Analysis of Factors Affecting the Number of Poor People in Indonesia Using Geographycally Weighted Regression
Keywords:
Poverty, Global Regression, GWR, Gaussian Kernel, T testAbstract
The GWR model is better at modeling the number of the poor in each province than the global regression model. The variables affecting poverty in Indonesia are the number of population of provinces (X8), percentage of provincial ground floor housing (X12). On the other hand, the variables that are not affecting the poverty in Indonesia for all provinces are the percentage of provincial electricity users (X4) and the percentage of households that can access decent drinking water in the province (X11), the factors that influence the number of poverty between provinces differ depending on the socio-cultural of province.
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