Sistem Pakar Diagnosis Penyakit Gigi

Abstract

Dental and oral diseases are common health issues affecting many individuals. Regular check-ups are essential for early detection and treatment, but high costs, long waiting times, and fear of pain often discourage people from visiting dentists. To address these concerns, this study developed an expert system using the forward chaining method to help diagnose dental and oral conditions. This approach enables the system to trace symptoms, identify possible diseases, and recommend appropriate treatments. The system was developed using a prototyping approach, with data collected through observation, interviews, and literature reviews. It focuses on three key variables: symptoms, disease types, and treatment recommendations to provide an initial diagnosis. Testing was conducted using black box methods and user evaluations. Results indicated that all system features performed as expected during black box testing. An expert who evaluated the system reported complete satisfaction (100%) with its functionality. Among ten general users, 66% found the diagnoses to be accurate, while 34% were reasonably satisfied. These findings suggest that the expert system for diagnosing dental and oral diseases is effective and reliable. It can assist individuals in making preliminary diagnoses before visiting a clinic, potentially reducing the burden on healthcare facilities and enhancing service efficiency. Future research should focus on expanding the system's database of symptoms and disease types and incorporating artificial intelligence for improved decision-making capabilities.