ANALISIS K-MEANS CLUSTERING PADA PEMETAAN PROVINSI INDONESIA BERDASARKAN INDIKATOR RUMAH LAYAK HUNI - Amin Septianingsih (Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 2022)
Liveable houses, based on national and global have various indicators criteria, they are proper access to sanitation, adequate living space, building resilience, drinking water access, and living security. In addition, the government also pays attention to the housing ownership status variable. This research aims to map Indonesia provinces based on liveable houses indicator that consists of 9 variables, they are access to adequate housing, decent drinking water, electric lighting, decent sanitation, houses area <7.2 m2, the widest land floor, the widest bamboo wall, top of the widest fibers palm, house for rent/contract. This study uses K-Means Clustering analysis and coefficient silhouette width validation method to determine the level of cluster validation. The analysis results are 4 clusters, which cluster 1 consists of 10 members, cluster 2 consists of 19 members, cluster 3 consists of 3 members, and cluster 4 consists of 2 members. Cluster 1 is the lowest percentage for houses size variable with <7,2 m2, the widest fibers roof and ownership of rent/contract houses compared to other clusters. Cluster 2 has the highest percentage of liveable access variable and descent drinking water. Cluster 3 has the lowest percentage of liveable access, descent drinking water, electric lighting, and decent sanitation, while the highest percentage of houses size variable is <7,2 m2, The Widest Land Floor and Wall. Cluster 4 has the highest percentage of other variables of electric lighting variable, descent sanitation, the widest fibers roof, and ownership of temporary rent/contract houses. Meanwhile, has the lowest percentage of the widest land floor and bamboo wall, compared to other clusters