<![CDATA[Indonesia’s customs administration operates at the intersection of maritime mobility, trade facilitation, border protection, and revenue assurance, yet its risk systems are still primarily organized around declarations, manifests, entities, and transactions rather than the wider maritime operating picture. This article develops a conceptual model for transforming Maritime Domain Awareness into a Customs Risk Picture that can support earlier, more contextual, and more explainable targeting of vessels, voyages, cargoes, and commercial actors. The study applies a structured integrative review of 40 peer-reviewed journal articles published between 2017 and 2026, including five articles from the Journal of Maritime Policy Science, and synthesizes evidence from maritime surveillance, sensor fusion, customs analytics, port governance, and digital logistics. The findings identify four requirements for the transformation: multi-source maritime data fusion, risk-oriented entity and voyage profiling, interoperable institutional governance, and a human-in-the-loop decision architecture. The proposed framework connects Automatic Identification System data, radar, satellite imagery, port and logistics information, customs declarations, historical compliance records, and contextual intelligence without treating any single signal as conclusive. The article contributes a layered architecture, a risk-fusion logic, an institutional coordination model, and a phased implementation roadmap for Indonesian Customs. The core argument is that the maritime picture should not merely show where vessels are; it should be translated into an auditable explanation of why a movement, voyage, consignment, or network deserves customs attention while preserving proportionality, trade facilitation, and accountable human judgment.]]>
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