PENGARUH ANTARA EFIKASI DIRI DAN INTELIGENSI DENGAN PRESTASI BELAJAR SISWA SMA NEGERI 12 JAKARTA

ABSTRACT SUCI ADIYANI. The Influence Between Self Efficacy and Intelligence With Student’s Academic Achievement of SMAN 12 East 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, May 2012. This study aims to determine whether there is the influence between self efficacy and intelligence with student’s academic achievement of SMAN 12 East Jakarta. The study was conducted over five months from December 2011 to May 2012. The research method used is survey method with the correlational approach. The study population was all student’s of SMAN 12 East Jakarta as much as 698 students, and affordable population of this study is a class X which amounts to 239 students. The sample used as many as 142 students by using proportional random technique. Data variable Y (Academic Achievement) is a secondary data obtained from the value of a class X student mid semester report cards at the second semester 2011/2012 School Year. While the data variable X (Self Efficacy) instrument used was a replica of New General Self-Efficacy (NGSE) of researchers Gilad Chen, et.al., with internal consistency reliability of a 1 = 0.86 and was measured using a Likert scale. Data variable X (Intelligence) is a secondary data obtained from intelligence test scores. Techniques of data analysis using SPSS 17.0 begins with finding the test requirements analysis test for normality using the Kolmogorov Smirnov method and obtained values of X1, X 2 2 and Y is 0,200, 0,058 and 0,063 which are all more than the 0.05 then the data are normally distributed. Linearity test can be seen from the output results Test of Linearity at 0.05 significance level. Linearity test results X (Self Efficacy) with Y (Academic Achievement) of 0.000 which is less than the 0.05, it can be concluded the data X (Self Efficacy) with Y (Academic Achievement) has a linear relationship. Then the results of linearity test X 1 2 1 (Intelligence) with Y (Academic Achievement) of 0.000 which is less than the 0.05, it can be concluded the data X (Intelligence) with Y (Academic Achievement) also has a relationship linearly. Then look for the classic assumptions test the multicollinearity test. A good regression model requires the absence of multicollinearity problems. The 2 results obtained are the Tolerance values of 0.744 which means more than 0.1and the Variance Inflation Factor (VIF) 1.344, 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 (Self Efficacy) for 0.385 > 0.05 and the significance of X 2 1 (Intelligence) for 0.060 > 0.05. Since the significance value of more than 0.05 then the regression model didn’t occur heterokedastisitas. Regression equation obtained is Y= 29.853 + 0.539X 1 +0.235X Test the hypothesis that the F test in ANOVA table produces F count 2. (60.471) > F table (3.06), this means that X (Self Efficacy) and X 2 1 (Intelligence) simultaneously affect the Y (Academic Achievement). T test produce t count of X 1 (Self Efficacy) is 4.450 and t Count of X (Intelligence) is 6.422 and t table. is 1.66. Because t count > t table, 2 it can be concluded that there is a positive influence on the self efficacy with intelligence with academic achievement. The results of these studies concluded that there is a positive influence between self efficacy and intelligence with academic achievement. Then a coefficient of determination of test results obtained 46.5%, academic achievement variable (Y) determined by X 1 (Self Efficacy) and X 2 (Intelligence)