Indonesian Journal of Applied Statistics
Vol 2, No 2 (2019)

Analisis Cluster Intensitas Kebencanaan di Indonesia Menggunakan Metode K-Means

Hafiz Yusuf Heraldi (Universitas Sebelas Maret)
Nabila Churin Aprilia (Universitas Sebelas Maret)
Hasih Pratiwi (Universitas Sebelas Maret)



Article Info

Publish Date
27 Dec 2019

Abstract

Indonesia is one of the most prone countries to natural disasters in the world because of the climate, soil, hydrology, geology, and geomorphology. There are many different natural disasters, but the three most common natural disasters in Indonesia are flood, landslide, and tornado. This research aimed to cluster the provinces in Indonesia based on the flood, landslide, and tornado’s intensity in 2018. The results of clustering by K-Means method in this research divided the provinces in Indonesia into four clusters. The second cluster contained West Java, Central Java, and Bali, the third cluster contained DKI Jakarta, the fourth cluster contained DI Yogyakarta, and the first cluster contained the other 29 provinces. The result of this research hopefully can help the government in order to make decision and improve the natural disaster management system, such as preparedness, disaster response, and disaster recovery based on the most common disaster in each province. Furthermore, the society is expected to be more aware on natural disaster management based on the most common natural disaster in province that they lived.Keywords : natural disaster, cluster, k-means

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Journal Info

Abbrev

ijas

Publisher

Subject

Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science

Description

Indonesian Journal of Applied Statistics (IJAS) is a journal published by Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. This journal is published twice every year, in May and November. The editors receive scientific papers on the results of research, scientific ...