Analisis Faktor-Faktor Penyebab Depresi Mahasiswa di Indonesia Menggunakan Metode Regresi Logistik - Kiki Mustaqim; Woro Isti Rahayu; Muhammad William Farma; Muhammad Rizky El Sulthani Lintang (SATESI: Jurnal Sains Teknologi dan Sistem Informasi, 2026)
Depression is one of the most common mental health disorders experienced by university students and can have a serious impact on their psychological state, academic performance and social interactions. Academic pressure, financial demands, and changes in living environment are often factors that trigger an increased risk of depression in this age group. Therefore, a comprehensive analysis is needed to identify factors that contribute to the emergence of depression so that prevention efforts can be targeted. This study aims to analyze the factors associated with depression among university students in Indonesia using logistic regression method as a classification approach. The research data was obtained from the Kaggle platform and included several independent variables, namely age, gender, academic pressure, sleep duration, diet, financial stress, study satisfaction, and suicidal thoughts. The results of the analysis showed that the suicidal thoughts variable was the most significant factor affecting the likelihood of students experiencing depression, with a coefficient value of 15.0964. In addition, the logistic regression model built is able to provide good prediction performance with an accuracy rate of 95%. The findings are expected to serve as a basis for educational institutions and policy makers in designing early detection strategies, interventions, and depression prevention programs to create a healthier and more supportive campus environment.