<![CDATA[Background: Coastal areas of Jakarta, Indonesia face increasing flood risk due to sea-level rise, land subsidence, tidal inundation, dense urban development, and uneven social vulnerability. Existing coastal flood studies in Indonesia often analyze hazard, exposure, or vulnerability in isolation, limiting their value for integrated adaptation, especially in data-limited planning. This study aims to create a data-minimal risk assessment framework for Penjaringan District, North Jakarta, by integrating tidal flood trends, asset exposure values, and social vulnerability at the urban village level. Methods: The study used official tidal flood records, spatial building data, asset values from official unit costs and content ratios, and social vulnerability indicators (population density, slum settlement proportion, and malnutrition prevalence). Analysis included trend assessment, exposure estimation, min-max normalization, composite risk indexing, sensitivity analysis, risk typology, and hazard-vulnerability quadrant analysis. Findings: Results show a spatial mismatch between hazard concentration and composite risk. Pluit accounted for 149 of 171 flood-affected days (87.1%) and scored the highest Hazard Index (HI = 1.000), but Penjaringan reached the highest Risk Index (RI = 0.628), due to a Very High Exposure Index (EI = 0.816) and High Social Vulnerability Index (SVI = 0.667). District replacement asset value was estimated at Rp 159.42 trillion. Sensitivity analysis showed Penjaringan remained the highest risk in most scenarios, except for hazard-dominant, where Pluit ranked highest. Conclusion: Flood risk in Penjaringan cannot be explained by hazard frequency alone. The proposed framework offers an initial risk assessment and adaptation prioritization tool in data-limited coastal urban areas. Novelty/Originality: This study presents a replicable framework combining tidal flood records, asset exposure values, social vulnerability, composite risk indexing, sensitivity tests, risk typology, and hazard-vulnerability quadrant analysis.]]>
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