Deteksi Pola Kejadian Bencana Menggunakan Algoritma Naïve Bayes di Kabupaten Boyolali
Abstract
Boyolali Regency, which is geographically located between Mount Merbabu and the still active Mount Merapi, does have high potential as a disaster-prone area. According to data from the Boyolali Regional Disaster Management Agency, during the period from 2022 to 2023, 936 disaster events were recorded in the region. These disasters have a devastating impact on ecosystems and the environment, causing significant material losses, causing psychological disorders, and even threatening human safety. In this context, detecting patterns of disaster events is an important step in disaster mitigation and management efforts. This research was conducted with the aim of understanding patterns of disaster events based on data collected by BPBD Boyolali. The method used is the Naive Bayes algorithm, which has proven to be a powerful tool in data analysis. The results of this research show a high level of accuracy of 92.52%, precision of 92.68%, and recall of 91.64% using the Naive Bayes algorithm. This indicates that the algorithm is effective in recognizing and classifying patterns of disaster events based on existing data. Thus, the results of this research can provide a valuable contribution to the development of an early disaster detection system, as well as assist the authorities in designing more effective mitigation strategies to protect the community and environment in Boyolali Regency.
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