Expert System for Diagnosing Phone Damage with Repair Shop Recommendations Using CF Method - Willyadam Saad As’saidy; Fajar Novriansyah Yasir; Tri Bondan Kriswinarso (Brilliance: Research of Artificial Intelligence, 2025)
Based on observations conducted by the author through interviews at one of the repair shops in Palopo City, the owner—Zul, in 2024—stated that repair shops tend to direct mobile phone users to other shops when the type of device damage cannot be handled by their own repair shop. This reflects a lack of a centralized diagnostic system that can accurately identify damage and recommend the appropriate service provider. In response to this issue, this study aims to develop an Android-based expert system application for diagnosing mobile phone damage, equipped with a responsive and location-aware repair shop recommendation feature using the Certainty Factor (CF) method. The application was built using the 4D development model (Define, Design, Develop, Disseminate) and utilizes the results of observations, literature reviews, and interviews with local technicians to form its knowledge base and rule sets. The diagnosis process is carried out by calculating the confidence value between selected symptoms and corresponding damage types using a combined CF formula, such as CFcombine = CF1 + CF2 × (1 – CF1). This allows the system to measure the degree of certainty with which a particular diagnosis can be made. User testing involving target users showed a high level of feasibility and satisfaction, with a System Usability Scale (SUS) score of 82.5, falling into the “Acceptable” and “Good” categories. The application has proven effective in identifying various types of device damage and providing accurate, real-time repair shop recommendations based on both user location and the type of damage detected. This offers a relevant and practical digital solution for the community in Palopo City.