PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA PERSENTASE KRIMINALITAS DI PROVINSI JAWA TIMUR TAHUN 2017
DOI:
https://doi.org/10.29244/ijsa.v4i1.557Keywords:
akaike’s information criterion (aic), criminality, geographically weighted regressionAbstract
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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References
Anselin, L. (2013). Spatial econometrics: methods and models. Springer Science & Business Media.
Anselin, L., & Bera, A. K. (1998). Spatial Dependence in Linier Regression Models With an Introduction to Spatial Econometrics. In Handbook of applied economic statistics. New York (US): Marcel Dekker.
[BPS] Badan Pusat Statistik. (2018a). Provinsi Jawa Timur dalam Angka tahun 2018. Surabaya (ID): Badan Pusat Statistik Jawa Timur.
[BPS] Badan Pusat Statistik. (2018b). Statistika kriminal 2018. Jakarta (ID): Badan Pusat Statistik.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2003). Geographically weighted regression: the analysis of spatially varying relationships. John Wiley & Sons.
Gujarati, D. N., & Porter, D. C. (2012). Dasar-dasar ekonometrika Edisi 5 buku 1 & 2. Jakarta (ID): Salemba Empat.
LeSage, J. P. (2008). An introduction to spatial econometrics. Revue d’économie Industrielle, (123): 19–44.
Leung, Y., Mei, C.-L., & Zhang, W.-X. (2000). Statistical tests for spatial nonstationarity based on the geographically weighted regression model. Environment and Planning A, 32(1): 9–32.
