english : english - Mustika Sari, Ratna; Melantika Sihombing; Rizky Ahmad Yudanegara; Meraty Ramadhini (Jurnal Inotera, 2025)
Slums are densely populated settlements that are not habitable, the building density is very high in a very limited area, causing various problems such as being prone to social diseases and diseases. The distribution of slums in an area can be analyzed using geographic information systems as an innovative strategy to visualize geospatial information accurately, allowing for more in-depth and data-based analysis to support decision making. This study uses the Geographically Weighted Regression (GWR) method. Geographically Weighted Regression (GWR) is a statistical analysis that allows researchers to evaluate spatial variations in the relationship between dependent and independent variables, using the Fixed Gaussian kernel function to provide constant weighting across research locations, so that they can understand complex and different spatial relationships in each location. Based on data processing on seven indicators and 16 slum parameters stipulated in PUPR Regulation No. 14 of 2018, Panjang District, Bandar Lampung City, there are 5 sub-districts that are categorized as light slums with slum distribution points spread across various locations without clear concentration. The results of the Geographically Weighted Regression (GWR) model show that the independent variables (X) and dependent variables (Y) reflect a complex relationship with variable X 11 (non-standard wastewater management system) having the highest coefficient of 0.213830. The results of the GWR model in the ANOVA table show that the GWR model does not provide significant improvement.