Expert System for Diagnosing Gastric Diseases with the Application of the Fuzzy Logic Sugeno Method (Case Study: Delia General Hospital)

Stomach diseases, such as gastritis, GERD, and gastric ulcers, are digestive disorders with a high prevalence and have the potential to reduce the quality of life of sufferers. Conventional diagnosis still faces obstacles, including limited medical personnel, the length of examination procedures, and the similarity of symptoms between diseases. This study developed a web-based expert system with the Fuzzy Logic Sugeno method to assist in the early diagnosis of gastric diseases. Symptom data was obtained from literature and consultation with specialist doctors at Delia General Hospital. The system is designed with the stages of needs analysis, UML modeling, database design, and the implementation of fuzzy algorithms (fuzzification, inference, defuzzification). The simulation results showed that the system was able to provide diagnostic recommendations with a membership rate of 28% for gastritis, 62% for GERD, and 80% for gastric ulcers. The implementation of a web-based interface allows users to select the symptoms they are experiencing, then the system displays the results of the diagnosis along with their severity. This study shows that the Fuzzy Sugeno method is effective in handling vague symptom data, as well as acting as a consistent and efficient early diagnosis tool.