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Table 3.1 Likert scale of five 5 levels
Sugiyono, 2009: 94
No Range
Weight 1
Strongly Agree SA 5
2 Agree A
4 3
Neutral N 3
4 Disagree D
2 5
Strongly Disagree SD 1
D. Types and Source of Data
Types and sources of data used in this study are: 1. Primary Data
Is data obtained directly from the original source without going through an intermediary, the data obtained from the respondents through
questionnaires filled out by respondents directly. Primary data specifically address the question of research. This data can be the subject of opinion
people, the observation of the activities and results of testing Indriantono and Supomo, 2002: 147.
2. Secondary Data Data is obtained indirectly through an intermediary medium obtained
and recorded by the other party Indriantoro and Supomo, 2002: 147, or a maker of data produced from the primary data. This data can be obtained
from the results or outcomes data from other people or certain institutions are published for general obtained through research journals, magazines,
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newspapers, the internet and other literature concerning the object studied.
E. Data Analysis Methods
Analysis of the data in this study using SPSS application assistance 20. Tests were performed using SPSS 20 aid applications are as follows:
1. Test Validity
Validity is the level of research instruments to express the data in accordance with the matter to be disclosed. In other words, the validity
indicates the extent to which a measuring instrument that can be used to measure what should be measured. Validity test is used to determine the
feasibility of the items in a list of questions to define a variable. The list of questions generally support a group of specific variables. A questionnaire
as valid if there are similarities between the data collected by the data actually happened on the object under study. Sugiyono, 2004: 172.
In determining whether or not an item that will be used, usually to test the significance of the correlation coefficient in the minimum limit of
correlation of 0.30, meaning that an item is considered valid if the total
score is greater than 0.30 Priyatno, 2010: 90. 2. Test Reliability
Reliability test is a tool to measure a questionnaire which is an indicator of the variables or constructs. A questionnaire said to be reliable
or reliable if someone answers on the statement is consistent or stable over time Ghozali, 2011: 47. Reliability measurements performed with
Cronbach Alpha statistical test. A variable is said to be reliable if the
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value of Cronbach Alpha 0.60 Nunnally in Ghozali, 2011: 48.
3. Classical Assumption Test
a. TestMulticolinearity This test is used to test whether there is any correlation between the
independent variable or the independent variable Ghozali, 2011: 105. Another opinion says that multicollinearity in the regression model to test
whether there is formed a high or perfect correlation between the independent variables of the model has revealed multicollinearity
symptoms Suliyanto, 2011: 81. Multicolinierity test is done by looking at R
2
and the value of t statistics If R
2
is high and the F test rejects the null hypothesis, but the value of t statistics are very small or even not having independent
variables significantly so that it shows any symptoms of multicollinearity Suliyanto, 2011: 81. Other methods multicolinierity test is to analyze
the correlation matrix between the dependent variable and calculating the value of Tolerance and Variane Inflation Factor VIF. Low tolerance
value equal to the value of high VIF because VIF = 1 tolerance. Cutoff value that is commonly used to indicate the presence of multicollinearity
is the tolerance value ≤ 0.10, or equal to the value of VIF 10.
b. Test Heteroscedasticity Heteroskesdasticity test aims to test whether the regression model
occurred inequality variant of the residuals of the observations to other observations remained, is called homocedasticity. Two methods used in
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this study to see heteroscedasticity is to look at the graph plot between the predicted value of the dependent variable ZPRED with residual
SRESID Ghozali, 2011: 139. Heteroscedasticity Test whether there is a variant of variables in the regression model is not the same constant
called heteroscedasticity, or variants of variables in the regression models have the same value constant called homocedasticity Suliyanto, 2011:
95. c. Normality Test
Normality test aims to test whether the regression model, or residual confounding variable has a normal distribution. Good data and fit
for use in research is one that has a normal distribution. Normality of data can be viewed in several ways, including by looking at the normal curve
p-plot. A variable is said to be normal if the distribution of the image data points are spread around the diagonal line, and the spread of the data
points in the direction to follow a diagonal line. Ghozali, 2011:161. 4. Multiple Linear Regression Analysis
In general, this analysis is used to examine the effect of some independent variable variable X to the dependent variable Y. In the
multiple regression independent variable variable X are taken into account its effect on the dependent variable Y, there are more than one.
Regression Suilyanto, 2011: 53 is the dependent variable is affected by two or more independent variables so that the functional relationship
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between the dependent variable Y with independent variables X1, X2, ... .Xn.
In this study, the independent variable is consumer unsatisfaction, advertising, pricing, word of mouth and brand image X. The dependent
variable in this research is brand switching Y so that multiple regression equation is:
Y = a + b1X1 + b2X2 + b3X3 + B4X4 +B5X5 e
Explanation: Y = The dependent variable displacement brand brand switching
a = Intercept constant b1 = Regression coefficient for the dependent variable X1
b2 = Coefficient of regression for the dependent variable X2 b3 = Coefficient of regression for the dependent variable X3
b4 = Coefficient of regression for the dependent variable X4 b5 = Coefficient of regression for the dependent variable X5
X1 = Customer unsatisfaction X2 = Advertising
X3 = Price X4 = Word of Mouth
X5 = Brand image e = Error.
a. Simultaneous testing of Regression Coefficients Test F F test is done to look at the distribution of variants caused by
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regression and variance caused by residual danPada basically used to indicate whether all independent or independent variables have
influence together to dependent variable bound Ghozali, 2011: 98. This can be done by the following criteria Ghozali, 2011:
98: 1 Determining Hypothesis Formulation
a Ho: b1, b2, b3 = 0. That is, there are no positive effects of each independent variable X simultaneously the
dependent variable Y. b
Ho: b1, b2, b3 ≠ 0. That is, there are no positive effects of each independent variable X simultaneously the
dependent variable Y. 2 Determining the degree of probability of 95 or the 0.05 one-way
One-tail. 3 Determine the criteria for decision-making
When the F count F table, then Ho is rejected and Ha accepted. It means that independent variables simultaneously
affect the dependent variable. b. Test Coefficient of Determination
The coefficient of determination R2 was essentially used to measure how far the regression models ability to explain variation
in the dependent variable Ghozali, 2011: 97. R2 small value means the ability of independent variables in explaining the
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dependent variable is very limited. However, many researchers recommend using adjusted R2 values when evaluating where the
best regression model Ghozali, 2011: 97. c. Tests on Partial Regression 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 unsatisfaction, the characteristics of the product category, and variety seeking
influence on brand switching brand switching. Test steps are as follows Ghozali, 2011: 98:
1 Determining Hypothesis Formulation a Ho: bi = 0. That is, there is no influence of each
independent variable X partially on the dependent variable Y.
b Ho: bi ≠ 0. That is, there is the influence of each
independent variable X partially on the dependent variable Y.
2 Determining the degree of probability of 95 or the 0.05 one-way One-tail.
3 Determine the criteria for decision-making a Quick look: if the value of t 2 in absolute value, then Ho is
rejected and Ha accepted. b If t t table, then Ho is rejected and Ha accepted. That is
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partially independent variables affect the dependent variable.
F. Variable Operational Research
1. Operational Definition The variable is a construct that is measured with a variety of value to give
a more concrete picture of the phenomena. The operational definition is the determination of the construct so that it becomes a variable that can be
measured. The operational definition describes a particular method that is used to operationalize the construct, making it possible for other
researchers to replicate measurements in the same way or develop a way of measuring construct better Indriantoro and Supomo, 2002: 147
The variables in this study are generally grouped into two, namely the independent variable independent and the dependent variable
dependent. The dependent variable is the variable types described or influenced by independent variables. The independent variable was the
type of variables that describe or affect other variables, either positively or negatively. The independent variable in this research is consumer
unsatisfaction, advertising, pricing, word of mouth and brand image. The dependent variable in this research is the transfer of the brand brand
switching. The operational definition of these variables is as follows: 2. Independent variable
The independent variable is variables that affect or be the cause of the amount of value of other variables. Variation changes will affect its
independent variable variation changes the dependent variable Suliyanto,
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2011: 7. The independent variable in this study is:
1. Customer unsatisfaction X1.
2. Advertising X2.
3. Price X3.
4. Word of mouth X4.
5. Brand image X5.
3. Dependent Variable The independent variable dependent variables variations are influenced
by variations in the independent variables. This variable is often referred to as criterion variables. Variation changes in the dependent variable is
determined by the variation Interchangeability of the dependent variable Suliyanto, 2011: 8
The dependent variable is the variable whose value depends on other variables, which value will change if the variables that influence change.
The dependent variable in this research is brand switching Y.
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Table 3.2 Variable operating table
No. Variable
Sub Variable Indicator
Scale
1. Customer
unsatisfaction X1
1 Performance The main
operational characteristics.
Ordinal
2 Features Characteristic or
features. 3 Reliability
Consistency of the performance
of the resulting product.
4 Conformance Views on the
quality of the resulting
products according to
product.
5 Durability
Continually used.
6 Serviceability
Service quality.
7 Aesthetics
Product design.
8 Perceived quality
Brand name image reputation.
2. Advertising
X2 1 Knowing
Attract attention attention
Consumer interest interest
Ordinal
2 Affected Mobilize desire.
desire Convince
potential buyers. conviction
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No. Variable
Sub Variable Indicator
Scale
3 Act to make a purchase
Measures of consumer
purchasing decisions.
action
3. Price
X3 1 The price policy
Suitability prices offered.
Affordable price. Stable price.
Ordinal
2 Adjustment price Discount.
Promotion price. 4.
Word of mouth X4
1 Perception of risk
Financial risk. Promotion risk.
Ordinal
2 Consumer
knowledges Product
knowledge Experience with
product Information that
owned. 3
Satisfaction Specific Features
of products. Perceptions of the
quality of products.
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No. Variable
Sub Variable Indicator
Scale
5 Brand image
X5 1 Strength
Physical of the product.
The price of the product.
Product quality. Ordinal
2 Uniqueness Variety of
products. Variations in
product appearance.
3 Favourable Brand name easy
to say. The brand name
easy to remember.
The brand name is known.
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No. Variable
Sub Variable Indicator
Scale
6.
Brand Switching Y
1 Advertising
Ads desire consumer move
into other products.
2 price
comparing price
3 quality
comparing quality
4 brand loyalty
attitude to the brand
5 resistance to
change attitude to change
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CHAPTER IV RESEARCH FINDINGS AND ANALYSIS
A. General Description of Research Object
1. Product Overview
Specs shoes are football shoes form domestic production. Although domestic production, Specs are not afraid to face competitors that have famous brands from
abroad. Actually, in 1980 Specs are already being produce and are now starting to focus on providing sports shoes, clothing and other specific gear to the sport like
futsal, football and badminton. Specs produced by PT. Panarub Industry, which is a manufacturer of shoes
which was also producing the Adidas brand. PT. Industry Panarub is then authorized the PT. Panatrade Caraka to create shoes sports with the brand Specs.
Specs with more professional handling of this kind began in 1994. In the beginning Specs have not classify as soccer shoes, futsal and badminton, but just
as sport shoes as general. The economic crisis that occurred in Indonesia in 1998, making Specs at that time could only penetrate the lower middle market segment.
But since 2001 Specs marketing management change with the target market turn around targeting the upper middle market segment.
Specs marketing and business strategy is to achieving one by one target. Specs soccer shoes is the first in developing a marketing strategy of Specs. This
