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Anggreani, Desi
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Neuroscience Social Sciences

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Classification Of Student Mental Health Based On Academic And Social Variables Using The Decision Tree Method Anggreani, Desi; Danuputri, Chyquitha; Hayat, Muhyiddin A M; Setiawan, Dedi
Jurnal Algoritma, Logika dan Komputasi Vol 8, No 1 (2025): Jurnal ALU, Maret 2025
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v8i1.8652

Abstract

Mental health problems are suffered by many people, including students who often have poor lifestyles. Depression and anxiety are widespread among students, with all universities reporting students with depression and 75.5% reporting students with severe anxiety. This research aims to determine the classification of student mental health based on academic and social by using the Decision Tree method so that early treatment can be carried out. The dataset used consists of 11 aspects concerning academic and social. The data that has been collected is processed through the preprocessing stage and analyzed using the Decision Tree classification method. The classification results showed that out of 973 students who did not suffer from depression, the method classified them correctly. In addition, of the 104 college students who were classified as suffering from major depression, all of them were actually suffering from major depression. The agreement between the classification results and the actual condition shows the reliability of this method, with an accuracy rate of 76.71%. This research underscores the importance of academic and social variables in influencing students' mental health. The findings confirm the reliability of the Decision Tree method in detecting students' mental state and point to the need for effective counseling services and mental health interventions in campus and social environments. 
Co-Authors A M Hayat, Muhyddin Abd. Rasyid Syamsuri Aji Prasetya Wibawa Bakti, Rizki Yusliana Danuputri, Chyquitha Dedi Setiawan Dewi MJ, Wanda Tyrana Hamdani Lukman Lukman Lukman Lukman Lukman Lukman LUKMAN, LUKMAN Muh. Alamsyah Muhyiddin A M Hayat Nurmisba Nurmisba, Nurmisba Purnawansyah Purnawansyah Putri, Desy Pratiwi Ika Rizky Yusliana Bakti Setiawan, Dedi Wiwik Handayani