Grouping of Regencies/Municipalities in Eastern Indonesia in 2021 Based on Socio-Economic Indicators

Abstract

Abstrak Perbedaan kondisi sosial, ekonomi, demografi dan sumber daya pada masing-masing daerah mampu menyebabkan ketimpangan, sehingga perlu mendorong pembangunan ekonomi sesuai kemampuan yang dimiliki oleh daerah tersebut. Pentingnya melihat indikator sosial ekonomi yang menjadi target pembangunan, khususnya di Kawasan Timur Indonesia (KTI). Penelitian ini menggunakan dua metode non hierarki, yaitu K-Means dan K-Medoids. Dalam penelitian ini dilakukan Principal Component Analysis (PCA) menghasilkan 3 faktor. Penentuan jumlah cluster menggunakan validitas internal dan stabilitas menunjukkan bahwa metode K-Means dengan jumlah cluster sebanyak 2 menghasilkan cluster yang paling optimal. Cluster 1 terdiri dari 152 kabupaten/kota, sedangkan cluster 2 terdiri dari 80 kabupaten/kota. Cluster 1 memiliki karakteristik sarana dan prasarana serta ekonomi di atas rata-rata, sementara kualitas manusia nya masih di bawah rata-rata. Abstract Differences in social, economic, demographic and resource conditions in each region can cause inequality, so it is necessary to encourage economic development according to the capabilities of the region. The importance of looking at socioeconomic indicators that are development targets, especially in Eastern Indonesia (KTI). This study uses two non-hierarchical methods, namely K-Means and K-Medoids. In this study, Principal Component Analysis (PCA) was carried out to produce 3 factors. Determining the number of clusters using internal validity and stability shows that the K-Means method with a number of clusters of 2 produces the most optimal clusters. Cluster 1 consists of 152 regencies/municipalities, while cluster 2 consists of 80 regencies/municipalities. Cluster 1 has above average infrastructure and economic characteristics, while its human quality is still below average.