Classification of Risk and Protective Factors for Students' Mental Health Using Data Mining Techniques

Abstract

Mental health issues affecting university students, particularly first-year students, are increasingly concerning, with many experiencing anxiety, depression, and substance abuse. Globally, approximately one in three first-year students faces these challenges. In the U.S., 22% of students receive psychiatric treatment, while in Indonesia, 10% of youth aged 15-24 report psychological problems, with suicide rates on the rise. These disorders negatively impact academic performance, emotional well-being, and social interactions, with contributing factors such as lifestyle, genetics, and gender. Unhealthy habits heighten the risk, while regular physical activity and engagement in hobbies act as protective factors. This research aims to analyze the risk factors and mental health protection of students using a data mining approach. With classification techniques, this research is expected to provide a holistic understanding of the risk factors causing mental health disorders among students and to identify the protective factors. Based on responses from 1,039 students across 15 districts in Lampung Province, the analysis identifies key risk factors including academic pressure, poor time management, heavy workloads, and lack of social support. Protective factors identified include spending time in nature, ensuring sufficient sleep, and balanced participation in student organizations. Findings suggest that universities should implement targeted mental health interventions, provide counseling services, offer workshops and peer support groups, and create a supportive, green campus environment to enhance student well-being and mitigate stress