MODEL GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) FAKTOR-FAKTOR YANG MEMENGARUHI KECELAKAAN LALU LINTAS DI PROVINSI BALI

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.

Downloads

Download data is not yet available.

Author Biographies

NI KADEK ENDAH YANITA UTARI, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

I GUSTI AYU MADE SRINADI, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

MADE SUSILAWATI, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

Published
2019-06-06
How to Cite
UTARI, NI KADEK ENDAH YANITA; SRINADI, I GUSTI AYU MADE; SUSILAWATI, MADE. MODEL GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) FAKTOR-FAKTOR YANG MEMENGARUHI KECELAKAAN LALU LINTAS DI PROVINSI BALI. E-Jurnal Matematika, [S.l.], v. 8, n. 2, p. 140-147, june 2019. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/49857>. Date accessed: 28 mar. 2024. doi: https://doi.org/10.24843/MTK.2019.v08.i02.p245.
Section
Articles

Most read articles by the same author(s)

1 2 3 > >>