Traffic Accident Severity Prediction Using Naive Bayes Algorithm - A Case Study of Semarang Toll Road

Annual Conference on Industrial and System Engineering 2019

工业技术（总论）

Budiawan, W.^1^2 ; Saptadi, S.^1 ; Sriyanto^1 ; Tjioe, C.^1 ; Phommachak, T.^2

Department of Industrial Engineering, Faculty of Engineering, Diponegoro University, Jl. Prof. H. Soedarto, SH. Semarang

50275, Indonesia^1

Department of Architectural and Civil Engineering, Toyohashi University of Technology, Japan^2

关键词: Accident prediction model;    Accident severity;    Indonesia;    Naive-Bayes algorithm;    Prediction model;    Traffic accident severities;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/598/1/012089/pdf
DOI  :  10.1088/1757-899X/598/1/012089

学科分类：工业工程学

来源: IOP

【 摘 要 】

A traffic accident was one of the leading cause of death in Indonesia. Toll Road is one of the places where traffic accidents occur. In 2007-2017 there were 501 accidents at Semarang Toll Road. Accident in Semarang Toll Road has a variety of severity. The most severe case is death. A traffic accident can lead to death. One of the ways to decrease the number of the accident was decreased the severity of the accident. This achieved by making a prediction model. The prediction model can predict the severity of the accident based on the attribute affecting the severity of the accident. In this research, Days, Type of Road, Weather, Condition of Road, Time of the accident, Sex of Driver, and Type of Vehicle were chosen as attributes to make prediction model of accident severity. Naive Bayes algorithm was used to make the model which can predict accident severity. The result was an accident prediction model with an accuracy of 39.49% to predict accident severity and the probability of an accident.