SOCIAL MEDIA USER PERSONALITY CLASSIFICATION BASED ON HOW USER LIVE AND MAKE DECISION

Personality classification is one of the ways in field Natural Language Processing (NLP) with a collection data that can describe user's personality through input sets text documents such as status uploads. Social media way to interact online provide convenience for users, interacting, expressing themselves, and expanding friendships. Status posts on social be extracted into useful information process. This research performs based how users live their lives make decisions, which representation "Thinkers/Feelers" "Judgers/Perceivers" class attributes Myers-Briggs Type Indicator (MBTI) model. Researchers are encouraged develop system feature extraction improve performance. In this research, there three main experiments conducted, using oversample techniques Thinker/Feelers (TF) Judgers/Perceivers (JP) classes best results compared other f1-score accuracy 92% Random Forest method Glove feature.