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All Journal Research in the Mathematical and Natural Sciences
Rahman, Mohamad Iswanto
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Computer Science & IT Education Mathematics

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Klasifikasi Tingkat Depresi Mahasiswa Menggunakan Image Recognition dengan Support Vector Machine Abdussamad, Siti Nurmardia; Doholio, Nadya Pratiwi; Lasaleng, Wahyu Pratama; Usia, Putu Ayu Indah N.; Rahman, Mohamad Iswanto; Adam, Dwi Putri Juniar
Research in the Mathematical and Natural Sciences Vol. 4 No. 1 (2025): November 2024-April 2025
Publisher : Scimadly Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55657/rmns.v4i1.193

Abstract

Mental health problems in Indonesia are increasing, with university students being one of the groups vulnerable to depression due to academic pressure, social expectations, and exposure to negative information. Early detection of depression still relies on questionnaire methods that have limitations in objectivity and accuracy. Therefore, this research aims to develop a classification system for student depression using image recognition technology with Support Vector Machine (SVM). The system analyses students' facial expressions and combines them with questionnaire results to improve the accuracy of early depression detection. The results showed that out of 131 respondents, 74% experienced moderate depression, with academic pressure as the main factor. This finding is consistent with the condition of final-year students who face high academic loads. With this method, early detection of depression is more accurate than conventional methods, which can help intervene more quickly in dealing with student mental health crises.
Co-Authors Adam, Dwi Putri Juniar Doholio, Nadya Pratiwi Lasaleng, Wahyu Pratama Siti Nurmardia Abdussamad Usia, Putu Ayu Indah N.