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According to traffic accident data collected by the East Java Police Department through IRSMS and AIS portal in 2018, the number of accidents tended to incline from 2015 to 2017. The objective of this research focusing on Kediri and Surabaya area is finding the characteristic of motorcycle riders in the study locations, looking for the characteristic of motorcycle-related accidents in both cities, and creating a motorcycle-related accident probability model in the targeted cities. The primary data was obtained using questionnaires and interview with 200 participants. The analysis method used in this research was descriptive frequency analysis and logistic regression analysis. The result of the descriptive analysis shows that 112 respondents has been in a traffic accident before. Based on the social economy characteristic, riders aged under 25 (50%) are the biggest group. Also, based on the motorcycle movement aspects, the most influential group was the one with more than 5 km mileage a day (68%). While based on logistic regression analysis, it resulted that the influencing factor are X2 (ages) and X12 (mileage of travel). Overall, the probability of motorcycle-related accident probability of riders under 25 whose mileage more than 5 km a day is 91.5 %.

The Probability Prediction Model of Motorcyclist Accident Against IRSMS and AIS from the Police Department, East Java (A Case Study in Kediri Regency and Surabaya City)