ANALISIS KLASTER KEMISKINAN KABUPATEN KOTA DI PROVINSI BANTEN MENGGUNAKAN METODE K-MEANS

ANALISIS KLASTER KEMISKINAN KABUPATEN KOTA DI PROVINSI BANTEN MENGGUNAKAN METODE K-MEANS

Blog Article

Poverty is a special problem that needs to be discussed in Indonesia.Because poverty that occurs in a certain area will have an impact on development in Indonesia.Banten province has a percentage of 6.04 percent with a total poverty of 576.62 thousand poor people.

Given this, the Provincial Government of Banten requires knowledge of district/city socio-economic data in Banten Province.This study aims to cluster regencies/cities in Banten Province using the K-Means method.The K-Means method is a clustering technique that aims to group data based on the same characteristics.The variables observed in this study were the percentage of poor people aged 15 and over 5 Piece Outdoor Seating who had graduated from elementary/junior high school, the percentage of poor people aged 15 and over who had finished high school and above, the percentage of poor people aged 15 and over by district/city not working, the percentage of poor people aged 15 Years and over by district/city working in the informal sector, percentage of poor population aged 15 and over by district/city working in the formal sector, percentage of expenditure per capita for food by Hockey Sticks - Intermediate district/city and poor status.the results of the analysis showed that the district/city poverty clustering in Banten Province using the K-means method obtained 2 clusters, namely cluster 1 consisting of Tangerang City, Cilegon City and South Tangerang City and cluster 2 consisting of Pandeglang Regency, Lebak Regency, Tangerang, Serang Regency, Serang City.

And formation 2 cluster has a good structural test value based on the results of the silhouette index so that 2 cluster has the best accuracy value compared to 3 clusters and 4 cluster.