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238. a. Looking at the scatterplot graph, if forming certain patterns,
such as dots form a certain pattern regularly wavy, widened then narrowed, then heteroscedasticity indicates has occurred.
If there is no clear pattern, and the points spread above and below the 0 on the Y axis, then there is no heteroscedasticity
Santoso, 2012: 240. b. Glejser Test
Glejser test is done with the regressed absolute value of residuals against the independent variables service quality
X1, and promotion X2. Guideline from glejser test are looking at the significance level of each independent variable
service quality X1, and promotion X2 on the dependent variable customer satisfaction. If the significance level yield
number 0.05, it can be said regression model does not contain any heteroscedasticity. Ghozali, 2006: 129.
F. Hypothesis Test
1. Simultaneous test F – Test
According to Sarwono 2007:29 cited in Akbar 2014 F-test is used to see the influence of exogenous variable to endogenous variable
simultaneously. The criteria for testing the significant level is 5 or 0.05. Step to examine the hypothesis with F-test are as follow:
a. Calculate F-test by SPSS
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b. Calculate the F table with the criteria significant level is 0.05 c. Determine the criteria of hypothesis test as follows :
1 If F
test
F
table
, H is rejected and H
1
is accepted, it means exogenous variable has significant influence to endogenous variable
simultaneously 2 If F
test
F
table ,
H is accepted and H
1
is rejected, it means exogenous variable
doesn’t have significant influence to endogenous variable simultaneously.
2. Partial test t – Test
The t-test was conducted to test each independent variable X to the dependent variable Y, which is conducted to determine how much each
variable consumer dissatisfaction, the characteristics of the product category, and variety seeking influence on brand switching brand
switching. Test steps are as follows Ghozali, 2011: 98: a. Determining Hypothesis Formulation
1 Ho: bi = 0. That is, there is no influence of each independent variable X partially on the dependent variable Y.
2 Ha : bi ≠ 0. That is, there is the influence of each independent
variable X partially on the dependent variable Y. b. Determining the degree of probability of 95 or the 0.05 two-way
Two-tail. c. Determine the criteria for decision-making
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1 Quick look: if the value of t 2 in absolute value, then Ho is rejected and Ha accepted.
2 If the value of t 2 in absolute value, then Ho is accepted and Ha is rejected.
G. Multiple Linier Regression Analysis
According to Malhotra 2004:502, the regression analysis is a statistical procedure to analyze the relationship between the dependent
variable and the independent variables. If there are two or more independent variables then using multiple linear regression analysis. Thus
it can be seen how big the independent variables influence on the dependent variable.
According to Malhotra 2004:512 formulas that can be used as a multiple linear regression analysis calculation is as follows:
Y = a + b
1
X
1
+ b
2
X
2
+ e Description:
Y = customer satisfaction dependent
a = constanta
X
1
= service quality independent X
2
= promotion independent b
1
= regression coefficient of X1 b
2
= regression coefficient of X2 e
= error
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H. The Coefficient of Determination r2
