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Implementation of K-Modes Clustering in Determining Traffic Accident Patterns
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 30 |
| Year of Publication: 2021 |
| Authors: Septyan Eka Prastya, Muhammad Zulfadhilah, Nurhaeni |
10.5120/ijca2021921689
|
Septyan Eka Prastya, Muhammad Zulfadhilah, Nurhaeni . Implementation of K-Modes Clustering in Determining Traffic Accident Patterns. International Journal of Computer Applications. 183, 30 ( Oct 2021), 32-37. DOI=10.5120/ijca2021921689
Abstract
The increasing number of traffic accidents in South Kalimantan continues to occur, which needs to be considered by all parties, especially the traffic police. One of the efforts to reduce it is by finding the pattern of traffic accidents through the clustering method. Data from police reports will determine the grouping of traffic accidents based on day, time, victim, type of accident, geometry, age of the perpetrator, age of the victim, weather, Profession of the perpetrator, Profession of the victim, and type of vehicle involved which are some of the factors causing traffic accidents. This study aims to find the pattern of traffic accidents that often occur using the k-modes algorithm and to find the optimal k value; this study uses the Cohesion and Separation algorithm. The application of clustering using the k-modes algorithm will produce a traffic accident pattern based on the optimal k. The results of this study by testing the K-Modes algorithm at K=2, K=3, K=4, K=5, K=6, K=7, K=8, K=9, and K=10 with each experiment. -each k 5 times produces the optimal k value, which is located at K=3 in the 1st Cohesion experiment with a value of 2641. The pattern generated from the K-Modes algorithm has 3 patterns obtained from each cluster for K=3. At the final stage of determining the pattern of traffic accidents, it is known that the first cluster is the cluster with the largest size (61), namely when the weather is sunny, there are double accidents on the road with straight geometric shapes involving motorbikes and motorbikes.
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