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Analisis K-Means dan Naive Bayes Untuk Pengelompokan Rawan Bencana di Daerah Kabupaten Labuhanbatu Lubis, Nadira Jannah Adeni; Harahap, Syaiful Zuhri; Ritonga, Irmayanti
Jurnal Informatika Vol 12, No 1 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i1.5492

Abstract

A natural disaster is an event that arises from the state of nature and has a significant impact on humans. Natural disasters can include events such as floods, volcanic eruptions, earthquakes, tsunamis, landslides, blizzards, droughts, hail, heat waves, hurricanes, tropical storms, typhoons, tornadoes, wildfires, and the spread of disease.Natural disasters that hit Labuhanbatu Regency include various types, such as floods, fires, tornadoes, and landslides. Each region within the district has specific characteristics associated with a particular type of natural disaster. In order to understand the level of vulnerability to disasters in Labuhanbatu District, K-Means and Naive Bayes methods are implemented to classify the level of vulnerability to frequent disasters.The results of this analysis will improve understanding of the level of vulnerability to disasters in Labuhan Batu Regency, enabling interested parties to identify areas that require increased attention in disaster mitigation and management efforts. In addition, the use of a combination of K-Means and Naive Bayes methods can serve as a solid basis for the development of more effective early warning systems in the future.