Pengelompokan Desa Atau Kelurahan Di Kutai Kartanegara Menggunakan Algoritma Divisive Analysis

Abstract

Potential Villages (PODES) provide data on the existence, availability and development of the potential of each government administrative area. In order to make it easier for governments to make policies for a region, it is necessary to group the village and sub-districts. Cluster analysis is an analysis that aims to group objects based on the information that found in the data. One of the cluster analysis methods is the divisive analysis, which is a hierarchical grouping method with a top-down approach, where all objects are placed in one cluster and then sequentially divided into separate groups. This research aim to group villages or sub-districts in Kutai Kartanegara based on the determinants of village backwardness and obtaining the silhouette coefficient value from the optimal cluster analysis using the divisive analysis algorithm. The data used is the 2018 PODES data in Kutai Kartanegara and used 15 variables from natural and environmental factors, facilities infrastructure and access factors as well as socio-economic factors of the population. The results of the optimal cluster formed in the grouping of villages or sub-districts in Kutai Kartanegara using the divisive analysis method are 2 clusters. Cluster 1 consisting of 230 villages or sub-districts and cluster 2 consisting of 2 sub-districts. Silhouette coefficient value for data validation from clustering village or sub-districts in Kutai Kartanegara using the divisive analysis method produces 2 clusters is 0,744 which states that the cluster structure formed in this grouping is a strong structure.

Agglomerative Nesting Cluster Analyst in Mapping District/City Health Facilities in West Java Province

“…Penelitian lain oleh [10] yaitu Pengelompokkan Desa atau Kelurahan di Kutai Kartanegara Menggunakan Algoritma Divise Analysis Tahun 2018. Penelitian ini menyimpulkan bahwa terdapat dua cluster optimal yang terbentuk pada pengelompokkan desa/kelurahan.…”

“…Kedua penelitian tersebut menganalisis data yang sama dan mengasilkan jumlah cluster cluster yang sama pula. Oleh karena itu, dalam penelitian ini, akan diterapkan Agglomerative Nesting (AGNES) dengan menerapkan studi kasus seperti penelitian yang dilakukan oleh Magfiroh dkk yaitu mengelompokkan sarana Kesehatan di Jawa Barat [10].…”