PROFIL SOSIAL EKONOMI DAN KEMISKINAN KABUPATEN/KOTA DI PULAU SUMATERA TAHUN 2012 - Eka Ramadhansyah; Fajar Restuhadi; Jumatri Yusri (Jurnal Online Mahasiswa (JOM) Bidang Pertanian, 2015)
One of the most significant current discussions in development country is poverty, including in Indonesia.  Indonesia is one of the most populous in the worlds with 237.6 million people in 2010, where 76.93 % of povertyareconcentratedin Java(55.33%) andSumatra(21.6%). This paper attempted to create profiling poverty of 151 residences and cities in Sumatera. The poverty characteristics included in the profiling are:levelof education, manpower distribution, expenditures per capita, health, housing facilities, and government’s poverty eradication programs. Data resources are from Badan Pusat Statistik (BPS). The data were analyzed by principle component analysis (PCA) and Hierarchical Data Analysis.Factor analysis produced as many as 32 variables as the main components, adequate for further analysis as 'key factors' for social economic characteristic profile of residences and cities in Sumatera.  These main components demonstrated the adequate values of KMO, MSA, and Bartlett's Test of Sphericity. Following the result from Factor Analysis to obtain the important factors of poverty, the method of hierarchical cluster analysis was, further, used to classify the profiles of 108 residences and cities in Sumatera. The results of cluster analysis with 5interesting clusters of poverty profile of socio-economic indicators show that Cluster 1 comprises of 7 residences with similar characteristic of level of educationand manpower distribution. Cluster 2 includes 9 residences with similar level of education and expenditures per capita. Cluster 3 consists of 36 residences and 2 cities with similar manpower distribution and expenditures per capita patterns. Cluster 4 comprises of 23 residences and 3 cities showing its own distinct characteristics in their similarity patterns of expenditures per capita and housing facilities. Then, the cluster 5 consists of 2 residences and 27 cities showing the similar patterns in level of education and housing facilities.   Keywords: economic social, poverty, factor analysis, cluster analysis.