An Expert System for Diagnosis of Rheumatic Disease Types Using Forward Chaining Inference and Certainty Factor Method

摘要

This study aims to develop an expert system using forward chaining inference and certainty factor methods in order to diagnose types of rheumatic disease. Types of rheumatic disease under investigation in this study cover Gout Arthritis, Rheumatoid Arthritis, and Osteoarthritis. These three types of rheumatic disease have been chosen because they constitute the most common ones suffered by Indonesian people. Steps in developing the expert system consist of Problem Identification aiming to analyze problem domain and functional need, Knowledge Acquisition used to obtain MB and MD values for each symptom of rheumatic diseases through experts interview, Designing used to design knowledge representation such as decision table and inference engine, Coding used to create the expert system by means of PHP programming language and MySQL database, and the last step is Testing. The result shows that the forward chaining inference and certainty factor method can be used to diagnose types of rheumatic diseases and the developed system can help experts, doctors, or doctor assistants to diagnose rheumatic diseases. In addition, the testing done using the BlackBox method shows that all functions in this expert system works in line with the functional requirement analysis. The accuracy value of this system is 80%, which means the combination of forward chaining inference and certainty factor method to diagnose types of rheumatic diseases has a good performance.