Mental Health Analysis at the University of Dipa Makassar using Naïve Bayes Classifier
DOI:
https://doi.org/10.25299/itjrd.2023.11444Keywords:
Mental Health, Naive Bayes Classification, RapidMiner, Mental Disorder, Data Mining, Data ClassificationAbstract
Maintaining the stability of our mental health as a student and keeping it healthy is one of the most important things to live a healthy mindset to become academically advanced. A good healthy mentality shall produce a positive mindset so that the body can function better emotionally, psychologically, or socially and it will affect the way of thinking. The purpose of this research is to classify mental disorders that are felt by the university students at Dipa Makassar. The results of the classification of mental disorders were carried out on 50 students at the university. 38 students were Identified as having mental disorders while the other 12 students were Unidentified as having mental disorders. Data testing performed on RapidMiner resulted in an accuracy rate of 100%. With this research, it is possible to classify mental disorders felt by the students of Dipa Makassar University
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