Gastric Disease Diagnostic Expert System Application Using the Fuzzy Mamdani Method

Abstract

The level of awareness among Indonesian society regarding the importance of maintaining gastric health is still very low, even though gastric diseases can significantly disrupt daily activities. In a medical examination, a doctor detects diseases in a patient's body based on their symptoms or complaints. The patient's action is to meet the doctor in person, and the doctor asks about the symptoms experienced by the patient. In the manual system, there is a drawback where patients have to visit the doctor for consultation or to have their diseases examined, and they also need to prepare the necessary fees for the examination. Such a manual system can be simplified with an information system where patients don't need to visit the doctor to diagnose their diseases. Therefore, the researcher will develop a gastric disease diagnostic expert system application using the fuzzy Mamdani method. The aim is to make it easier for patients/the public to identify the type of disease based on the symptoms experienced, as well as to provide information on solutions, actions, and medication for the disease. The methodology used in developing the gastric disease diagnostic expert system application involves four stages: fuzzification process, implication function, inference process (rules), and defuzzification. The research flow includes data collection through interviews and data sampling, data analysis, calculation using the fuzzy Mamdani method, implementation, and testing using a black box. The result of this research is a gastric disease diagnostic expert system application using the fuzzy Mamdani method with an accuracy of 65%. This application can help individuals to identify the type of disease based on the symptoms experienced without having to immediately consult a doctor, thus avoiding potential issues