Traffic violation clasterization analysis using k-prototype algorithm

The occurrence of traffic violations is a form of problem that often causes problems on the highway, such as accidents and traffic jams. One of the causes of high cases of traffic violations is the lack of knowledge and awareness of vehicle users in complying with traffic rules. This research aimed to classify and analyze data on traffic violations at the Kotabumi State Court in 2020 using the K-Prototype algorithm to make it easier to find out the types of breaches often committed by motorists. Attributes used as many as 4 points consisting of the kind of violation, type of vehicle, fines, and articles. There are 3 clusters comprised of C1, totaling 2202 with the highest number of violations, namely Article 281, C2 totaling 861 with the highest number of violations, namely Article 291(2); and C3 totaling 586, with the highest violation of Article 307. From the results of the optimal k test using elbow analysis, it was found that the optimal number of clusters was 3.