PEMBENTUKAN KLASTER TERHADAP INDEKS PEMBANGUNAN MANUSIA DI WILAYAH JAWA TIMUR

Abstract

The Human Development Index (HDI) is one of the efforts to achieve the Sustainable Development Goals (TPB) with HDI components including health, education and a decent standard of living. Referring to the Central Statistics Agency, it always increases from 2010 to 2022, but there are still several regions in East Java that have low HDI values. Based on this, it is necessary to carry out analysis using clustering techniques so that we can find out more deeply about the characteristics of each district or city in East Java. The research method used is by collecting data which includes HDI, UHH, RLS, HLS per capita expenditure values, income inequality, HDI, city minimum wage, GRDP, number of poor people, open unemployment rate, population, and labor force participation rate. After obtaining the data, data exploration and cleaning was carried out, principal component analysis (PCA), factor analysis, modeling using K-Means and DBSCAN, and silhouette calculations were carried out. The results show that the K-Means model has 3 clusters. Cluster 1 has a purple color with superior characteristics in all aspects except the HDI value, GRDP, and the number of poor people. Cluster 2 has a green color with less superior characteristics in terms of UHH, RLS, HLS, real per capita expenditure, income inequality, and IPG. And cluster 3 in yellow has superior characteristics in terms of UHH, RLS, HLS, real per capita expenditure, income inequality, and IPG. East Java Province always experiences increasing HDI values, but there are still disparities between one district or city and another as shown by the K-Means silhouette value of 0.43

Keywords

• indeks pembangunan manusia, k-means, dbscan, klaster
• human development index, cluster