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NI KADEK ENDAH YANITA UTARI
Udayana University
Mathematics

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MODEL GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) FAKTOR-FAKTOR YANG MEMENGARUHI KECELAKAAN LALU LINTAS DI PROVINSI BALI NI KADEK ENDAH YANITA UTARI; I GUSTI AYU MADE SRINADI; MADE SUSILAWATI
E-Jurnal Matematika Vol 8 No 2 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2019.v08.i02.p245

Abstract

The number of traffic accidents in Bali kept increasing since 2015 until 2017. The factors that affected the traffic accidents in every region were suspected to be varied according to geographic position. This geographic effect was known as spatial heterogeneity. Spatial heterogeneity was analized by using Geographically Weighted Regression (GWR). This study aim to model the factors which affected the traffic accidents in every subdistrict in Bali by using fixed and adaptive gaussian kernel. The result showed that GWR with adaptive gaussian kernel was better at estimated the models because it had higher value of which was at . The factors which significantly affected the number of traffic accident in 57 subdistrict in Bali were the average rainfall and the number of population within age of 15 to 29 years old.
Co-Authors I Gusti Ayu Made Srinadi Made Susilawati