Indonesia’s archipelagic geography places considerable demands on marine transport, port environmental management and fisheries surveillance. This article develops an evidence-informed artificial intelligence (AI) framework linking public marine statistics to three proposed analytical functions: gradient-boosted water-quality prediction, recurrent time-series forecasting and vessel-trajectory anomaly screening. The study reviews the officially published BPS Marine and Coastal Resources Statistics 2023, related KKP fleet data and traceable peer-reviewed methods. Government-reported 2022 marine fishing craft totaled 893,258, while the 2022 fisheries production figures in a later BPS statistical compilation were approximately 7.49 million tonnes from capture fisheries and 14.78 million tonnes from aquaculture. The proposed four-layer architecture specifies data, preprocessing, analytics and human-validated decisions. Importantly, the submitted manuscript does not supply model code, station-level training data, out-of-sample predictions or patrol simulation logs; its claimed AI accuracy and fuel savings therefore cannot be independently validated. The contribution is a reproducible research design and evidence map rather than a demonstrated performance improvement.
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