better the obtained clustering. For example, in MATLAB, the cophenetic correlation coefficient can be obtained by means of the command cophenet.
Herein, the agglomerative clustering and averagelinkage method are adopted for visualizing the two resulting matrices of item-to-item distances based on Eqs. (5) and (6), respectively [43].
In Fig. 4, we see a clear position of China followed by the sub-cluster formed by Iran, Italy, Spain, Korea, United States, France and Germany. On the other hand, the tree based on the frequency response gives more importance to a sub-cluster formed by the United States and China, followed by a second group including United Kingdom, Italy, Germany, France, Spain, and Iran. Moreover, the second tree separates better those countries with a smaller impact from the virus spread. In Fig. 4, the countries with a smaller (larger) number of occurrences and a smaller (larger) number of days since the first case are to the left (right). In Fig. 5, the distribution for smaller (medium/larger) values is located on the right (left/middle bottom) sides. Figure 6 represents the Shepard plot for assessing the HC tree for the 74 countries and the item-to-item dissimilarities d t,y C i j . The chart reflects an accurate clustering of the original data. For the index d f,X C i j , the Shepard plot is identical to the one in Fig. 6 and, therefore, is not presented.

Multidimensional scaling and visualization of the COVID-19 dataset
The MDS is a computational technique for clustering and visualizing multidimensional data [44]. As for the  We have several variants of the MDS, such as the metric, non-metric and generalized MDS. In the case of the metric MDS, the iterative algorithm minimizes the stress cost function S. We can have for example the residual sum of squares: The Sammon criterion can be also adopted The MATLAB command cmdscale and stress criterion Sammon were adopted. The interpretation of the MDS locus is based on the patterns of points. Similar (dissimilar) objects are represented by points that are close to (far from) each other. Therefore, the information retrieval is not based on the point coordinates, nor the shape of the clusters. This means that it is possible to magnify, translate and rotate the MDS locus. The axes of the MDS plot have neither units nor a special physical meaning. The quality of the MDS can be assessed through the stress and Shepard diagrams. The stress chart represents S versus d. The plot is monotonically decreasing and choosing a given value of d is a compromise between obtaining low values of S and d. The values d = 2 or d = 3 are usually adopted, because they allow a direct representation. The Shepard diagram compares φ i j and δ i j for a given value of d. A narrow scatter represents a good fit between φ i j and δ i j . Figures 7 and 8 depict the 3D MDS maps for d t,y C i j and d f,X C i j , respectively, for the period τ . As before, the size of the dots is proportional to the logarithm of the number of infections (i.e., ln[y i (T )]) and the color is proportional to the time between the first reported case in each country and T . The clusters are the same obtained with the HC, however, for their clear visualization we need to rotate the 3D maps.
As for the HC we verify that the time domain approach makes a better distinction of the countries with a larger number of infections, while the MDS based on the frequency domain has a more eclectic distribution, that is with a larger dispersion, and leaves some room for distinguishing the countries with a smaller number of infections. In both figures, the countries to the left (right) have a smaller (larger) number of infections and more (less) time elapsed since their first case in each country.   when varying time [40,[45][46][47][48]. Procrustes is a statistical method that takes a collection of shapes and transforms them (using translation, rotation, and amplification/reduction of size) for maximum superposition. The comparison is performed for a shorter period of time τ from t = 40 up to t = T , so that there is significant non null data for the analysis.
Let y c (t), c = 1, . . . , 16, denote the data time series representative of the countries in C for periods of time starting at t = 40 and increasing up to k ≤ T . The individual 3D MDS maps (one for each value of k) are generated using the item-to-item dissimilarities d t,y C i j and d f,X C i j , and processed with Procrustes. We must note that we are now using T − 39 matrices Δ of dimension 16 × 16. Therefore, the MDS locus produced for each k is not a magnification of the previous charts. For each index, the collection of MDS maps yields one global chart (Figs. 10, 11, respectively) that represents world recent evolution of the COVID-19. We verify different behaviors of the time and frequency domains MDS loci being, apparently, slightly more representative the first. In Figs. 12 and 13, we redraw the MDS charts of Figs. 7 and 8 (for the initial period of time τ ) with a connection between those countries that lie close to each other in the MDS locus [49]. Therefore, the lines do not represent clusters, and, instead they indicate that in the near future the evolution of a given country will probably be similar (in the sense of the adopted distances) to the neighboring countries. We observe also some discontinuities in the lines. Again they do not represent different clusters. The discontinuities simply mean that some neighbor is closer than the other and, therefore, it is likely that its evolution is closer.

Is it possible to foresee?
It is written 'The future belongs to God, and it is only he who reveals it, under extraordinary circumstances' [50]. To the authors best knowledge, the HC and MDS techniques are not designed to make predictions. Indeed, they allow a better interpretation of the past and present. Nonetheless, we can take advantage of the MDS computational visualization to trace some similarities between the items represented in the loci. From Figs. 10 and 11, where time is a parametric variable, we verify that we do not obtain our intuitive feeling of time as a smooth and continuous variable embedded and synchronizing all events. In fact, we see that the time instant for the beginning and end of the trajectories vary considerably from country to country. Therefore, if we adopt a critical view we can interpret that the 1-dimensional time continuum (if exists) is not adequately represented by the two technique combination (i.e., MDS and Procrustes). However, it was already noticed in previous studies [51,52], addressing a distinct phenomenon and applying only MDS, that datasets under the influence of social and human factors phenomena exhibit a relativistic behavior and eventually different velocities. Let us name the 'relativistic time' to make it distinct from the standard notion of constant speed physical time.
Let us consider the Canberra and Lorentzian distances [38] to measure the dissimilarity between the pairsx i (t) andx j (t): wherex represents the ith vector of N consecutive values of x(t) obtained from non-overlapping time windows. Therefore, the time series is subdivided into identical periods of time giving rise to R = T /N windows, where · denotes the integer part of the argument. Obviously, the larger the width of the window the better the filtering, but the weaker the notion of time 'instant'. Now, the MDS has for input a matrix Δ of dimension R × R and produces a single locus that compares the set of N -dimensional R vectors, corresponding to the different time windows. The MDS with MATLAB command cmdscale was adopted. We verify again the emergence of areas involving a large variability, coincident with large transients, and zones with a smoother evolution, corresponding to a continuous dynamics. In both cases we observe clearly four phases: (i) an initial transient, (ii) a fast progress up to a peak, (iii) a return back (but not exactly to the initial state), and (iv) the emergence of a new, unclear, second wave. As usual with the MDS technique the distinct measures highlight different aspects but the overall conclusions are similar.
For estimating future outcomes we now propose a technique embedding the trendline and the MDS datadriven techniques for estimating the evolution. In what follows we adopt the case of Italy (i = 36) as our test bench and we shall tackle the values of the number of daily infections x i (t). The main idea is to fit a set of trendlines to the available data and, based on them, to extrapolate the future behavior. In a second phase we adopt MDS to compare the real-world data and the estimations provided by the trendlines.
We consider four models, namely the 'Hoerl', 'Reciprocal quadratic', 'Gaussian' and 'Vapor' given by: respectively, where a, b, c ∈ R are parameters and t ∈ τ . We emphasize again that these models have no specific meaning and are just some functions that fit adequately the available data. In fact, the proposed heuristic models follows the common sense that number of infections will diminish in the future. However, these trendlines are just for estimating the near future and we shall consider M 1 and M 3 as representing a 'optimistic' scenarios, while M 2 and M 4 stand for 'pessimistic' future outcomes. Moreover, models M 1 , M 2 and M 4 have an asymmetric evolution about the peak, while M 3 con-  Figure 15 represents the curve fitting for the period τ and an estimation up to an extended period of time τ = 80 days.
For assessing the quality of the estimations we compare the real data and the results provided by M j , j = 1, . . . , 4, for Italy using the Canberra and the Lorentzian distances defined previously in (11)- (12). As before, the heuristic models cover an extended period of τ = 80 days for providing an estimation of the near future. We adopt the stress S for assessing the conformity between the data and the trendlines including their estimation. The MATLAB command cmdscale and stress criterion Sammon were adopted. Figure 16 depicts the stress yielded by the MDS loci generated by the Canberra and the Lorentzian and the models M j , j = 1, . . . , 4 for the case of Italy.
We verify that for d = 3 the models M 2 and M 3 are superior when considering the Canberra distance. However, the models M 1 and M 3 are superior in the perspective of the Lorenzian distance. Figures 17 and 18 show the resulting MDS loci for the Canberra and the Lorenzian distances for the two best models in each case.
The Lorentzian distance is more sensitive and gives more space to the artifact represented by the value x 36 (t = 23) = 90 (the neighbor values are x 36 (t = 22) = 2547 and x 36 (t = 24) = 6230), but, on the other hand, shows more clearly the recent final phase. The Gaussian model, M 3 seems a good compromise between the two distances and produces a trajectory consistent with the data series without exhibiting acceleration/deceleration time periods distinct from those available at the time of writing the paper. Nonetheless, the authors highlight that the COVID-19 evolution has an underlying plethora of phenomena going from cultural and economical up to political and geographical issues. As someone said, 'Prediction is very difficult, especially if it's about the future' [53].

Conclusions
This paper investigated an example of an extreme event, namely the dynamics of the COVID-19 spreading. Two approaches were considered for the period from December 31, 2019 up to April 12, 2020. In a first phase, heuristic models were used to fit the time series of the number of infections verified in a set of 79 countries. In a second phase, two metrics were used for comparing the countries data both in the time and frequency domains, and the HC and MDS techniques were adopted for clustering and visualization. The time evolution was also considered for a group of countries exhibiting a more dramatic spread of the COVID-19. The combination of Procrustes and MDS showed that besides the number of infections, the dynamic characteristics play an important role that is not evident in standard representations. In fact, the computational and mathematical modeling lead to the emergence of patterns both highlighting the main clusters and the similarities or dissimilarities between them. Given the potential of the techniques discussed here we can think of their application in several research directions such as the subdivision of data sets according with distinct criteria such as the age, or the geographical origin of the patients. Additionally, analysis considering a large set of influential factors besides merely the casualties can be tried, such as infected people staying in general or in intensive care in hospital, or recovered based on some type of treatment. Therefore, if sufficient and assertive information is collected, then research can follow the aforementioned computational methods to unravel space and time nonlinear dynamics embedded the data.