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All Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research Eksponensial
Messakh, Gerald Claudio
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Penerapan Metode K-Means Dalam Pengelompokan Kabupaten/Kota Di Kalimantan Berdasarkan Indikator Pendidikan Messakh, Gerald Claudio; Hayati, Memi Nor; Sifriyani, Sifriyani
EKSPONENSIAL Vol. 14 No. 2 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i2.1103

Abstract

Cluster analysis is an analysis that aims to classify data based on the similarity of spesific characteristics. Based on the structure, cluster analysis is divided into two, namely hierarchical and non-hierarchical methods. One of the non-hierarchical methods used in this study is K-Means. K-Means is a partition-based non-hierarchical data grouping method. This purpose of this study is to obtain the best results of grouping regencies/cities on the island of Kalimantan based on education indicators using the K-Means method based on the smallest ratio of standard deviation. Based on the results of the analysis, it can be concluded that the best grouping results based on the smallest ratio of standard deviation is 0.6052 which produces optimal clusters of 2 clusters with the first cluster consisting of 14 Regencies/Cities while the second cluster consists of 42 Regencies/Cities on Kalimantan Island
PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN DATA JUMLAH KEJADIAN DAN DAMPAK BENCANA BANJIR MENGGUNAKAN METODE FUZZY C-MEANS Hayati, Memi Nor; Goejantoro, Rito; Siringoringo, Meiliyani; Purnamasari , Ika; Yuniarti, Desi; Nida, Khairun; Messakh, Gerald Claudio
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 01 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm167

Abstract

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.
Co-Authors Ika Purnamasari Memi Nor Hayati Nida, Khairun Rito Goejantoro, Rito Sifriyani, Sifriyani Siringoringo, Meiliyani Yuniarti, Desi