Cluster Analysis of Disaster Data Intensity in Central Sulawesi Province Using K-Means Method

Abstract

Central Sulawesi often experiences natural disasters such as earthquakes, floods, and landslides. The Central Sulawesi Regional Disaster Management Agency is in charge of managing, responding to, and providing accurate information about the event. This study aims to categorize the Central Sulawesi region based on annual disaster intensity using the k-means method. Using the K-Means algorithm, each region is grouped according to the characteristics of its disaster events. Utilizing data from the Regional Disaster Management Agency (BPBD) of Central Sulawesi Province, this study focuses on understanding disaster event patterns and intensity clusters. From the results of clustering obtained every year, the most dominant type of flood disaster occurs in several regions of Central Sulawesi, and these areas tend to be included in cluster 2 (high disaster intensity) or 1 (medium disaster intensity) and this study records a downward trend in the number of disaster events over time on a scale of 2020 to 2023 which reaches 66%. The information obtained can facilitate mitigation planning, improving the effectiveness of future disaster response.