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impact of work motivation factor towards job satisfaction

Analytical Method
To analyze the influence of Work motivation factor towards job satisfaction and to know which job satisfaction factors that have the highest influence on job satisfaction, writer is using the multiple regression to analyze the influence of each work motivation factors towards job satisfaction. Furthermore, writer will use reliability and validity test and four classic assumption tests to measure the data.
Justification of the Data
Validity and Reliability Test
To justify the data from the questionnaire, writer will use validity and reliability test. The purpose of validity test it know whether the measurement items used able to measure the variable (Ghozali, 2001).
Ghozali (2001) stated a variable is reliable if the responds from the respondents are consistent across the research. The purpose of the reliability test is to measure the consistency of the measurement items. Writer are going to measure the variable‘s cronbach alpha to measure the internal consistency of variables. Ghozali (2001) added that if the cronbach alpha value of a variable is higher than 0.6 it means that the variable is reliable.
Statistical Method
Classic Assumption Test
When a research uses multiple regressions as the statistical tool, that research directly use several assumption (Lind and Marchal and Whaten, 2008). Thus, writer will use classic assumption tests to prove that these assumptions are correct.
Normality Test
Writer will conduct normality test in this research. The purpose of this normality test is to measure the distribution of the residual. Distribution of the residual in multiple regressions should follow normal distribution (Lind and Marchal and Whaten, 2008). There are two ways to conduct the normality test and...

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...f-test is the overall evaluator for the whole model and t-test is the evaluator for each of the independent variable. Thus, in this
T-Test
According to Cooper and Schindler (2011), t-test is a test to know the statistical significance of an independent variable towards dependent variable. Writers will compare the results of the t-test with the ANOVA table. Writer will compare the results of the T-test with the significance level of the research. If the significance level of the t-test is higher than 0.05 it means that the independent variable is not significant.
Adjusted R2
Adjusted r2 is a test to know the ability of the independent variable to predict the variance of dependent variable. Adjusted r2 ‘s value range from 0-1. The higher the value of the adjusted r2 means higher ability of the independent variables to predict the variance of dependent variables.

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