Analisis Hubungan Antara Tingkat Inflasi Dan Produk Domestik Bruto Terhadap Tingkat Penggangguran Di Indonesia(Periode 1980 – 2010)

This Research Titled "Analysis of the Relationship Between Inflation And GDP Against the unemployment rate in Indonesia (Period 1980-2010)". This study uses time series data from 1980 through 2010 as many as 31 research data using two independent variables. To see how large the effect of inflation is calculated from the Inflation Rate of Cities in Indonesia which is calculated in units of percent and the Gross Domestic Product is calculated in units of billions of rupiah against the Unemployment rate is calculated from the TPT in units of percent, using data obtained from BPS publications.This study uses a coherent data model of time which is then estimated by the method of Ordinary Least Square (OLS) with the help of software E - Views 5.1. The results of estimation by the method of multiple linear regression showed that a number of other related variables that were previously tested who subsequently joined pursed into 2 variables, it is known that the value of t-statistics that proved significant at 155.7591% of GDP, which means the GDP is very influential on changes in TPT. While the inflation effect of 7.5756%, proved to be significant, which means inflation is not a big influence on changes in TPT. In testing the F - statistic and the coefficient of determination (R - squared) noting that the two independent variables that could explain the dependent variable was tested for and proven significant. And having tested whether there is multicollinearity problem with the method of correlation matrix, the results did not reveal any multicollinearity problems.By using the Durbin Watson Test (DW test) and the Lagrange Multiplier Test (LM test) is known that found a problem with autocorrelation (serial correlation) in the model, it also can not be fixed by adding AR (1) as independent variables in Test Durbin Watson. Thus, the authors advise researchers to conduct further research to improve model estimation results are obtained more perfect.