Application of Tsukamoto Fuzzy Logic in Expert System Application for Diagnosing Web-Based Skin Diseases - KN, Nurwijayanti; Rasna, Rasna; Ismail, Rima Ruktiari; Sugiharto, Agus; Nugroho, Fifto (Malikussaleh University, Aceh, Indonesia, 2025)
Skin health is essential for everyone. In addition to supporting someone who can reduce self-confidence, skin diseases can also interfere with a person's concentration in activities. An expert system is a system designed to be able to imitate the expertise of an expert in answering questions and solving a problem. The expert system will solve a problem obtained from a dialogue with the user. With the help of an expert system, someone who is not an expert can answer questions, solve problems, and make decisions that an expert usually makes. This needs to be anticipated and handled seriously, especially for types of skin diseases, some of which can be fatal, and some can even be classified as cancer. Experts are needed to diagnose each disease in this case, but consultation with experts requires costly funds. For this reason, this system is designed to help people diagnose skin diseases online, making it easier for sufferers to diagnose the diseases they suffer from by themselves. The method used is the fuzzy Tsukamoto method. Analysis of the introduction of the disease is carried out by identifying various symptoms of the disease. The types of diseases diagnosed include tinea versicolor [P001], scabies [P002], ringworm [P003], dandruff [P004], vitiligo [P005], pityriasis alba [P006], hives [P007], erythema multiforme [P008], acne [P009], keloids [P010], melanoma [P011], eczema [P012], boils [P013], measles [P014], psoriasis [P015], impetigo [P016], and herpes [P017]. Skin disease sufferers can diagnose their disease without consulting with a specialist directly. This system can be used as a substitute for a specialist in producing a diagnosis in the form of the name of the disease suffered by the system user (user). This system provides a solution for users regarding more economical disease diagnosis.