The questionnaire contains several questions to be analyzed. Likert Scaling is used to measure all of the answers, which are divided into five
categories as follows: 1 Strongly Disagree, 2 Disagree, 3 Neutral whether agree or disagree, 4 Agree, 5 Strongly Agree. The data were
analyzed in simple regression by using SPSS 16.00 for Windows.
IV. CHAPTER 4 - DATA ANALYSIS AND FINDINGS
4.1. Response Rate and Profile of Respondents
The result of the response rate is 89,41 which is included as a quite high response rate. It shows that the questionnaire had positive
response from the respondents.
Figure of Respondent’s Profile
All the figures above s hows us the respondent’s profile. In the
questionnaire, respondents are asked about their age, their cigarettes consumtion per day and their smoking duration. As the result regarding the
data that has been collected, most of the repondents are in age below 20 years old the minimum age of the respondent is 18 years old until 25
years old. Most of them smoke less than 15 cigarettes per day, and most of them have been smoking for more than 2,5 years.
4.2. Validity, Reliability and Regression
Table 4.1.3 below shows the validity and reliability of the variables, and also the correlation among variables which is going to prove
the hypothesis.
20 Years
Old 23
20 - 25 Years
Old 77
Age
15pcs 70
15pcs 30
Cigarettes Consumption day
2,5 Years
26 2,5
Years 74
Smoking Duration
VARIABLE CRONBACH
’S ALPHA
QUESTION CORRETED ITEM-
TOTAL CORRELATION
DESCRIPTION
Health Warning
Labels 0,796
1
.300
Valid 2
.290
Valid 3
.500
Valid 4
.564
Valid 5
.602
Valid 6
.573
Valid 7
.536
Valid 8
.655
Valid
Smoking Behavior
0,769 1
.451
Valid 2
.548
Valid 3
.639
Valid 4
.524
Valid 5
.558
Valid 6
.346
Valid 7
-.012
Not Valid 8
.176
Valid 9
.331
Valid 10
.669
Valid 11
.389
Valid
Purchase Intention
0,744 1
.574
Valid 2
.571
Valid 3
.489
Valid 4
.468
Valid 5
.475
Valid
For the three variables, it is clear that they are reliable because the α is more than 0,6 according to Sugiyono. It means that all of the
variable are reliable. A validity test has also been run in order to measure the validity for each item in the variables. Unfortunately, there is 1 item
which is not valid and will not be proccessed in simple regression.
Table of Regression Analysis
Hypothesis Adjusted R²
Standardized Coefficient Beta
Description
H1: Health warning labels on cigarettes packages is
affecting smoker’s smoking
behavior. 7,5
0,299 Significant
H2: Smoker’s smoking behavior is affecting
purchase intention. 37,3
0,695 Significant
H3: Health Warning Labels on cigarettes packages is
affecting consumer’s purchase intention
26,3 0,536
Significant
Data is run in simple regression, and the result came up as mentioned above. The correlation between health warning labels towards
smoking behavior is significant, means that the first hypothesis is positively proven for 7,5. The second hypothesis is also significant,
means that smoking behavior do give impact to purchase intention as much as 37,3. Finally for the last hypothesis, it is proven that health
warning labels give impact towards purchase intention for 26,3. By looking at the result, all the hypothesis is proven significant.
4.3. One Way – ANOVA
