PENGARUH PERTUMBUHAN EKONOMI DAN TINGKAT PENDIDIKAN TERHADAP KEMISKINAN DI INDONESIA

ARYANTIH, IIN (2012) PENGARUH PERTUMBUHAN EKONOMI DAN TINGKAT PENDIDIKAN TERHADAP KEMISKINAN DI INDONESIA. S1 thesis, Universitas Negeri Jakarta.

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Abstract

ABSTRACT IIS ARYANTIH. Thesis. Jakarta. The Influence of Economic Growth and Level of Education to Poverty in Indonesia. Economics Education Studies Program, Concentration on Economic Education Cooperative, Economic and Administration Departemen, Faculty of Economics, State University of Jakarta. 2012. The purpose of writing this thesis is intended to investigate the influence of economic growth and level of education towards poverty in Indonesia. This study was carried out by regarding to the development of PDRB, average lenghth of the school population aged 15 years and over, and percentage of poor people in Indonesia, particulary during the period of 2008-2010 with the method of ex post de facto. Type of data used is the time series and cross section with secondary data published by BPS and data processing is used SPSS 19.0. From the F test, the effect of economic growth and level of education to poverty, F calculated is counted for about 13.382 while the F table is equal to 3,15them Fcalculated > F table. It means that there is the effect of economi growth and level of education to poverty simultaniosly. The same conclution occurs is tests of significance and value sig. the point that can we get is about 0,000 from the these result is means that the sig is smaller than a and then Ho is rejected, means that there are some influences of economic growth an level education to poverty in Indonesia. R2 value is obtained is equal to 0,218. It means that the variable economic growth and level of education can explained variability about 21,8% from poverty variable. Meanwhile, the rest is explained by other variables. And then the regression equation which is obtained is Y= 57.489 – 4,682LnX1-2,719X2. Based on the classic assumption test is heterokeastisitas test, multikolinearity test and autocorrelation test ts used then the data already is BLUE, so that the calculation results achieved are not biased

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