Open AccessPengaruh Kecerdasan Matematis–Logis dan Kemandirian Belajar terhadap Hasil Belajar Matematika
Author(s) -
Huri Suhendri
Publication year - 2011
Publication title -
formatif
Language(s) - English
Resource type - Journals
eISSN - 2502-5457
pISSN - 2088-351X
DOI - 10.30998/formatif.v1i1.61
Subject(s) - multicollinearity , mathematics , pearson product moment correlation coefficient , correlation coefficient , mathematics education , test (biology) , regression analysis , simple linear regression , statistics , linear regression , psychology , paleontology , biology
This study aims to obtain empirical data and analyze the influence of mathematical-logical intelligence, and self study of learning outcomes in mathematics. The variables consisted of: independent variable mathematical-logical intelligence and self study, the dependent variable is the result of learning mathematics. This research was done in class X Vocational High School in South Jakarta district municipality Jagakarsa. The research method used is survey method with correlation analysis. The sample totaled 120 students. Based on the testing of hypotheses to conclusions: (1) There is a significant positive effect of mathematical-logical intelligence on the results of learning mathematics, where the value of the simple correlation coefficient is positive, significant correlation with test Sig. <0.05, and test the regression coefficient with the Sig. <0.05. (2) There are no significant positive influence on the result of self study to learn mathematics. Where the value of the simple correlation coefficient is positive, significant correlation with test Sig. <0.05, and test the regression coefficient with the Sig. > 0.05. (3) There is a significant positive effect of mathematical-logical intelligence and independence of learning on mathematics learning outcomes. Where the value of multiple correlation coefficient is positive, significant correlation with test Sig. <0.05, and test the regression coefficient with the Sig. <0.05. And multiple regression models are free from multicollinearity or no relationship between the independent variables.