An Expert System for Detection of Diabetes Mellitus with the Forward Chaining Method - Tati Mardiana; Ega Maulana Ditama; Tuslaela Tuslaela (Jurnal Riset Informatika, 2020)
In recent years, diabetes mellitus in Indonesia has become a health problem in the community because its population has increased 2-3 times faster than in other countries. Diabetes prevalence in Indonesia ranks 4th highest globally after China, India, and the United States. People can prevent complications and premature death if they detect early symptoms of diabetes. However, people do not know that they are at risk of diabetes and do not have knowledge about the symptoms of diabetes, the complexity of the process of diagnosis, and the high cost of examinations. Therefore, we need an application that can provide the results of the type of diabetes and its management solutions as practiced by experts. This research aims to develop an expert system for detecting types of diabetes such as type one diabetes, type two diabetes, neuropathy diabetes, diabetes retinopathy, and diabetes nephropathy. The object of this research is diabetes, which was carried out from March to April 2019 in the Klinik Pratama Desa Putera. This study uses primary data from patients with a history of diabetes at Klinik Pratama Desa Putra and secondary data from literature, research journals, and data documents needed to compile this study. In addition, we generated a knowledge base using forward chaining. The test results show that the expert system meets the functional requirements, and the system performance reaches an accuracy of 100%. This expert system helps people in Indonesia to detect diabetes early so that it can prevent complications.