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All Journal PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Rafiq, Ainul Mardhiah Binti Mohammed
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Depression Classification in University Students using A Machine Learning Approach Based on Multi-Layer Perceptron Azzahra, Fatimah; Pohan, Muhammad Rafiq; Rafiq, Ainul Mardhiah Binti Mohammed; Salim, Imran Hazim Bin Abdullah; Ayub, Azwa Nurnisya Binti; Nizam, Nuralya Medina Binti Mohammad
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 3 No. 2: PREDATECS January 2026
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v3i2.2107

Abstract

Depression among university students is a critical mental health concern, often exacerbated by academic pressure and social adaptation. While prior studies have utilized Multi-Layer Perceptron (MLP) models to achieve up to 78% accuracy, the effectiveness of these systems remains highly sensitive to architectural design and optimization strategies. To address this gap, this study systematically evaluates the performance of modern MLP architectural variants including DenseNet, ResMLP, and ResNet paired with SGD, Adam, and RMSprop optimizers. Using a dataset of 1,025 student records, the methodology integrates Chi-Square feature selection and Min-Max normalization, followed by an 80:20 Hold-Out validation. Results demonstrate that the ResNet-RMSprop synergy yields a superior accuracy of 83.86%, significantly outperforming traditional MLP benchmarks . By identifying the optimal combination of deep learning structures and optimization algorithms, this research provides a more robust and precise technical foundation for AI-driven early detection systems in academic settings.
Co-Authors Ayub, Azwa Nurnisya Binti Fatimah Azzahra Nizam, Nuralya Medina Binti Mohammad Pohan, Muhammad Rafiq Salim, Imran Hazim Bin Abdullah