K-Means method for analysis of accident-prone areas in Palangka Raya
Hotmian Sitohang, Rosmiati, S Merni · Journal of Physics Conference Series · 2020
Abstract Traffic accidents are the most feared thing for everyone. Even though people are careful using vehicles, accidents can occur. This can be caused by humans not obeying traffic rules, drowsiness, damaged roads, and bad weather. In recent years the accident rate in Palangka Raya has increased sharply and even resulted in death. Accidents often occur in different places and times, making it difficult to determine accident-prone areas. By utilizing data mining techniques using the K-Means method, it can explore information on areas where accidents occur frequently. So that it helps the police in providing signs of accident-prone areas. The results of the study stated the K-Means Clustering algorithm in determining the accident-prone point of success obtained by 68%.