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All Journal Indonesian Journal of Statistics and Its Applications
Yusuf, Dessy Wulandari Syahputri
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PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA PERSENTASE KRIMINALITAS DI PROVINSI JAWA TIMUR TAHUN 2017 Yusuf, Dessy Wulandari Syahputri; Hermanto, Elvira Mustikawati Putri; Pramesti, Wara
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i1.557

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.
Co-Authors Elvira Mustikawati Putri Hermanto pramesti, wara