provides the facility to measure the reliability of the st atistical test Cronbach’s Alpha
α. The formula used is :
K ∑σ²
Rii = 1-
k-1 σt²
Description: Rii = reliability of the instrument
K = the number of the questions Σσ² = number of variants grains
σt² = variant total 3.6.3
Normality Test
According to Ghozali 2011 normality test is used to determine whether the regression model, or residual confounding variables have a normal distribution.
There are two ways to detect whether residual normal distribution or not is by analysis of graphs and statistical tests. A simple statistical tests can be done by
looking at the value of kurtosis and skewness of the residual
3.7 Analysis Method
3.7.1 Description Survey Results
According to Sugiyono 2010 description of the statistical results of the survey are used to analyze the data by describing or depicting data that has been collected as
without intending to make conclusions or generalizations apply to the public.
3.7.2 Quantitative Analysis
Quantitative analysis is performed to determine and measure the independent variables affect performance. The method used is multiple linear regression. General
equation of linear regression are as follows:
Y = α+ b
1
X
1
+ e Y = α+ b
2
X
2
+ e Y = α+ b
1
X
1
+ b
2
X
2
+ e
Description: Y = Job Satisfaction
α = constant b1 = coefficient X1
b2 = coefficient X2 X1 = Organizational Climate
X2 = Career Development e = error
3.7.2.1 t Test Partial
t Test was used to test the partial each variable. t statistic or significance probability 0.05, it can be said that there is the influence of independent variables on the
dependent variable partially, if the probability value or significance t 0.05. It is said that there is no significant influence of each independent variable on the dependent
variable. t test can also be done with the help of SPSS software. t statistic can be calculated by the following formula:
b T statistic =
σb
Description: b = regression coefficient dependent variable
σb = standard deviation of the regression coefficients of the independent variables. 3.7.2.2 F Test Simultaneous
F test is used to determine the influence of independent variables jointly simultaneously on the dependent variable. Significant means that the relationship
can apply to the population. Use of significance levels vary, depending on the desire of researchers, 0.01 1, 0.05 5 and 0.10 10. For example, we use a
significance level of 5 0.05, if the probability value 0.05, it can be said there is significant influence jointly between the independent variables on the dependent
variable. If significant values 0.05, no significant difference jointly between the independent variables on the dependent variable. F test can be done with the help of
SPSS software. The F can be searched by the formula:
R²k F =
1-R² n-k-1
Description :
R² = coefficient of determination n = number of data
k = number of independent variables.
