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Journal : Jurnal Siger Matematika

Penerapan Model Geographically Dan Temporally Weighted Regression Pada Kecelakaan Lalu Lintas Naomi Nessyana Debataraja; Dadan Kusnandar; Riani Mahalalita; Nurfitri Imro’ah
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (741.391 KB) | DOI: 10.23960/jsm.v2i1.2751

Abstract

Geographically and temporally weighted regression (GTWR) is a model that is used to deal with instability in data both spatially and temporally and to produce local parameters. In this paper, The GTWR model is used to analyze the factors that are thought to significantly influence the number of traffic accidents in Mempawah Regency.  The data used in this study came from 8 districts with the variables used were the number of traffic accidents, the number of population (gender ratio, length of damaged road conditions, and percentage of adolescence. The parameter estimation of the GTWR model was obtained using the weighted least square (WLS) method. The optimal bandwidth selection uses the Cross-Validation (CV) method and the weighting used is the Fixed bisquare function. The results of the analysis show that using the GTWR model, it was found that only the population size variable significantly affected the number of traffic accidents in all locations in Mempawah Regency from 2015 to 2018. The GTWR model was known to be better than the multiple regression model because it produced smaller AIC and RSS values and a larger R-square value.