Application of the K-Means Cluster for the Classification of Disadvantaged Districts/Cities in Maluku Province
DOI:
https://doi.org/10.30595/jrst.v6i1.11637Keywords:
Classification, K-Means, Disadventages Areas, MalukuAbstract
Maluku Province is still the 4th poorest province in Indonesia. This is due to the disparity in development between the provincial and district centers, cities and villages as well as government work programs that are not implemented evenly. To overcome and evaluate these problems, it is necessary to plan or study the classification of underdeveloped regions, namely by grouping districts/cities based on indicators of nderdeveloped areas. This research was conducted using secondary data obtained from the Central Statistics Agency (BPS) of Maluku Province. The method used in this study is to use the K-Means Cluster analysis method. The results of the study indicate that there are 2 classifications of underdeveloped and undeveloped areas in Maluku Province. Cluster 1 consists of Tanimbar Islands Regency, Southeast Maluku Regency, Central Maluku Regency, Buru Regency, Aru Islands Regency, West Seram Regency, Eastern Seram Regency, Southwest Maluku Regency, South Buru Regency and Tual City. In Cluster 2 there is only one area, namely Ambon City.
References
Indonesia, K. M. K. R., & BEA, P. H. E. U. P. (2021). Kementerian Keuangan Republik Indonesia.
Maluku, B. P. S. (2021). Provinsi Maluku Dalam Angka 2017. Ambon: BPS Maluku.
Mustika, D., & Pujiyono, A. (2017). Pengaruh Infrastruktur terhadap PDRB Kabupaten tertinggal di provinsi Nusa Tenggara Timur (Doctoral dissertation, Fakultas Ekonomika dan Bisnis).
Ningrat, D. R. (2016). Analisis Cluster Dengan Algoritma K-Means Dan Fuzzy C-Means Clustering Untuk Pengelompokan Data Obligasi Korporasi (Doctoral dissertation, Fakultas Sains dan Matematika, Undip).
Poerwanto, B., & Fa’rifah, R. Y. (2016). Analisis cluster k-means dalam pengelompokan kemampuan mahasiswa. Indonesian Journal of Fundamental Sciences, 2(2), 92-96.
Simamora, B. (2005). Analisis multivariat pemasaran. Gramedia Pustaka Utama.
Suhaeni, C., Kurnia, A., & Ristiyanti, R. (2018). Perbandingan Hasil Pengelompokan menggunakan Analisis Cluster Berhirarki, K-Means Cluster, dan Cluster Ensemble (Studi Kasus Data Indikator Pelayanan Kesehatan Ibu Hamil). Jurnal Media Infotama, 14(1).
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