Modelling Gender Development Index in Central Java In 2021 with Geographically Weighted Regression
DOI:
https://doi.org/10.31258/jsmds.v1i1.7Keywords:
gender development index, gwr, kernel fixed gaussianAbstract
Regression analysis is a statistical analysis used to determine and model the influence of the relationship between one response variable and one or more predictor variables using the Ordinary Least Squares (OLS) method. In some cases involving spatial data, it can lead to violations of heterogeneity and autocorrelation, indicating the presence of spatial effects. One regression analysis that can address spatial effects is Geographically Weighted Regression (GWR). The Gender Development Index is an index used to measure the achievement of basic human development capabilities in various areas within a region, taking gender into consideration. This study aims to model the GDI of Central Java Province in 2021 using the GWR approach. The data used in this study are secondary data from 35 Districts/Cities in Central Java Province in 2021. Based on the GWR modeling analysis above, it can be concluded that the GWR model is the best model for modeling the GDI in Central Java Province in 2021 with an R2 value by 51.82% and AIC value of 159.0621. In the formed GWR model, the significant variables are X1 or average length of schooling, X4 or school participation rate, and X5 or gender ratio.
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