Klasterisasi Desa dengan Menggunakan Algoritma K-Means pada Data Potensi Desa
DOI:
https://doi.org/10.30865/jurikom.v8i6.3724Keywords:
Clustering, The Developing Village Index, K-Means, Village Potential DataAbstract
The Developing Village Index (Indeks Desa Membangun) is a composite index compiled based on three indices, namely the Social Resilience Index, the Economic Resilience Index and the Village Ecological Index. Based on the Developing Village Index, there are 5 classifications of villages, namely Independent Villages, Developed Villages, Developing Villages, Underdeveloped Villages, and Very Underdeveloped Villages. In line with that, the Central Statistics Agency also issued a Village Development Index (Indeks Pembangunan Desa) to show the classification of the village. This study aims to determine village clustering using the K-Means Algorithm on the 2020 Village Potential (Podes) data, especially on the economic dimension. K-Means is a non-hierarchical data clustering method that can partition data into two or more groups. The number of clusters is determined based on the number of The Developing Village Index statuses, which are 5 clusters. The results of 6 iterations of calculations using the K-Means algorithm show that cluster 1 is grouped into the status of Very Underdeveloped Villages as many as 8 Villages. Then in cluster 2 it is grouped as Underdeveloped Villages as many as 3 Villages. Furthermore, in cluster 3, it is grouped as Developing Villages as many as 83,987 Villages. In cluster 4, they are grouped as Developed Villages as many as 24 Villages. Then in cluster 5 it is grouped as Independent Villages as many as 16 Villages
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