THE EFFECT OF KINGCO PERFUME PRODUCT QUALITY AND PRICE ON CUSTOMER BUYING INTEREST

ABSTRACT


INTRODUCTION
Appearance is a big issue for people from all walks of life. Many people apply other things to their bodies, such as fragrances. The added benefit of wearing fragrance is that it can boost our self-esteem and provide comfort to others around us. In Akbar's opinion (2014), Perfume is one of the most popular and widely used goods in the world. The practice of wearing perfume has evolved into a way of life in many groups. Perfume has become one of the lifestyle goods that can boost attractiveness and increase self-confidence, according to Wijanarko and Fachrodji (2020). Perfume is one of the supporting components for a person's look in order to appear perfect, according to Astari and Widagda (2014). Perfume has become a necessity for everyone as a booster of looks in order to boost self-confidence, as well as a trend among many groups of people, both teenagers and adults, from various professional perspectives.
Many businesses or perfume traders have sprouted up in Patumbak District, Deli Serdang Regency, North Sumatra, one of which is the KingCo Perfume Shop, which offers a variety of perfume smells. KingCo Perfume is not just sold in stores; many people sell it from the comfort of their own homes. Not only do young people enjoy the scent of KingCo Perfume Products, but many parents do as well. The following is a list of prices for KingCo Perfume Products per size/ml that researchers observed and are included in Table 1: In order to uncover study phenomena, researchers performed a survey of residents in Hamlet V, Patumbak district, Deli Serdang Regency, North Sumatra. The results of a pre-survey questionnaire distributed to 37 communities in Hamlet V, Patumbak District, Deli Serdang Regency, North Sumatra are shown in Table 2:  Table 2 demonstrates that in Hamlet V, Patumbak District, Deli Serdang Regency, North Sumatra, the quality and price of interest in buying KingCo perfume is still not excellent. This may be evident in consumer reviews, where the majority of people disagreed with queries about buying interest. The statement " I'm interested in purchasing KingCo perfume because there are so many different scents to choose from" was agreed upon by 9 people (24.3 percent), disagreed upon by 28 people (75.6 percent). Customers believe that KingCo's perfume scent selection is limited. Citrus, Nature, Flowers, and Fruits make up the scent of KingCo perfume, according to researchers. This is the reason why customers aren't interested in purchasing KingCo perfume products. The KingCo Perfume bottle size is also less diverse in shape. KingCo Perfume products are exclusively available in 35 ml, 55 ml, and 100 ml bottle sizes, with prices ranging from Rp. 75,000 to Rp. 120,000. According to customer responses from as many as 29 people, there is no variance in the design of the KingCo perfume bottle size (78.3 percent ). Similarly, KingCo's Perfume product design still features packaging that is less appealing to clients, with 28 people (75.6 percent) disagreeing.
Product quality, according to Kotler and Armstrong (2015), is a value that may satisfy customers both physically and psychologically. According to Nasution and Syamsuri (2016), product quality may be improved by tailoring product characteristics to consumers' current demands and preferences. Product quality is something that any business should strive for if they want to compete in the marketplace. Consumers are always looking for high-quality products for a reasonable price. Although some individuals believe that an expensive product is of higher quality. According to Nasution and Syamsuri (2016), sources of knowledge about a product can aid in product evaluation. Consumers are becoming more astute in their purchasing judgments as a result of this predicament. The researchers established quality indicators that were modified to the opinions (Kotler and Keller, 2014) based on the statement items in the pre-survey questionnaire, including: 1) product form, 2) product design, 3) product adjustment, 4) product quality, and 5) durability product.
According to Kotler and Armstrong (2015), pricing refers to the amount of money charged for a product or service, or the amount of value exchanged by customers for the benefits of owning or utilizing a product or service. The researchers established price indicators based on the statement items in the pre-survey questionnaire, including: 1) price affordability, 2) price conformity with product quality, 3) price competitiveness, and 4) price suitability with benefits, which were adjusted to the views of Kotler and Armstrong (2015).
According to Kotler and Keller (2013), buying interest is a type of consumer behavior that occurs in response to objects that suggest a customer's desire to buy something. According to Ferdinand (2014), the desire to make a purchase generates motivation and turns into a very strong action, forcing customers to meet their demands. The researchers created indicators of buying interest based on the statement items in the pre-survey questionnaire that were adjusted to Ferdinand's (2014) perspective, including: 1) transactional interest, 2) referential interest, 3) preferential interest, and 4) exploratory interest.

METHOD
Quantitative research methods can be used to look at specific populations or samples, gather data with research tools, and evaluate quantitative data in order to test hypotheses. This study collects data using a survey method based on assessment data about the research object in order to gain individual opinions. The study took place between January and March of 2022. The participants in this study were 37 people who bought KingCo Perfume items in Hamlet V, Patumbak District, Deli Serdang Regency, North Sumatra. Saturated sampling was employed to collect data. Saturated sampling is a sampling method that takes a sample from the entire population. Primary and secondary data are the types and sources of data used in this investigation.

RESULTS AND DISCUSSION 1. Validity Test Results
The statement items included in the study were subjected to a validity test. The validity test began with the distribution of questionnaires to study participants in Hamlet IV, Patumbak District, Deli Serdang Regency, North Sumatra (outside the original sample of the study). The validity test measurement requirements have a significant level of 5% or equivalent to 0.5. (Ghozali, 2013). Table 3 summarizes the findings of the validity test for quality: The Corrected Item-Total Correlation value is compared to the validity measurement value of 0.5 to make a conclusion on the validity test. Table 3 reveals that the statement '2nd indicator' has the greatest Corrected Item-Total Correlation value of 0.834 and the lowest value of 0.554, indicating that the measurement statement is valid. The results of the pricing validity test may be found in Table 4: By comparing the Corrected Item-Total Correlation and the validity measurement value of 0.5, a decision on the validity test may be made. Table 4 reveals that the '1st indicator' statement has the greatest Corrected Item-Total Correlation value of 0.842 and the '4th indicator' statement has the lowest value of 0.701, indicating that the measurement statement is valid. The Corrected Item-Total Correlation and the measurement value of 0.5 are used to validate decision-making. Table 5 reveals that the '3rd indicator' statement has the highest Corrected Item-Total Correlation value of 0.809 and the '1st indicator' statement has the lowest value of 0.647, indicating that the research instrument in the form of this questionnaire is genuine.

Reliability Test Results
The stability and consistency of an instrument that measures variables is demonstrated by a reliability test (Sekaran and Bougie, 2016). Cronbach Alpha is the instrument used to assess reliability. If the result is greater than or equal to 0.7, the variable is said to be dependable. If the result is less than or equal to 0.7, the variable is said to be unreliable (Ghozali, 2018). The findings of this study's reliability test can be found in Table 6: Because Cronbach alpha > 0.7, all study variables are included in the reliable group, according to Table 6. The results of the reliability test with Cronbach Alpha. The reliability test results demonstrate that the variable item measurement in this study passes the reliability test and may be utilized as a measuring instrument.

Normality Test Results
The normality test, according to Ghozali (2018), is used to determine whether or not confounding variables or residuals are regularly distributed. The normalcy test results can be viewed in Figure 1:    Table 7 to enhance the results of the p-plot graph:  Table 7 shows that the Asymp.Sig (2-tailed) value of the One-Sample Kolmogorov-Smirnov Test is 0.014, which is greater than the significant value (0.05), indicating that the data in this study are evenly distributed normal.

Multicollinearity Test
The multicollinearity test examines the correlation between independent (independent) variables in a regression model. There should be no correlation between independent variables in a decent regression model (Ghozali, 2018). Table 8 contains the results of the multicollinearity test:  Table 8 shows that the two independent variables have a VIF value less than 10 and a tolerance value more than 0.10, indicating that there is no multicollinearity between them.

Heteroscedasticity Test
The heteroscedasticity test is used to evaluate a regression model in which the variance and residuals from one observation to the next are unequal. It is called Homoscedasticity when the variance and residuals of one observation are fixed, and it is called Heteroscedasticity when they are different (Ghozali, 2018). The Heteroscedasticity Test findings can be found in Figure 3: The scatter plot graph reveals that the data is randomly dispersed and does not follow any particular pattern. On the Y axis, the data is scattered both above and below the number 0. Table 9 contains the findings of the Heteroscedasticity Test with the Glejser Test: The Glejser test results in Table 9 show that the two independent variables in this study have a significant value above the significant value (0.05), with Quality at 0.440 and Price at 0.100, indicating that the regression model does not exhibit heteroscedasticity symptoms.

T Test Results (Partial)
The t-test was performed to determine whether the independent variable and the dependent variable had a significant amount of influence. Probability is used to set the test criteria. If the significant level is 5%, that is, if the probability Ha > 0.05, it is considered inconsequential, and if the probability Ha 0.05 or less, it is considered significant (Ghozali, 2018). Table 10 can be used to load the t-test results: According to Table 10, the t-test results show that Quality (X1) has a t-value (3.356) > t-table value (2.034), indicating that Ha is accepted and Ho is rejected. With a significant value of 0.002, it can be concluded that the Quality variable (X1) has a positive influence. Price (X2) has a t-count value (2.966) greater than t-table value (2.034), indicating that Ha is accepted and Ho is rejected. With a significant value of 0.005, Ha is accepted and Ho is rejected, indicating that price has an effect on buying interest.

F test results (simultaneous)
The accuracy of the sample regression function in estimating the real value is measured by the statistical test f. The regression model can be used to predict the independent variable if the significant value of f is less than 0.05. The f statistic test additionally displays all of the independent variables in the model that have a combined effect on the dependent variable (Ghozali, 2018). Table 11 can be used to load the test results f:  Table 11 shows that the fcount value is 29.342 > ftable 2.88 with a sig. 000 < 0.05 in the f test. The findings of this f test show that both Quality (X1) and Price (X2) have a positive and significant impact on Purchase Interest at the same time (Y).

Coefficient of Determination Test Results
The coefficient of determination test is used to assess how well a model can explain variations in the dependent variable (Ghozali, 2018). The coefficient of determination has a value between 0 and 1. The correlation coefficients are classified as follows: 0 (no correlation), 0-0.49 (weak correlation), 0.50 (moderate correlation), 0.51-0.99 (strong correlation), 1.00 (high correlation) (perfect correlation). The ability of the independent variable to explain the dependent variable is measured by R2. A number close to one indicates that the independent variable gives nearly all of the information required to forecast the dependent variable's fluctuation. Table 12 contains the test findings f: The R Square value is 0.633 or 63.3 percent, indicating that the link between Quality and Price factors on Purchase Intention is 0.796 or 79.6 percent, according to the results of the Coefficient of Determination analysis. The obtained results show that the independent variable and the dependent variable have a close association. The Adjusted R Square value of 0.612 indicates that 61.2 percent of Buying Interest can be explained by Quality and Price variables, while the remaining 38.8 percent can be explained by other variables not examined in this study. The standard error of the estimate is 1.358, indicating that the more variables examined in this study, the more variables can be explained. The better the model, the lower the standard deviation.