P opulation growth and the rapid expansion of industry, business, and settlements are directly proportionate to the increase the clean water demand, while land modification will reduce the areas that become water catchments. When amount of groundwater withdrawal increases it will pose a threat of seawater intrusion. The purpose of this research is to identify the distribution of shallow groundwater salinity in North Jakarta, West Jakarta and Central Jakarta and to developed a statistically based model of shallow groundwater salinity distribution using SPSS 26.0 and geographic information system (GIS). Primary data was taken at 6 (six) sampling locations for model validation. Beginning with data clustering, the Hierarchical Cluster Analysis (HCA) approach generates four (4) clusters. Furthermore, to examine the influence of DHL distribution, TDS, and salinity on shallow groundwater, a linear multiple regression model was established in each cluster, with coastal distance (X1), well depth (X2), and hardness (X3) as variables. DHL Models: YDHL1 = 919,29 + 0,67.X3; YDHL3 = -1,879,54+ (1,19.X1) + (5,08.x3). TDS models: YTDS1 = 642,87 + (0,55.X3); YTDS3 = -2,211,30 + (0,81.X1) + (101,41.X2) + (4,07.X3). Salinity model: Ysalinity1 = -0,03 + (9,95 x 10-6.X1) + (3,49 x 10-4.X2) + (2,36 x 10-4.X3); Ysalinity2 = 0,02 + (8,78 x 10-5.X3); Ysalinity3 = -0,07+ (6,75 x 10-5.X1) + (2,4 x 10-4.X3). Model verification results for R2DHL1 = 0,78; R2DHL3 = 0,78; R2TDS1 = 0,58; R2TDS3 = 0,92; R2salinity1 = -0,64; R2salinity1 = 0,79, R2salinity3 = 0,88. Validation results with 6 (six) sample points produce DHL = 45,33%; TDS = 44,65%; Salinity = 44,65%. It requires additional study by increasing the number of source samples used to validate the model. The results of the highest salinity distribution with brackish water categorization are in cluster 3 (three), which is a sampling point with a coastal distance of 440 meters to 4,340 meters and a groundwater depth ranging from 2 meters to 25 meters.