Implementasi logika fuzzy mamdani dan simple additive weighting (saw) pada sistem pakar berbasis web untuk deteksi dini gangguan neurologis - Harits, Muhammad Harits Firdaus; Thohir, Muhammad Ikhsan; Sujjada, Alun (Universitas Muhammadiyah Riau, 2025)
Neurological disorders such as low back pain, vertigo, ischemic stroke, epilepsy, and peripheral neuropathy affect the central and peripheral nervous systems and have the potential to reduce quality of life and be fatal if not detected early. In Indonesia, the high prevalence is not balanced with access to early diagnosis due to limited medical personnel, costs, and waiting times. This study developed a web-based expert system for early detection of five neurological disorders using the Mamdani Fuzzy Method for inference and Simple Additive Weighting (SAW) for symptom ranking. The diagnosis process includes fuzzification, rule evaluation, aggregation, centroid defuzzification, and SAW calculation. The system was tested through black box testing and accuracy evaluation using MAE, RMSE, and F1 Score. The results showed an MAE value of 2.8%, RMSE 2.83%, and F1 Score 0.75, which proves the system is accurate, consistent with manual calculations, and easy to use. With a user-friendly interface, this system has the potential to be a pre-diagnosis tool that increases public awareness and supports medical personnel in decision-making.