PENENTUAN DAERAH RAWAN KECELAKAAN DENGAN PENDEKATAN METODE JARINGAN SYARAF TIRUAN
DOI:
https://doi.org/10.21776/ub.rekayasasipil.2019.013.01.10Keywords:
Accident-prone area, Highway, Neural network, SafetyAbstract
Technology improvement gives positive impacts on increasing transportation mode. But it has a negative impact such as traffic jam and increasing number in traffic accident, so road safety issues must be a common concern. One of the efforts to prevent tha accident is to identify accident-prone areas as a warning system for user. Eleven road sections in Malang District and supported data from Satkorlantas Polres Malang District is used as scope of discussion in this study. In this study, the factors that caused accidents such as road characteristic, geometric and environment condition is used for identifcation the accident-prone area. Based on the data, database mapping was done and the pattern of potential accident-prone areas was determined. It can be used for analysis and decision. Mapping and testing process uses a neural network approach because the accuracy of this method has been already proven in various applications. The results approach on prone area identification indicates a precision with a variance of 0.15% in compare with accident-based data analysis through the validation process. This result shows that neural network approach can be used to identify the accident-prone areas as one of the solution in accident prevention and efforts in road safety improvement.References
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