Penerapan Algoritma K-Medoids pada Pengelompokan Wilayah Desa atau Kelurahan di Kabupaten Kutai Kartanegara
Studi Kasus : Data Hasil Pendataan Potensi Desa (PODES) Tahun 2018
Abstract
Kutai Kartanegara Regency (Kukar) was recorded as the largest contributor to the poor population in East Kalimantan (Kaltim) Province in 2017, so that appropriate strategies are needed to solve proverty problems. The development strategy is prioritized for the regions with the largest number of poor people. Identification is conducted based on facilities, infrastructures, access, social, population and economy is provided in the Village Potential data (PODES). K-Medoids is a grouping method that uses representative objects as a central point, which can be used to find out the characteristics of a region. This research is aimed to find out the optimal cluster formed by choosing the largest value of Silhouette Coefficient (SC) from the grouping of villages / political district in Kukar Regency using PODES data in 2018. Clusters that will be formed in this research are 2 clusters, 3 clusters, 4 clusters and 5 clusters. Based on the analysis, it can be seen that the value of SC 2 cluster is 0.430, the value of SC 3 cluster is 0.174, the value of SC 4 cluster is 0.175 and the value of SC 5 cluster is 0.196. So that the largest SC or optimal cluster values obtained in the grouping of 2 clusters with a SC value of 0.430. Cluster 1 consists of 186 villages / political dsitrict and cluster 2 consists of 46 villages / political district.
