PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA PERSENTASE KRIMINALITAS DI PROVINSI JAWA TIMUR TAHUN 2017

  • Dessy Wulandari Syahputri Yusuf Program Studi Statistika, Universitas PGRI Adi Buana Surabaya (UNIPA Surabaya), Indonesia
  • Elvira Mustikawati Putri Hermanto Program Studi Statistika, Universitas PGRI Adi Buana Surabaya (UNIPA Surabaya), Indonesia
  • Wara Pramesti Program Studi Statistika, Universitas PGRI Adi Buana Surabaya (UNIPA Surabaya), Indonesia
Keywords: akaike’s information criterion (aic), criminality, geographically weighted regression

Abstract

Crime is everything that exists in Indonesia. Based on BPS data in 2018, East Java Province ranks first in the Province of North Sumatra and the Special Capital Region of Jakarta. This research was conducted to determine the factors that support crime in each Regency / City of East Java Province. The method used in this research is Weighted Geographic Regression (GWR). Geographically Weighted Regression (GWR) is one of the statistical methods used to model variable responses with regional or area-based predictor variables. Based on the GWR results, it is recognized as a variable Population Density Percentage (X1), Open Unemployment Rate (X2), Poor Population (X3), Population who are Victims of Drug Abuse (X4), Human Development Index (X5), and Married Human Population (X6) ) importance in the city of Surabaya. The coefficient of determination (R2) and AIC from GWR is better than the OLS model. This refers to the optimal R2 and AIC values ​​of 91.40% and 129.293.

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Published
2020-02-28
How to Cite
Yusuf, D. W., Hermanto, E. M. P., & Pramesti, W. (2020). PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA PERSENTASE KRIMINALITAS DI PROVINSI JAWA TIMUR TAHUN 2017. Indonesian Journal of Statistics and Its Applications, 4(1), 156-163. https://doi.org/10.29244/ijsa.v4i1.557
Section
Articles