Spatial Regression Analysis to Evaluate Indonesian Presidential General Election

Abstract

Indonesia has held two presidential elections in 2004 and 2009. The result of these elections shows that number of voter abstention is very high. On the first term of 2004 presidential election, about 21.77% of official voters were abstain. On the second term, it increased to 23.37%. Five years later, the number of voter abstention was still high which increased to 27.19%. This research aims to identify spatial pattern and spatial relationship of 33 provinces that produce voter abstention number in the 2009 presidential elections and to identify voter characteristics. The data used are secondary data from General Election Commision of Indonesia (KPU) for an official result of 2009 presidential election and Central Bureau Statistics of Indonesia (BPS) for characteristics of provinces. The results of this research show that there is positive spatial autocorrelation for voter abstention data, which means that there are similiar proportion of provinces to their neighbors in Indonesia. Provinces that are significant to spatial autocorrelation are Riau, Riau Islands, West Sumatera, Central Kalimantan, and Gorontalo. According to significant provinces, there are not province identified as hotspot or coldspot observation. Determining factors that are significantly affected to voter abstention using Spatial Error Model (SEM) is better than Spatial Autoregressive Model (SAR) and Multiple Linier Regression. There are six significant explanatory variables, i.e. percentage of poor people, monthly average of wage/salary/income of employee, mean years of schooling population 15 years of age and over, human development index, school enrollment ratio 16-18 years of age, and life expectancy at birth.