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References
- Mariana, “Pendekatan Regresi Spasial dalam Pemodelan Tingkat Pengangguran Terbuka”, Jurnal Matematika dan Pembelajarannya, IAIN Ambon, Vol. 1, No. 1, pp. 42-63, 2013.
- J. Jiang, L. Luo, P. Xu, and P. Wang, “How Does Social Development Influence Life Expectancy? A Geographically Weighted Regression Analysis in China”, Int J Public Health, Vol. 163, pp. 95-104, October 2018.
- N. Lutfiani, S. Sugiman, S. Mariani, “Pemodelan Geographically Weighted Regression (GWR) dengan Fungsi Pembobot Kernel Gaussian dan Bi-Square”, UNNES Journal of Mathematics, Vol. 8, No. 1, pp. 82-91, 2019.
- BPS, Badan Pusat Statistika, [Online]. Available: https://jatim.bps.go.id/.
- N. R. Draper, and H. Smith, Applied Regression Analysis, New York: John Wiley and Sons Inc, 1998.
- A. R. Tizona, R. Goejantoro, and Wasono, “Pemodelan Geographically Weighted Regression dengan Fungsi Pembobot Adaptive Kernel Bi-Square untuk Angka Kesakitan Demam Berdarah di Kalimantan Timur Tahun 2015”, Jurnal Eksponensial, Vol. 8, No. 1, pp. 87-94, 2017.
- A. S. Fotheringham, C. Brunsdon, and M. Charlton, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Chicester: John Wiley and Sons, 2002.
- C. Brunsdon, A. S. Fotheringham, and M. Charlton, “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity”, Geographical Analysis, Vol. 28, No. 4, pp. 281-298, 1996.
- C. Chasco, I. Garcia, J. Vicens, “Modeling Spastial Variations in Household Disposible Income with Geographically Weighted Regression”, Munich Personal RePEc Archive (MPRA), [Online]. Available: https://mpra.ub.uni-muenchen.de/1682/.
- H. Yasin, “Pemilihan Variabel pada Model Geographically Weighted Regression”, Media Statistika, Universitas Diponegoro, Vol. 4, No. 2, pp. 63-72, 2011.
- I. Nurhuda, and I. G. N. M. Jaya, “Pemodelan Kriminal di Jawa Timur dengan Metode Geograhically Weighted Regression (GWR)”, Jurnal Matematika MANTIK, UIN Sunan Ampel Surabaya, Vol. 4, No. 2, pp. 150-158, 2018.
References
Mariana, “Pendekatan Regresi Spasial dalam Pemodelan Tingkat Pengangguran Terbuka”, Jurnal Matematika dan Pembelajarannya, IAIN Ambon, Vol. 1, No. 1, pp. 42-63, 2013.
J. Jiang, L. Luo, P. Xu, and P. Wang, “How Does Social Development Influence Life Expectancy? A Geographically Weighted Regression Analysis in China”, Int J Public Health, Vol. 163, pp. 95-104, October 2018.
N. Lutfiani, S. Sugiman, S. Mariani, “Pemodelan Geographically Weighted Regression (GWR) dengan Fungsi Pembobot Kernel Gaussian dan Bi-Square”, UNNES Journal of Mathematics, Vol. 8, No. 1, pp. 82-91, 2019.
BPS, Badan Pusat Statistika, [Online]. Available: https://jatim.bps.go.id/.
N. R. Draper, and H. Smith, Applied Regression Analysis, New York: John Wiley and Sons Inc, 1998.
A. R. Tizona, R. Goejantoro, and Wasono, “Pemodelan Geographically Weighted Regression dengan Fungsi Pembobot Adaptive Kernel Bi-Square untuk Angka Kesakitan Demam Berdarah di Kalimantan Timur Tahun 2015”, Jurnal Eksponensial, Vol. 8, No. 1, pp. 87-94, 2017.
A. S. Fotheringham, C. Brunsdon, and M. Charlton, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Chicester: John Wiley and Sons, 2002.
C. Brunsdon, A. S. Fotheringham, and M. Charlton, “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity”, Geographical Analysis, Vol. 28, No. 4, pp. 281-298, 1996.
C. Chasco, I. Garcia, J. Vicens, “Modeling Spastial Variations in Household Disposible Income with Geographically Weighted Regression”, Munich Personal RePEc Archive (MPRA), [Online]. Available: https://mpra.ub.uni-muenchen.de/1682/.
H. Yasin, “Pemilihan Variabel pada Model Geographically Weighted Regression”, Media Statistika, Universitas Diponegoro, Vol. 4, No. 2, pp. 63-72, 2011.
I. Nurhuda, and I. G. N. M. Jaya, “Pemodelan Kriminal di Jawa Timur dengan Metode Geograhically Weighted Regression (GWR)”, Jurnal Matematika MANTIK, UIN Sunan Ampel Surabaya, Vol. 4, No. 2, pp. 150-158, 2018.