Expert System for Diagnosing Personality Disorders Using Forward Chaining and Certainty Factor Methods

Abstract

This study aims to develop a web-based Expert System for Diagnosing Personality Disorders using Forward Chaining (FC) and Certainty Factor (CF) analysis methods, along with the Extreme Programming (XP) system development method. This system is designed to assist Mental Health Professionals and Patients in diagnosing Personality Disorders. The Forward Chaining (FC) and Certainty Factor (CF) methods were chosen as they are suitable for drawing conclusions and determining certainty based on existing facts, while the Extreme Programming (XP) system development method was selected for its ability to provide rapid responses to changing user requirements and produce high-quality software. The development of the web-based Expert System for Diagnosing Personality Disorders has successfully resulted in an efficient, effective, and high-quality system. Every process, from designing UML diagrams including UseCase Diagrams, Activity Diagrams, Sequence Diagrams, and Class Diagrams, was successfully completed up to the design of input and output processes. The results of this study indicate that the Expert System for Diagnosing Personality Disorders has successfully met the needs of Mental Health Professionals and Patients and possesses high quality. The system has undergone comprehensive testing and is free from bugs. Implementation trials within the local community demonstrate that this system is beneficial and can help improve efficiency and effectiveness in diagnosing Personality Disorders.