Analysis of Factors Affecting the Number of Poor People in Indonesia Using Geographycally Weighted Regression

Authors

  • Muhammad Nur Aidi  Ph.D in Statistics as Senior Statistics Lecturer of Bogor Agricultural University, Indonesia
  • Fitrah Ernawati  PhD in Nutrition and working at Biomedic and Basic Health Technology Research and Development Centre. National Institute of Health Research and Development. Ministry of Health, Indonesia
  • Siswanto  MSc in Statistics from Masteral Graduate Student of Bogor Agricultural University, Indonesia

Keywords:

Poverty, Global Regression, GWR, Gaussian Kernel, T test

Abstract

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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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-04-30

Issue

Volume 4, Issue 4, March-April-2018

Section

Research Articles

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How to Cite

[1]
Muhammad Nur Aidi, Fitrah Ernawati, Siswanto "Analysis of Factors Affecting the Number of Poor People in Indonesia Using Geographycally Weighted Regression" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.1538-1553, March-April-2018.