An Expert System for Diagnosing Leptospirosis Disease Using Forward Chaining and Bayes Theorem
Leptospirosis is the most serious zoonotic disease caused by Leptospira spp. Leptospirosis has spread throughout the world and spread more in the tropics than in temperate countries. Organisms are contained in the urine of infected animals, including rodents and pets. Humans can get this disease after contact with infected urine, or through contact with contaminated water, soil or food. This disease has several symptoms similar to other diseases such as influenza, dengue fever, typhoid fever, rickettsiosis, aseptic meningitides, hepatitis, and malaria. Similar to these symptoms make this disease a little difficult to diagnose quickly. the similarity of the symptoms of this disease to other diseases can also cause errors in diagnosing the disease, this can result in the wrong medication to be given to the patient. Slow handling can cause death to patients. Expert systems can be the solution to dealing with these problems. Expert systems can be computer software systems that use science, facts, and thinking techniques in the process of making decisions to solve problems that are usually only resolved by experts. Expert systems must be equipped with tracking techniques and mathematical calculation methods to improve the quality of diagnosis. The results of this study are combining forward chaining with Bayes theorem so that the diagnosis of leptospirosis is better.
2019 7th International Conference on Cyber and IT Service Management (CITSM)