PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN DATA JUMLAH KEJADIAN DAN DAMPAK BENCANA BANJIR MENGGUNAKAN METODE FUZZY C-MEANS

Memi Nor Hayati (Universitas Mulawarman)
Rito Goejantoro (Universitas Mulawarman)
Meiliyani Siringoringo (Universitas Mulawarman)
Ika Purnamasari (Universitas Mulawarman)
Desi Yuniarti (Universitas Mulawarman)
Khairun Nida (Universitas Mulawarman)
Gerald Claudio Messakh (Universitas Mulawarman)

VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Vol. 6 No. 01 (2024)

Cluster analysis is a technique used to find groups of similar data objects. The Fuzzy C-Means (FCM) method is a data grouping method where the existence of each data in a cluster is determined by the degree of membership. This study aims to determine the optimal number of clusters based on the Modified Partition Coefficient (MPC) validity index and to determine the optimal grouping results of 34 provinces in Indonesia based on data on the number of events and the impact of floods in 2017-2021. The optimal number of clusters using the FCM method is based on MPC value consists of 2 clusters, namely the first cluster consisting of 27 provinces in Indonesia and the second cluster consisting of 7 provinces in Indonesia.