Analyzing Spatial Groundwater Salinity Using Multivariate Analysis and Multiple Linear Regression Models - Binna, Kristin Ina; Yanidar, Ramadhani; Marendra, Sheilla Megagupita Putri; Taki, Herika Muhammad; Astuti, Ariani Dwi (Department of Environmental Engineering - Universitas Pasundan - Indonesia, 2024)
The increase in the amount of groundwater withdrawal will inevitably pose a threat of seawater intrusion. The purpose of this research was to identify the distribution of shallow groundwater salinity in North Jakarta, West Jakarta and Central Jakarta and to develop a regional model of shallow groundwater salinity distribution. The data used in this study was that of the groundwater quality monitoring, obtained from the Regional Environment Status Book (SLHD), published by The Environment office of Greater Jakarta released in 2022, involving a total of 121 sample points in North Jakarta, West Jakarta, and Central Jakarta. The primary data was taken at 6 (six) sampling locations for model validation purposes. The study began with data grouping, using the Hierarchical Cluster Analysis (HCA) method. The results of identifying the highest distribution of salinity are in cluster 3 (three). A model was subsequently developed, after removing the outliers, with multiple linear analysis methods using the variable the distance from the coastline (X1), well depth (X2) and hardness (X3), to determine the influence of EC, TDS and salinity distribution in shallow groundwater. The results obtained are as follows; EC Models: YEC3 = -1.879+ (1.19.X1) + (5.08.X3). TDS models: YTDS3 = -2.211.30 + (0.81.X1) + (101.41.X2) + (4.07.X3). Salinity models: Ysalinity3 = -0.07+ (6.75×10-5.X1) + (2.4×10-4.X3). Model verification results for R2EC3 = 0.70; R2TDS3 = 0.92; R2salinity3 = 0.88. Validation results produce 21.14% for EC, 8.21% for TDS, and 22.87% for Salinity. This needs further research by increasing the number of primary samples.