Analisis Prediksi Kecelakaan Pengguna Sepeda di Kota Surabaya, Jawa Timur
DOI:
https://doi.org/10.21776/ub.rekayasasipil.2018.012.02.4Keywords:
model predictions, an accident bicycle users, Generalized Linear Model, SurabayaAbstract
The developing of infrastructure and residential areas have a relative impact on traffic. The increasing number of the volume of traffic is directly proportional to the increasing number of an accident. Based on the data from Polda Jawa Timur, in 2014 namely 26 bicycle accidents and increased to 36 bicycle accidents in the year 2015, while in 2016 was decreased, namely to 24 bicycle accidents. To get a better understanding about bicycle accidnets, this study was conducted to know characteristic of traffic accident involving bicycle users in Surabaya. The method of analysis used is descriptive analysis frequency to find characteristic bicycle users involved accident and the characteristics of accidents involving bicycle users. Generalized linear model to make an accident prediction model that can happen on condition geometric and the traffic particular. Primary data consisting of the volume of traffic , speed and geometric conditions in the study locations. Secondary data obtained from related institution which is from Polda Jawa Timur, Bappeda Surabaya , and Dinas Perhubungan in Surabaya City. The analysis said that accident occurs has the majority of bicycle users involved accident in the city surabaya is man by 69,9% with age 15-20 year by 14,6 % and have a job as private sector workers. While characteristic of accidents involving bicycle users in the Surabaya is happening most in 06.00-11.59 WIB about 37,6 % with the double accident. Then the majority of injury was minor injuries at 38,2 % with a loss of < Rp. 200.000 at a good. An accident prediction model in Surabaya is McA = McA= 1,061  where: McA = number of accidents, Flow = traffic ( smp / hours ).
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Copyright (c) 2019 Rekayasa Sipil
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This journal is licensed under a Creative Commons Attribution 4.0 International License