Sahlan, Fadhluddin and Hamidi, Faris and Misrat, Muhammad Zulhafizal and Adli, Muhammad Haziq and Wani, Sharyar and Gulzar, Yonis (2021) Prediction of mental health among university students. International Journal on Perceptive and Cognitive Computing, 7 (1). pp. 85-91. E-ISSN 2462-229X
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Abstract
Mental Illness or mental disorder is defined as a health condition that changes a person’s thinking, feelings, or behaviour which can cause the person to distress and face difficulty to live normally. Unlike other diseases, mental illness doesn’t only harm the affected individual, but also others around them. Early detection of mental disorders can help to avoid severe consequences. Mental wellness issues have been largely reported in university students. This paper explores the state of student well-being and uses various machine learning algorithms for the prediction process based on the data of entrepreneurial competency in university students. The results indicate the choice of major and gender has a significant impact on a student’s well-being. Decision Tress perform better than KNN and SVM presenting an accuracy and F1-score of 0.64 and 0.61 respectively
| Item Type: | Article (Journal) |
|---|---|
| Uncontrolled Keywords: | Mental Health, Students, Decision Tree, K-Nearest Neighbors, Support Vector Machine |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science |
| Depositing User: | Dr. Sharyar Wani |
| Date Deposited: | 30 Apr 2025 15:36 |
| Last Modified: | 30 Apr 2025 15:36 |
| URI: | http://irep.iium.edu.my/id/eprint/120801 |
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