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Qamarina & Zuraidah (2022)

of element engaged in the research is referred to as a sample. According to Liew, J. M. (2019), minimum sample sizes between
100 and 200 serve as the optimum estimator as a population correlation coefficient. Tabachnick and Fidell were used to
calculate the sample size of responders in this study (2013). The five-to-one ratio is used to calculate the minimum sample size
based on the variables adopted in this research. Respondents needed for this study will be calculated according to the equation
stated below:

Independent Variables = (IV1 items × 5) + (IV2 items × 5) + (IV3 items × 5)
= (5×5) + (5×5) + (5×5)
= 75

Dependent Variable = (DV1×5)

= (5×5)
= 25
Demographic = (Demographic profiles x 5)

= (7×5)
= 35
Minimum number of = IV + DV + Demographic profiles

respondents
= 75 + 25 + 35
= 135 respondents

3.3 Research Intervention
As an intervention to increase brand awareness for Clayniq Enterprise especially for their product Dual-Antibax Cleansing
soap, the researcher proposed to do an online campaign on social media with the title of the campaign is “Skin Health Day ''.
This Dual-Antibax Cleansing soap is a product that promotes healthy skin especially when it comes to treating external wounds.
This intervention for Clayniq Enterprise is inspired by World Skin Health Day which is an initiative of collaboration between
the International League of Dermatological Societies (ILDS) and the International Society of Dermatology (ISD). This type of
campaign not only will expose the brand to more people but can also provide education about important of skincare and raise
awareness about skin health in Malaysia. This campaign also will promote awareness of a specific skin illness that affects the
Malaysian community. Because this skin disease can affect anyone, reaching as many people as possible is critical.

4.0 FINDINGS AND ANALYSIS
4.1 Data Analysis
This study's data was analysed using the IBM Statistical Package for Social Science (SPSS) version 27. SPSS is a well-known
software application that is used to test the relationship between independent variables (brand characteristics, advertising, and
sales promotion) and dependent variables (brand awareness of Clayniq Enterprise) as well as to prove the hypothesis stated in
Chapter 1 by comparing and analysing the mean of pre and post survey for brand awareness of Clayniq Enterprise using the
T-test. The data was analysed using a normality test, reliability analysis, descriptive statistics, and multiple regressions.
The first stage is to measure the normality test and reliability test. Normality test was evaluate based on skewness and kurtosis
tests with the approval range of skewing is ± 2 and range of kurtosis is ±7. Cronbach’s alpha was used to analyse the accuracy
of problems related to the Likert scale. A suitable reliability level is 0.7 or higher (Cronbach & Shavelson, 2004; Garth, 2008).
Multiple linear regression analysis is used to assess the relationship between independent and dependent variables (Lee et al.,
2018). Furthermore, Multiple Linear Regression analysis is the most frequently used method in business research for analysing
quantitative data (Ghauri et al., 2020). It is incredibly strong to consider the relationships between variables and which variables
have the most major impact and prediction. Thus, using SPSS software, the regression analysis method was used to measure
the factors in the research framework. This is because multiple linear regressions allow for the study of the effect of various
independent variables on the dependent variable. The coefficient of determination, R2, indicates how well the independent
variables can describe changes in the dependent variable, according to Kuan et al. (2014). Multiple Linear Regression is
significant when the p-value is less than 0.05. Table 4.1 shows the statistical techniques used.

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