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 0.015% 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
