ABSTRACT
Tuberculosis (TB) is an infectious disease caused by the Mycobacterium tuberculosis germ and easily transmitted through the air. Tuberculosis mostly attacks human organs such as the lungs, kidneys, intestines, and clear glands. Based on data from the RSUD Ungaran that examined patients at Ungaran Hospital, a lot of the disease that occurs in the city of Ungaran itself is TB. Another concerning piece of data reveals that the neonatal mortality rate in Semarang Regency in 2014 was 8.15 per 1,000, or as many as 74 cases. In response to these data, this study aimed to develop a TB diagnosis expert system for Ungaran using Bayes’s theorem and a forward chaining algorithm. An expert system seeks to adapt human knowledge to computers so that computers can solve problems as human experts do. This expert system uses Bayes’s theorem for calculating the probability value, and the forward chaining algorithm to produce a conclusion. This expert system is useful for diagnosing TB earlier, which can make it easier for sufferers to get proper treatment.
