Pendekatan Geographically Weighted Regression (GWR) untuk Menganalisis Hubungan PDRB Sektor Pertanian, Kehutanan, dan Perikanan dengan Faktor Pencemaran Lingkungan di Jawa Timur

  • Nurul Aulya Bakri Department of Statistics, Universitas Negeri Makassar
  • Suwardi Annas Department of Statistics, Universitas Negeri Makassar
  • Muhammad Kasim Aidid Department of Statistics, Universitas Negeri Makassar
Keywords: GRDP, Spatial, Environment, Geographically Weighted Regression

Abstract

The Geographically Weighted Regression (GWR) method is a method used to analyze spatial heterogeneity, where the same independent variable gives unequal responses at different locations in a research area. The purpose of this study was to determine the environmental pollution factors that affect GRDP in the agricultural, forestry and fisheries sectors in East Java. The data used in this study are the GRDP of the Agriculture, Forestry and Fisheries sectors in East Java in 2020 along with the environmental pollution factors that are thought to influence it. The results of this study obtained a different model for each district/city. The GWR model shows better results than the multiple linear regression model, as seen from the smallest AIC value and the largest R2

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Published
2024-04-30
How to Cite
Bakri, N. A., Annas, S., & Aidid, M. K. (2024). Pendekatan Geographically Weighted Regression (GWR) untuk Menganalisis Hubungan PDRB Sektor Pertanian, Kehutanan, dan Perikanan dengan Faktor Pencemaran Lingkungan di Jawa Timur. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 6(01), 11-20. https://doi.org/10.35580/variansiunm194
Section
Articles