Quality is what customers anticipate from the goods they buy. Customers' decisions to purchase a product can be influenced by the quality of the product. Customer satisfaction, business profitability, and product quality are all correlated. Consumer satisfaction will rise as a result of higher-quality products, which encourages maximum prices at the lowest possible cost. The quality of the client experience would suffer if the business cuts prices too much. The secret to generating value and client pleasure is quality. Kotler and Armstrong (2018) describe product quality as a product's ability to meet consumer market demands; in order to build a product, a company must have a thorough understanding of what customers want as well as the product's ability to function.

The customer determines quality. This suggests that quality is determined by the actual experiences of consumers or users of products and services, which are assessed based on specific requirements or attributes. Quality, in the words of Deming (2005), is everything that customers need and want. Kotler and Armstrong (2018) describe product quality as a product's ability to meet consumer market demands; in order to build a product, a company must have a thorough understanding of what customers want as well as the product's ability to function. Client feedback has a significant impact on quality. This indicates that consumer experiences with products and services, which are evaluated based on a number of criteria or specific characteristics, have an impact on quality.

"Sales promotion is a promotional activity to upload or stimulate purchases, so it's a special selling effort," asserts Assauri (2015). Therefore, it can be said that sales promotion is a type of promotional activity that can boost consumer purchases and distributor effectiveness through the use of display exhibitions, exhibitions, demonstrations, and other sales activities that are not routine and can be carried out at any time. A variety of events, performances, free trials or demos, contests, and limited-edition or special packaging are all part of the sales marketing process.

Along with advertising and personal selling, sales promotion is frequently employed as a crucial technique. As a result, sales promotion can also be seen as an activity that supports and enhances advertising and personal selling. However, it differs from personal selling in that the former is meant for individuals, whereas the latter is meant for groups of potential customers. Additionally, sales promotion focuses on a specific customer group in a comparatively smaller number, whereas advertising targets large consumer groups.

According to Aaker (1991), brand equity is a collection of brand assets and liabilities associated with a brand, including its name and symbol, that increase or decrease the value that a good or service provides to a business or its clients. Then (Shimp and Maden, 1988) claimed that "Brand equity is a brand value that produces high brand awareness and strong, preferred, and possibly unique brand associations, which consumers remember for a particular brand" . Personal

experience, recommendations from friends and family, and information from print or electronic media—such as newspapers, magazines, tabloids, and television—all play a significant role in shaping consumer behavior.

Since customer satisfaction is a measure of the company's performance and can impact customer loyalty and positively impact the product's brand equity, it is also a crucial consideration during the evaluation stage. In English, "Anything that can be offered to a market to meet wants and needs is called a product" is how Kotler (2012) defines a product. Standard and high-quality products are the primary prerequisites that a business must fulfill in order to build brand equity and ensure the survival of its products. The corporation expects the product to have strong brand equity, and the accompanying product qualities undoubtedly support this and be accepted by consumers can be achieved.

The willingness of customers to regularly purchase a product or use a service offered by a business is known as customer loyalty. Both short-term success and long-term competitive advantage will depend heavily on customer loyalty. This is due to the fact that customer loyalty is strategically significant to the company. The rewards of loyalty are cumulative and long-lasting. Therefore, the longer a customer stays loyal, the more money the company may make from them. Oliver (Sangadji & Sopiah, 2013) defined customer loyalty as a client's steadfast will to renew their subscription or make additional purchases of particular goods or services in the future, even though circumstances and advertising campaigns may influence behavior.

In contrast, Morais (Sangadji & Sopiah, 2013) defined customer loyalty as a consumer's dedication to a supplier or retail brand, demonstrated by a consistently favorable attitude and consistent repeat business.

Sugiyono (2017) asserts that the research technique is a scientific approach to gathering data with specific applications and goals. An proper research approach is therefore required in order to collect the data that will be examined in a study. This research employs a quantitative methodology. According to Sugiyono (2017), quantitative methods are research techniques that are grounded in positivism and are employed to examine certain populations or groups. In order to test the given hypothesis, this data collection process employs research equipment and quantitative statistical data analysis. (Source Title, n.d.) A population is a broad category that consists of two elements: the research object and topic and the established quality and inclusion criteria that are used to derive conclusions for more investigation. This population seeks to restrict the use of the generalization area and facilitate the determination of the sample size drawn from the population. Additionally, the study's population consists of PT.

Krama Yudha Ratu Motor customers who purchased a Mitsubishi Canter Euro 4. According to Sugiyono (2017), samples represent a component of the population's size and makeup. The research findings drawn from the sample are inferences about the population since sampling must accurately represent the population's current condition. It is a method of gathering data that involves giving respondents a set of written questions to complete. If researchers are certain of the variables to be measured and the expectations of the respondents, then questionnaires are a very time-efficient way to collect data. Sugiyono (2017) states that the Likert scale is used to gauge a person's or a group's attitudes, beliefs, and perceptions on social phenomena. We'll refer to the variables that the Likert scale measures as variable indicators. Each answer will be given a score and respondents will provide two answers to the researcher's questions, supporting or not supporting.

b. Data Analysis Techniques

1. Validity Test

A validity test is used to measure or evaluate the validity of the used questionnaire, according to Ghozali (2018). If the questionnaire's questions can be measured reliably, the validity test results will be considered appropriate. This test determines if the questionnaire's components can measure the results of this investigation. The following serves as the foundation for determinations regarding the validity of the questionnaire items:

When respondents consistently answer the same items on a questionnaire, it's considered to be positive. One of the measurement instruments for a questionnaire that serves as a time-series indicator is the reliability test. When a research instrument contains reliable data, it indicates that the data is trustworthy. The Cronbach alpha approach, which compares the magnitude of the obtained alpha value to > 0.70, can be used to measure it. The variable question is unreliable if the alpha value is less than 0.70. The variable question is dependable if the alpha value is greater than 0.70.

To ascertain whether the dependent variable and the variable in the regression model have a normal distribution, the Normality Test is used. The normal probability plot, which contrasts the cumulative distribution of the original data with the cumulative distribution of normal data, was used to conduct this test in the study. One of the two techniques utilized in the Normality Test to ascertain the residual value of regression data between the predictor and the variable is the Kolmogorov-Smirnov statistical test. The requirements are as follows:

The multicollinearity test is useful for determining whether there is a correlation between the independent variables in the regression model, claims Ghozali (2018). If there is no connection between the independent variables, the regression model is said to be good. The independent variables are not orthogonal if they have a correlation with one another. When the correlation between independent variables is zero, the variables are said to be orthogonal.

The heteroscedasticity test, according to Ghozali (2018), looks for variance inequality in the regression model of residuals between observations. Heteroscedasticity can be found by examining specific patterns in the scatterplot graph between SRESID and ZPRED, where the X axis represents the standardized residual (predicted Y-actual Y) and the Y axis represents the predicted Y.

The t test is used to determine the significance of each independent variable's constant, specifically if the variables Product Quality (X1), Sales Promotion (X2), and Brand Equity (X3) have a partial (separate) influence on the dependent variable, Customer Loyalty Level (Y).

The F test measures how three independent variables—product quality (X1), sales promotion (X2), and brand equity (X3)—affect the dependent variable, customer loyalty level (Y), at the same time.

Used to determine the percentage of influence of the independent variable, namely variable X, on changes in the dependent variable, namely variable Y. In simple terms, the coefficient of determination is always associated with how much the independent variable is able to explain the variance of the dependent variable.

This test is used to analyze how the condition (rise and fall) of the dependent variable, if two or more independent variables as predictor factors are manipulated (increased or decreased in value). The multiple linear regression equation is:

Y = a + b X1 + b X2 + b X3 + e………1)

Where: Y = Dependent variable

a = constant

b = regression coefficient

X1 = first independent variable X2 = second independent variable X3 = third independent variable

e = error

A validity test can be used to assess a questionnaire's applicability or validity, claims Ghozali (2018). If the questionnaire's questions can yield information that will be measured and identified by a precise measurement procedure, it will be considered appropriate. Each question indicator is considered legitimate if Sig

<= 0.05. This test assesses if the questionnaire's components can measure the study's outcomes. The following are the findings of this study's validity test:

Source : Data processed by SPSS (2024)

The output of the significance findings for every indicator indicates that the results are significant (0.000 < 0.05). Thus, it can be said that all of the question indicators have reliable findings.

Reliability test is one of the measuring tools for a questionnaire which is an indicator of a time variable. Reliable data in a research instrument means that the data can be trusted. To measure it, you can use the Cronbach alpha technique, namely the magnitude of the resulting alpha value compared to > 0.70 Decision making if the alpha value < 0.70 then the question of the variable is not reliable and if the alpha value > 0.70 then the question of the variable is reliable.

Source : Data processed by SPSS (2024)

The reliability of the questionnaire employed in this study is indicated by the Cronbach's Alpha value of 0.909 > 0.70, which can be deduced from the data in the above table.

Source : Data processed by SPSS (2024)

According to the data in the above table, the Sig value (2-tailed) for variable (X1) is 0.000 <0.05, for variable (X2) it is 0.000 <0.05, for variable (X3) it is 0.000 <0.05, and for variable (Y) it is 0.000 > 0.05. As a result, one could argue that the data in this study is not appropriately dispersed

Source : Data processed by SPSS (2024)

In contrast, the Variance Inflation Factor (VIF) value for the variables of Product Quality (X1), Sales Promotion (X2), and Brand Equity (X3) is 2.477 < 10.00, 2.335 < 10.00, and 2.937 < 10.00, respectively, according to the output table "coefficients" in the "Collinearity Statistics" section. The tolerance value for the Product Quality variable (X1) is 0.404 > 0.10, Sales Promotion (X2) is 0.428 > 0.10, and Brand Equity (X3) is 0.341 > 0.10. With values less than 0.90, there is also no association between the independent variables. Therefore, it may be said that there is no multicollinearity based on the multicollinearity test's decision-making basis.

Based on the image above, it shows that there is no heteroscedasticity because the points are spread randomly above and below the number 0 on the Y axis. Thus, it can be concluded that the regression model is suitable for predicting brands based on the input of independent variables, namely product quality, marketing strategy, and promotion.

Source : Data processed by SPSS (2024)

Based on the table data above, the regression equation is as follows:

Y = a + b X1 + b X2 + b X3 + e 2) Y = 5.501 + 0.204 X1 + 0.151 X2 + 0.437 X3 + e 3)

The following may be inferred from the regression equation above:

coefficient of variable X1 = 0.204.

With a significance level of 5%, the t-test is a test used to determine whether the independent variables—Product Quality (X1), Sales Promotion (X2), and Brand Equity (X3)—have a positive and significant influence on the dependent variable, Customer Loyalty (Y). The following are the findings of this study's t-test:

Source : Data processed by SPSS (2024)

The t table is 1.985 with n = 100 and df = 100-2 = 98. The aforementioned data leads to the conclusion that the hypothesis is accepted or that the independent variable X partially influences the dependent variable Y, as indicated by the t value of 4.304 > 1.985 with sig 0.000 < 0.05.

Source : Data processed by SPSS (2024)

F table = (k, n-k) = (3, 100-3) = (3.97) was produced with n = 100, and F table then obtained 2.70. According to the data above, the f count value is 68.312 > F table 3.10, and the sig. value is 0.000 < 0.05, indicating that the variables of product quality (X1), sales promotion (X2), and brand equity (X3) all have an impact on customer loyalty (Y) at the same time. Therefore, it may be said that H3 is accepted, indicating that variable X and variable Y are influenced at the same time.

Source : Data processed by SPSS (2024)

The Adjusted R Square value is 0.671, or 67.1%, as can be seen from the Determination Coefficient Test (R2) in the table above. This suggests a relationship between the three independent variables: product quality (X1), sales promotion (X2), and brand equity (X3). The study's dependent variable, customer loyalty (Y), has an explanation value of 0.671 (67.1%). The remaining proportion, however, is influenced by other variables that were not taken into account in the study's regression model (100% - 67.1% = 32.9%).

The expected benefits of the results of this study include:

Researchers can investigate factors such as customer satisfaction, product or service quality, perceived value, customer experience, and emotional connection to the brand.

Researchers can classify loyalty based on the level of involvement, namely behavioral loyalty (repeat purchases), affective loyalty (liking and trusting the brand), and cognitive loyalty (believing the brand is the best choice).

Researchers can examine how consumer loyalty impacts revenue, customer retention, word of mouth, and brand loyalty.

Research can examine how reference groups (such as family, friends, or community) can influence consumer purchasing decisions and loyalty.

Research can examine how customer satisfaction levels (compare product/service performance with customer expectations) are related to loyalty.