Expert System to Diagnose Diseases of Mental Health with Forward Chaining and Certainty Factor

Abstract

The latest developments in the medical world use computers to help diagnoses and treat diseases. This study aims to develop an expert system which can be used to diagnose mental health problem, especially in the category of depression. User can diagnose based on the symptoms felt by patients. The knowledge representation used in this study is the production rule. The inference method used to get conclusions is using Forward Chaining the Certainty Factor method, and the platform used is a web-based system. After analyzing and applying the Forward Chaining and calculation of Certainty Factor method into the expert system, the conclusion is that the Forward Chaining and Certainty Factor methods can solve the problem of depression psychiatric diagnosis by prioritizing the value of the certainty of users and experts so that the value is close to certainty from diagnoses that are made to psychiatric illness depression.