PENGELOMPOKAN DAERAH BENCANA ALAM MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING
DOI:
https://doi.org/10.55606/juisik.v3i1.417Keywords:
Data Mining, Natural Disasters, K-Means, ClusteringAbstract
Natural disasters are events that significantly affect the human population. Landslides, earthquakes, floods, fires, droughts, earthquakes and other natural disasters often occur in West Java Province. Information and technology skills are developing quite fast nowadays. Thanks to modern technology, anyone can access and obtain information without restrictions. Information is very important for every aspect of life. One of them is information about natural disasters, because disaster management needs this kind of information. Data mining is a popular method for analyzing disaster data because it is considered a potential answer to disaster management challenges. Therefore, this study discusses the grouping of natural disaster areas for prediction of natural disaster areas in West Java with data mining techniques using the k-means clustering algorithm. The results of the study obtained 3 clusters including low clusters, medium clusters, and high clusters. The selected research source comes from the official website, namely West Java Open Data. The results of this research are expected to provide useful information in determining solutions to natural disaster management problems
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