Expert System for Diagnosing Post-Flood Diseases Using the Certainty Factor Method Based on Mobile Application - David Chandra (STMIK Methodist Binjai, 2026)
The post-flood condition is a critical phase highly susceptible to disease outbreaks such as Diarrhea, Dengue Hemorrhagic Fever (DHF), Leptospirosis, Skin Diseases, and Acute Respiratory Infections (ARI). In these emergency situations, the speed and accuracy of diagnosis are determining factors for victims' safety. However, the reality on the ground shows that access to medical experts is often cut off due to damaged infrastructure, coupled with an unbalanced doctor-to-refugee ratio in disaster shelters. This study aims to develop a mobile-based (Android) expert system for post-flood disease diagnosis that can operate offline (offline-first architecture). This system applies the Certainty Factor method to handle the uncertainty of symptoms experienced by users, thereby providing an accurate percentage of disease confidence levels comparable to an initial diagnosis by a medical expert. The testing results show that the system successfully identified the five diseases with an accuracy rate of 88.5% based on 50 real-case test data. Usability testing using the System Usability Scale (SUS) yielded a score of 78, meaning the application is in the acceptable category and is easy to use by laypeople in disaster-prone areas.