PENGARUH ANTARA KETERLIBATAN KERJA (JOB INVOLVEMENT) DAN KEPUASAN KERJA (JOB SATISFACTION) DENGAN KINERJA PADA KARYAWAN PT. ASAHIMAS FLAT GLASS TBK JAKARTA

CHAIRULIA, RATNA (2012) PENGARUH ANTARA KETERLIBATAN KERJA (JOB INVOLVEMENT) DAN KEPUASAN KERJA (JOB SATISFACTION) DENGAN KINERJA PADA KARYAWAN PT. ASAHIMAS FLAT GLASS TBK JAKARTA. S1 thesis, Universitas Negeri Jakarta.

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Abstract

ABSTRACT RATNA CHAIRULIA. The Influence Between Job Involvement and Job Satisfaction With Performance at PT. Asahimas Flat Glass Tbk Jakarta. Scientific Paper, Jakarta : Study Program of Economic Aducation, 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 influence between job involvement and job satisfaction with performance on employees PT. Asahimas Flat Glass Tbk Jakarta. The study was conducted from October to January 2012. The research method used is survey method with the correlational approach. The study population was all employees of PT. Asahimas Flat Glass Tbk Jakarta as much as 500 employees, and affordable population of this study is an Administrative Divition which amounts to 55 employees. The sample used as many as 48 employees by using proportional random sampling. 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 X 1, X Y, and Residual is 0.200 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 2, (Job Involvement) with Y (Performance) of 0.000 which is less than the 0.05, it can be concluded the data X 1 1 (Job Involvement) with Y (Performance) has a linear relationship.Then the results of linearity test X (Job Satisfaction) with Y (Performance) of 0.001 which is less than the 0.05, it can be concluded the data X 2 (Job Satisfaction) with Y (Performance) 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 results obtained are the Tolerance 2 values of 0.786 which means more than 0.1 and the Variance Inflation Factor (VIF) 1,272, 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 (Job Involvement) for 0,829> 0.05 and the significance of X (Job Satisfaction) for 0,415> 0.05. Since the significance value of more than 0.05 then the regression model didn’t occur heterokedastisitas. Regression equation obtained is Y = 19,792 + 0,246 X 1 + 0,480 . 2 Test the hypothesis that the F test in ANOVA table produces F count (10,819)> F table (3,204), this means that X 1 (Job Involvement) and X (Job Satisfaction) simultaneously affect the Y (Performance). T test produce t 1 2 count of X 1 (Job Involvement) is 2,108 and t count of X 2 (Job Satisfaction) is 2,702 and t is 1,679. Because t Count > t it can be concluded that there is a positive influence on the job involvement with job satisfaction with performance. Then a coefficient of determination of test results obtained 32,5%, performance variable (Y) determined by X 1 table, (Job Involvement) and X (Job Satisfaction).

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