Geographically Weighted Regression for Prediction of Underdeveloped Regions in East Java Province Based on Poverty Indicators

Rusdi Hidayat N, Bambang Widjanarko Otok, Zumarsiyah Mahsyari, Siti Halimah Sa’diyah, Dimas Achmad Fadhila

2018

Abstract

Underdevelopment problem of a region can be seen from the dimensions of the economy, human resources, financial capability, infrastructure, accessibility, and regional characteristics. One method to see a region is underdeveloped or not is by looking the percentage of people living in poverty in a region in the publication data of underdeveloped regional indicators issued by the Central Bureau of Statistics (BPS). The results showed that the percentage of people in East Java Province who are living in poverty using linear regression is not yet appropriate. The percentage of people living in poverty spread spatially because there is heterogeneity between the observation sites which means that the observation of a location depends on the observation in another location with adjacent distance so that the spatial regression modeling was done with Adaptive Bisquare Kernel function. The grouping results with GWR resulted in nine groups based on significant variables. Each group eas characterized by life expectancy, mean years of schooling, expenditure and literacy rate.

Paper Citation

in Harvard Style

Hidayat N R., Otok B., Mahsyari Z., Sa’diyah S. and Fadhila D. (2018). Geographically Weighted Regression for Prediction of Underdeveloped Regions in East Java Province Based on Poverty Indicators.In Proceedings of the 2nd International Conference Postgraduate School - Volume 1: ICPS, ISBN 978-989-758-348-3, pages 898-907. DOI: 10.5220/0007553708980907

in Bibtex Style

@conference{icps18,
author={Rusdi Hidayat N and Bambang Widjanarko Otok and Zumarsiyah Mahsyari and Siti Halimah Sa’diyah and Dimas Achmad Fadhila},
title={Geographically Weighted Regression for Prediction of Underdeveloped Regions in East Java Province Based on Poverty Indicators},
booktitle={Proceedings of the 2nd International Conference Postgraduate School - Volume 1: ICPS,},
year={2018},
pages={898-907},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007553708980907},
isbn={978-989-758-348-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference Postgraduate School - Volume 1: ICPS,
TI - Geographically Weighted Regression for Prediction of Underdeveloped Regions in East Java Province Based on Poverty Indicators
SN - 978-989-758-348-3
AU - Hidayat N R.
AU - Otok B.
AU - Mahsyari Z.
AU - Sa’diyah S.
AU - Fadhila D.
PY - 2018
SP - 898
EP - 907
DO - 10.5220/0007553708980907