Sistem Pakar Diagnosa Gejala Awal Computer Vision Syndrome Menggunakan Metode Certyanty Factor

Computer Vision Syndrome (CVS) is an eye health disorder caused by excessive use of digital devices and is characterized by symptoms such as eye strain, dry eyes, headaches, and blurred vision. The low level of public awareness regarding eye health and the limited access to eye care services, particularly in the Bengkalis region, highlight the need for an easily accessible early detection solution. This study aims to design and develop a web-based expert system capable of diagnosing the early symptoms of Computer Vision Syndrome (CVS) based on the symptoms experienced by users. The Certainty Factor (CF) method is employed to handle uncertainty in symptom data and to produce a confidence level for the diagnostic results. Symptom data and CF values are obtained through expert interviews and literature review. System testing is conducted using Blackbox Testing to evaluate system functionality, as well as accuracy testing by comparing the system’s calculation results with manual expert calculations. The accuracy testing results indicate that the system achieves an accuracy rate of 85%, demonstrating that the developed expert system is able to provide accurate early diagnosis of CVS and can be utilized as a decision support tool for the early detection of Computer Vision Syndrome.