Analisis Spasial Faktor Ekonomi dan Pendidikan terhadap Angka Putus Sekolah Dasar di Indonesia dengan Pendekatan Algoritma Geographically Weighted Regression - Faiz Azraf; Farhan Cahya Permana; Muhammad Al Fathi Ayyash; Nadzira Rifqi Amin Rinawan; Ravelin Lutfhan Syach Putra (Journal of Information System Research (JOSH), 2026)
The elementary school dropout rate remains a significant educational problem in Indonesia, with varying characteristics across regions. This study analyzes the influence of socioeconomic and educational factors on the elementary school dropout rate in Indonesia in 2023 using a spatial approach. The variables used include poverty level, per capita expenditure, average length of schooling, and expected length of schooling, with 34 provinces as the analysis unit. The analytical methods used were Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR). OLS analysis was used as an initial comparison before applying the location-based model. The results showed that OLS had low explanatory power, while GWR was able to capture spatial variation and heterogeneity in the influence of variables across provinces. These findings suggest that a spatial approach is more relevant in analyzing the elementary school dropout problem and can serve as a basis for formulating policies that are more appropriate to regional characteristics. The purpose of this study is to evaluate the spatial influence of the following variables: poverty level, per capita expenditure, Mean Years of Schooling (RLS), and Expected Years of Schooling (HLS) on elementary school students in 34 provinces in Indonesia, and to examine the accuracy level of the Geographically Weighted Regression (GWR) model compared to the Ordinary Least Squares (OLS) model. The results of this study confirm that the determinants of school dropout are local and vary between provinces, so that the implications of government policies must be designed specifically on an inter-regional basis, rather than being made nationally average.