Model Hubungan dan Estimasi Tingkat Kecelakaan Lalu Lintas

Abstract

Background: The model of association between variables which cause road traffic accident will probably create high dimension association model, not only two dimension association model. This probably happened because there were interactions between variables which caused road traffic accident. Loglinear analysis is to analyze high dimension association model.

Objectives: The objectives of this study were to analyze the best association model between variables which caused road traffic accidents and to estimate road traffic accident rate in Surabaya.
Methods: This study is a secondary data analysis of police traffic report in Polwiltabes office Surabaya. Loglinier model with 2 orde association within time and season also motor vehicle type and pain order are the best loglinier model in this research.

Result: In rainy season, expected value of deadly accident for motor cycle riding is 3,38 times than car driving. And in dry season, expected value of deadly accident for motor cycle riding is 1,83 times than car driving. The highest accident rate happened in between bright time, motor cycle, rainy season and deadly accident condition and the rale was 283,9 accidents per 1000 accidents.

Conclusion: Road traffic accident rate and deadly accident condition is highest in rainy season than dry season, and also highest in motor vehicle rider than car driver, The highest accident rate happened in rainy season, bright time, and motor vehicle rider.

Keywords: the model of association, estimation, road traffic accident rate