AI-AUGMENTED HEALTH INFORMATION SYSTEM DESIGN FOR SCALABLE MOBILE MENTAL WELLNESS SUPPORT IN INDONESIA - Tiawan; Eliza Ariesta; Nilam Atsirina Krisnaputri; Amril Mutoi Siregar; Surjandy; Merios Gusan Putra; Dani Lukman Hakim; Samsul Arifin; Nur Dava Kurniawan (Jurnal Informatika Teknologi dan Sains (Jinteks), 2026)
Indonesia faces a youth mental health crisis, with limited access to professional care. WHO recommends one mental health worker per 30.000 people, but Indonesia only has 1:200.000 for general mental health personnel and 1:223.587 for psychiatrists. This paper addresses the implementation gap through the design and integration of an AI augmented health information system within Teman Curhat, a mobile mental wellness platform. We applied thematic analysis to expert interviews and used K-Means clustering on 16.689+ user reported cases to classify concerns into three severity levels. The system’s novelty lies in embedding on device Gemini AI for offline triage, ethical chatbot support, and adaptive user routing. Key outputs include a validated clustering model (Silhouette Score: 0.61), AI assisted classification logic, integration within Android Studio, and a scalable conversational interface. This innovation supports SDG 3 (Good Health and Well being) and SDG 10 (Reduced Inequalities) by enabling inclusive, responsive, and privacy focused digital mental health services for underserved communities.