Expert System for Diagnosis of Diphtheria Disease Using Fuzzy Logic

Diphtheria is an infectious disease that affects the upper respiratory system and throat, arising suddenly and caused by Corynebacterium diphtheriae. The symptoms of diphtheria such as fever, swollen neck and slimy nose are often interpreted as influenza or laryngitis. Diphtheria is a contagious and deadly disease that requires specialized and rapid treatment and care. In today's technological era, it can be overcome with a system that can diagnose diphtheria like a doctor's diagnosis ability commonly called an expert system. This study describes the application of an expert system to diagnose diphtheria disease. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The method used to process input values is Forward Chaining. Fuzzy Tsukamoto to calculate the input value from the user. The research has been tested with Blackbox testing showing the results that the expert system works well and accuracy testing with 92% results. The results show effectiveness with a satisfactory level of accuracy in detecting diphtheria disease. This research contributes to the development of expert systems in the health sector with a focus on diagnosing diphtheria disease using a fuzzy logic approach.