Developing an AI-Enhanced Maritime Border Security Framework: A Case Study of Indonesia-Malaysia Border at Sebatik Island

Abstrak

Maritime border security in archipelagic regions faces increasing challenges from transnational threats, with traditional surveillance approaches proving inadequate. This study examines the implementation of Artificial Intelligence (AI) in maritime border security at Sebatik Island, Indonesia, focusing on socio-technical conditions influencing AI adoption in resource-constrained environments. Through a qualitative case study incorporating interviews with 12 stakeholders, observations at 29 border points, and document analysis (2022-2023), the research identifies three critical success factors: infrastructure readiness, operational integration capabilities, and human resource development. Findings reveal the crucial role of local knowledge networks in effective border security operations, necessitating their preservation during technological advancement. The study contributes theoretical insights by extending socio-technical systems theory to maritime border contexts and practical applications through a framework for AI implementation that aligns with Indonesia's Vision 2045 and ASEAN's Political-Security Community Blueprint 2025.