PENGARUH ANTARA MOTIVASI BELAJAR DAN INTELLIGENCE QUOTIENT DENGAN PRESTASI BELAJAR PADA SISWA SMAN 90 JAKARTA

BIANA, FEBRIA LELLY (2012) PENGARUH ANTARA MOTIVASI BELAJAR DAN INTELLIGENCE QUOTIENT DENGAN PRESTASI BELAJAR PADA SISWA SMAN 90 JAKARTA. S1 thesis, Universitas Negeri Jakarta.

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Abstract

ABSTRACT FENRIA LELLY BIANA. The Influence Between Motivation Learning and Intelligence Quotient (IQ) With Academic Achievement at SMAN 90 Jakarta. Scientific Paper, Jakarta : Study Program of Economic Education, Concentration of Office Administration Education, Economics and Administration Department, Faculty of Economics, State University of Jakarta, January 2012. This study aims to determine whether there is the relation between motivation learning and intelligence quotient (IQ) with academic achievement on student SMAN 90 Jakarta. The study was conducted over five months from August to December 2011. The research method used is survey method with the correlational approach. The study population was all students of SMA Negeri 90 Jakarta as much as 1056 students, and affordable population of this study is a class XI student of Science and Social concetration which amounts to 346 students. The sample used as many as 169 students by using proportional random sampling. Data variable Y (academic achievement) is a secondary data obtained from the value of a class XI student report cards at the third semester school year 2011/2012. While the data variable X (Motivation learning) questionnaireshaped instrument used with take the idicators external motivation of learning And internal motivation learning. Then, also take the sub of indicators an effort to 1 succed, a need to study, a wish for the future,achievement, a condusif studying environment, and attractive studying activity and was measured using a Likert scale. Prior to use, tested the validity of construct (Construct Validity) through the validation process of calculating the correlation coefficient score points with a total score and reliability testing with Alpha Cronbach. The results of the reliability of the instrument variable X (Motivation of learning) is 0.805. Techniques of data analysis using SPSS 17.0 begins with finding the test 1 requirements analysis test for normality using the Kolmogorov Smirnov method and obtained values of X 1; 0.63 , X Y Residual is 0.200 which are all more than the 0.05 then the data are normally distributed. For the data variable X 2 2, and (Intelligence Quotient (IQ)) is a secondary data from the school with the indicators a thinking ability and problem solving. Linearity test results X (Motivation of learning) with Y (academic achievement) of 0.000 which is less than the 0.05, it can be concluded the data X 1 (Motivation of learning) with Y (academic achievement) has a linear relationship. Then the results of linearity test X 2 1 (Intelligence Quotient (IQ)) with Y (academic achievement) of 0.000 which is less than the 0.05, it can be concluded the data X (Intelligence Quotient (IQ)) with Y (academic achievement) also has a relationship linearly. Then look for the 2 classic assumptions test the multicollinearity test. A good regression model requires the absence of multicollinearity problems. The results obtained are the Tolerance values of 0,978 which means more than 0.1 and the Variance Inflation Factor (VIF) 1.023, which means less than 10. Thus, it can be concluded that in the regression model didn’t occur multicollinearity. Then look for the heteroskedastisitas test with a Glejser test . A good regression model requires the absence of heterokedastisitas problem. Significance value of X (Motivation of learning) for 0,932> 0.05 and the significance of X 2 1 (Intelligence Quotient (IQ)) for 0,104> 0.05. Since the significance value of more than 0.05 then the regression model didn’t occur heterokedastisitas. Regression equation obtained is Y= 64,034 + 0,201 X 1 + 0,067 X Test the hypothesis that the F test in ANOVA table produces F count (26,899)> F 2. Table (3.06), this means that X (Motivation of learning) and X 2 1 (Intelligence Quotient (IQ)) simultaneously affect the Y (Academic achievement) T test produce t count of X (Motivation of learning) is 5.580 and t count of X 2 1 is 1.66. Because t count > t table, (Intelligence Quotient (IQ)) is 3,874 and t it can be concluded that there is a positive influence on the motivation of learning with intelligence quotient (IQ) with academic achievement. The results of these studies concluded that there is a positive influence between motiivation of learning and intelligence quotient (IQ) with academic achievement. Then a coefficient of determination of test results obtained 24,5%, academic achievement variable (Y) determined by X (Motivation of learning) and X 2 (Intelligence Quotient (IQ)).

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