Penerapan Regresi Terboboti Geografis untuk Data Produk Domestik Regional Bruto (Studi Kasus: 113 Kabupaten/kota di Pulau Jawa Tahun 2010)

Abstract

Java plays an important role for Indonesia’s economic growth because its Gross Domestic Regional Product (GDRP) contributies 58.7 % of Indonesias national Gross Domestic Product (GDP). The Districs of Java has a diverse structure of GDRP. Therefore it is difficult to fulfill the assumption of variance homogeneity in linier regression analysis. Hence, regression model isn’t appropriate. Geographycally Weighted Regression (GWR) is one of the models which can be used to solve this problem. In the case of Java’s GDRP of 2010, it can be concluded that GWR model is better than linier regression model based on Sum Square Error (SSE), Akaike Information Criterion (AIC), and R2. Globaly, there are 3 factors effecting GDRP in Java which are the percentage of poor people, the amount of families using electricity, and the ratio of total population and the amount of education facilities