Web-Based Expert System for Human Skin Disease Diagnosis Using Forward Chaining and Mamdani Fuzzy Inference - Muhammad Khadafi; Muhammad Faisal; Muhyiddin AM Hayat; Muh. Arief Muhsin; Muhammad Syafaat S.Kuba; Lukman Anas; Andi Makbul Syamsuri (Jurnal Teknik Informatika (Jutif), 2026)
This paper aims to develop a web-based expert system aimed at assisting the general public and parties involved in the health sector, particularly in the field of human skin diseases. This system uses a combination of forward chaining and Mamdani fuzzy inference methods. The knowledge base is created based on observations and interviews with a dermatologist at Bima Regional General Hospital, covering 13 symptoms and 6 types of skin diseases, each equipped with expert confidence weights. Disease candidates are inferred from symptoms selected by the user and rules using forward chaining, while symptom weights are managed through fuzzy logic using the Laravel framework with the PHP language. From 20 test data, a comparison between the results from doctors and the system in an operational web application model shows a compatibility level of 95%. This system is suitable for use by doctors with further review. With this application, it is hoped that it can solve problems experienced by the community, such as limited access to dermatologists and economic problems, which are some of the main reasons why this application was designed and developed.