Pengelompokkan Daerah Rawan Bencana di Kabupaten Boyolali Menggunakan Algoritma K-Means - Abdul Aziz , Muhammad; Sanjaya, Wisnu; Rama Pratama Zulkifli Putra (Universitas Boyolali, 2024)
The country of Indonesia, which is located in the Southeast Asia region, faces a high challenge of disasters due to demographic, geological and geographical factors that influence the occurrence of disasters, both those caused by natural, non-natural and human factors. In the Province of Central Java, especially Boyolali, disasters pose a significant threat, especially when the weather is uncertain. However, to identify priority areas for the lowest and highest levels of natural disasters in Boyolali, it is necessary to improve using data mining methods, therefore to facilitate analysis and grouping of data in identifying disaster-prone areas in Boyolali, the K-Means clustering algorithm is used. The method used in this research is qualitative and the data is analyzed using the Rapidminer Studio Ver application. 9.10. Based on the results of the analysis, there is a division of disaster-prone areas into 3 clusters in Boyolali Regency, namely very high vulnerability, medium vulnerability, and low vulnerability. The results of calculations with Rapidminer show that there are 3 sub-districts in cluster 2, 2 sub-districts in cluster 1, and 17 sub-districts in cluster 0. It should be noted that manual calculations can produce differences because the cluster center point or centroid is taken randomly for each calculation method. It is hoped that this grouping of areas can be used as a support for the Boyolali regional BPBD to focus on anticipatory steps to reduce the impact of disasters on society that may occur in the future.