Building the Predicting Model of a Road accident using data mining technique

This research applies data mining technique to assess the probability of diabetic paproposed factors and model affecting performance in road accident prediction by using the classification techniques. The sample data is road accidents in Thailand in the year 2020, totaling 11,128 rows. Results show road accident composed of 7 factors including road type factor, cause of accident factor, type of accident factor, climate during an accident factor, number of car involved in accident factor, number of injered and number of deaths factor. Comparison of classification models showed that Naïve Bays technique was the most suitable technique in prediction of road accident with 100% of accuracy, K-Nearest Neighbors 98.99% and decision Tree model 91.69%.