<![CDATA[Background: Social media addiction is a multidimensional issue affecting adolescent development in Indonesia. Objective: This study examined the influence of age, education, and regional minimum wage on adolescent social media addiction through psychological, sociological, and anthropological perspectives. Method: A mixed-methods design integrated machine-learning analysis of secondary data from the Indonesian Central Bureau of Statistics (BPS) with semi-structured interviews involving three adolescents showing indications of social media addiction. The interviews provided contextual insights rather than statistical generalization. Machine-learning algorithms identified the most influential predictors, while qualitative analysis explored social interaction, communication patterns, cultural values, identity construction, self-confidence, and mental health. Results: Age, educational status, and socioeconomic conditions emerged as important factors, with adolescents aged 13–20 years identified as the most vulnerable group. Social media also influenced identity formation and social interaction. Conclusion: Integrating machine learning with psychological, sociological, and anthropological perspectives provides a comprehensive understanding of adolescent social media addiction and supports future prevention and intervention strategies.]]>
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