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Search 10.35870/jimik.v4i2.225 , by doi

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CLUSTERING ZONASI DAERAH RAWAN BENCANA ALAM DI PROVINSI SUMATERA BARAT MENGGUNAKAN ALGORITMA K-MEANS DAN LIBRARY GEOPANDAS David Aryo Wicaksono; Yeremia Alfa Susetyo
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 2 (2023): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i2.225

Abstract

Indonesia is one of the countries that are often affected by natural disasters because it is located on the Asia Pacific Ring of Fire. West Sumatra province is one of the most frequently hit by natural disasters including earthquakes. According to the Central Bureau of Statistics of West Sumatra from 2018-2021, there were 1,148 earthquake cases and 1,503 flood cases. The objective of this study is to reveal areas prone to natural disasters in West Sumatra province using K-Means algorithm and GeoPandas visualization. After doing data processing for the optimal K value, 3 clusters were obtained, namely, cluster 1 is not prone to natural disasters, cluster 2 is prone to natural disasters and cluster 3 is very prone to natural disasters. From this research, it is found that cluster 1 has 7 members of the region, cluster 2 has 11 members of the region, and cluster 3 has 1 member of the region.
CLUSTERING ZONASI DAERAH RAWAN BENCANA ALAM DI PROVINSI SUMATERA BARAT MENGGUNAKAN ALGORITMA K-MEANS DAN LIBRARY GEOPANDAS Wicaksono, David Aryo; Susetyo, Yeremia Alfa
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 2 (2023): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i2.225

Abstract

Indonesia is one of the countries that are often affected by natural disasters because it is located on the Asia Pacific Ring of Fire. West Sumatra province is one of the most frequently hit by natural disasters including earthquakes. According to the Central Bureau of Statistics of West Sumatra from 2018-2021, there were 1,148 earthquake cases and 1,503 flood cases. The objective of this study is to reveal areas prone to natural disasters in West Sumatra province using K-Means algorithm and GeoPandas visualization. After doing data processing for the optimal K value, 3 clusters were obtained, namely, cluster 1 is not prone to natural disasters, cluster 2 is prone to natural disasters and cluster 3 is very prone to natural disasters. From this research, it is found that cluster 1 has 7 members of the region, cluster 2 has 11 members of the region, and cluster 3 has 1 member of the region.

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