MYERS-BRIGGS TYPE INDICATOR (MBTI) PERSONALITY TEST EXPERT SYSTEM USING BAYES THEOREM AND CERTAINTY FACTOR METHOD COMPARISON

Abstract

The Myers-Briggs Type Indicator (MBTI) is a method for understanding human personality in perceiving the world and making decisions. Identifying a person's personality requires an expert to provide guidance. An expert system is a form of artificial intelligence that adopts expert knowledge (psychologists) to generate information about MBTI personality types. The certainty factor method provides an expert's confidence level, while the Bayes theorem helps manage uncertainty from user input. This research aims to help users recognize their personality to make better future decisions. Based on testing, the system delivers information on MBTI types, their characteristics, and suggestions. From 16 system tests, the certainty factor method achieved an accuracy rate of 100%, higher than the Bayes theorem method, which reached 12.50%. Thus, the certainty factor method is concluded to be more accurate for this MBTI personality test expert system.

Keywords: Expert System, Myers-Briggs Type Indicator (MBTI) Personality Test, Certainty Factor, Bayes Theorem