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Salma Dewi Nur Faridah
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Computer Science & IT

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PENERAPAN DATA MINING UNTUK PEMETAAN DAERAH RAWAN BENCANA SEBAGAI UPAYA KESIAPSIAGAAN TERHADAP BENCANA Vega Purwayoga; Ali Astra Mikail; Salma Dewi Nur Faridah; Virra Retnowati A’izzah
Jurnal Teknoinfo Vol 17, No 1 (2023): Vol 17, No 1 (2023): JANUARI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i1.2381

Abstract

Disasters have a major impact on several sectors, such as infrastructure, manufacturing, tourism and transportation. One way to prepare for or improve disaster preparedness is to implement preventive measures. Preventive actions can be taken by identifying disasters in each area from past data. This study aims to map areas affected by disasters to facilitate disaster preparedness programs. The data used in this research are areas of West Java that will be affected by the disaster in 2022 from January to October. The disaster data used in this study are floods, landslides, abrasion, tornadoes, droughts, fires, earthquakes and tsunamis. Research to use data mining techniques, namely grouping techniques. The clustering algorithm used in this study is the K-means cluster. The clustering process was carried out several times to find out the comparison of the quality of the grouping results which in this study used the Within Cluster Sum of Squares (WSS). The best WSS value is when the number of k or the number of clusters is 5, which is 89.8%. This research is expected to be a reference for disaster preparedness. This research also produced disaster grouping maps, where each cluster has different characteristics or types of disaster.
Co-Authors Ali Astra Mikail Purwayoga, Vega Virra Retnowati A’izzah