<![CDATA[The southern waters of Java are suitable to be the largest supplier of Yellowfin tuna exports in Indonesia, but have not efficiently produced the expected yield. This research minimizes these constraints by modeling the yellowfin tuna fishing grounds in the southern waters of Java based on oceanographic factors such as Sea Surface Temperature (SST), chlorophyll-a (CHL_A), Sea Surface Salinity (SSS), Sea Surface Height (SSH) using an integration between remote sensing, Geographic Information Systems (GIS), and the Generalized Additive Model (GAM) statistical method. This study used oceanographic factor data from Aqua MODIS Level-3 and Copernicus, while yellowfin tuna fishery production was obtained from Palabuhanratu Nusantara Fishing Port (NFP), Cilacap Ocean Fishing Port (OFP), and Pondokdadap Coastal Fishing Port (CFP). The modeling process used 80% of the data, while the remaining 20% was used to validate the model results. The order of influence of oceanographic parameters from largest to smallest is SST > SSS > SSH > CHL-A. The best model from the GAM analysis showed that the combination of four oceanographic parameters had the greatest influence on yellowfin tuna CPUE. The catch per unit effort (CPUE) of yellowfin tuna was predicted to be high in May-October and low in November-April. The prediction model had high accuracy because most of the fishing activity was in the HSI 0.4-0.5 range and the RMSEP value was 0.63. Yellowfin tuna were suitable in habitats distributed from inshore to offshore in June and July, but less suitable in December. ]]>
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