<![CDATA[Malaria remains a major vector-borne disease and a persistent public health problem in Papua Province, Indonesia, particularly in Jayapura Regency and Jayapura City. This study applies remote sensing and Geographic Information Systems (GIS) integrated with the Analytical Hierarchy Process (AHP) to model malaria vulnerability, while presenting the analysis as a learning case for geospatial-based health studies. Spatial data derived from Landsat 8 OLI, SRTM, CHIRPS, meteorological observations, and official population and malaria records were analyzed using pairwise comparison and weighted overlay techniques. The results indicate that high malaria vulnerability is predominantly associated with lowland and coastal areas characterized by high rainfall, high humidity, and relatively high population density. The resulting vulnerability map shows strong spatial correspondence with reported malaria cases and is easily interpretable. Overall, this study demonstrates that AHP-based remote sensing and GIS analysis not only supports malaria vulnerability assessment but also provides an effective instructional framework for teaching spatial decision-making in environmental and geographic health education.]]>
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