Implementation of the Bayes Method for diagnosing tuberculosis

Abstract

Tuberculosis is an infection caused by acid-resistant bacilli or an infectious disease that can attack anyone through the air is also a dangerous infectious disease besides it is also a chronic or chronic disease that can strike between the ages of 15-35 years. The purpose of this study is to help prevent tuberculosis by implementing an expert system using the Bayes method. The method used in this research includes identifying problems faced in the medical world for treating tuberculosis, analyzing the problem, then formulating the problem and applying an expert system with the Bayes method to solve the problems that are obtained, the next stage is designing an application as needed, testing the application with the aim of knowing the success rate of the system. The implementation of the Bayes method in diagnosing tuberculosis is found. The result is that the calculation process using the Bayes method is based on the symptoms experienced by the patient. It can be seen that the patient is "most likely" to have pulmonary tuberculosis with a confidence value of 0.64 or 64%. From the results of the research conducted, it can be concluded that in diagnosing Tuberculosis by using the Bayes method expert system, it can help medical parties handle cases more quickly in terms of recognizing the symptoms of Tuberculosis so that people quickly know the disease they are experiencing.