The Impact of Service Quality, Price, and Brand Image on Consumer Loyalty at Yamaha Motor Workshops in Bekasi

This research aims to determine whether there is a partial and simultaneous significant effect between service quality, price, and brand image on consumer loyalty at Yamaha Motor Workshops in Bekasi. This research method uses a quantitative descriptive approach, the data collection used in this study are the google form questionnaires that distributed to their consumers, data analysis techniques using classical assumption techniques, multiple linear regression, T-test and F-test to test and prove the hypothesis of this study using the SPSS application, using incidental sampling technique methods with a sample of 150 respondents. This study found that the variables of service quality, price, and brand image together have a significant effect on consumer loyalty.

This research aims to determine whether there is a partial and simultaneous significant effect between service quality, price, and brand image on consumer loyalty at Yamaha Motor Workshops in Bekasi. This research method uses a quantitative descriptive approach, the data collection used in this study are the google form questionnaires that distributed to their consumers, data analysis techniques using classical assumption techniques, multiple linear regression, T-test and F-test to test and prove the hypothesis of this study using the SPSS application, using incidental sampling technique methods with a sample of 150 respondents. This study found that the variables of service quality, price, and brand image together have a significant effect on consumer loyalty.

INTRODUCTION
Over the time, in this modern era, consumers are very smart in making decisions. On the other hand, consumer loyalty is a very important factor. And why must consumer loyalty be maintained, because someone can be said to be a consumer if that person buy products or use services on an ongoing basis or repeatedly within a certain period of time.
Besides that, (Mashuri, 2020) states that creating customer value to fulfill customer desires requires various combinations of various combinations of existing marketing strategies. This means that strategic combinations are part of the attitude dimension of consumer loyalty towards something product. Service quality is the expected financial level and control over the level of excellence to fulfill customer desires according to (Tjiptono, 2012). Besides that (Setyaningriani, 2017) the increasing number of motorbike users, consumers will also definitely need a place to maintain and repair these motorcycles. So that the vehicle is suitable for use and always maintained and comfortable to use for every consumer. There are also new products and services that are made at quite high prices, therefore there is intense competition for service providers between authorized dealers who cooperate with other motorcycle brands. Therefore, service providers will further improve their goals in order to satisfy consumers who come and will continue to choose one service provider continuously and not move to another service provider.
This satisfaction can be obtained by providing services to consumers as optimally as possible. That way consumers are sure to feel satisfied with the service received. Yamaha Motor Workshop is an official Yamaha repair shop engaged in services and retail spare parts. Which provides service services and replacement of spare parts or motor spare parts. In the increase in the number of customers Yamaha Motor Workshop experienced ups and downs with the existing tight competition. Due to consumer ups and downs, therefore the Yamaha Motor Workshop service providers hope to evaluate the price and quality of service to consumers so that they are loyal to the company. (Kotler, 1994) emphasized that consumer satisfaction is the level of one's feelings after comparing the performance (or results) that he feels compared to his expectations. Satisfied customers are also more difficult to change the selection. High satisfaction will create emotional attachment with the brand. The result is high customer loyalty (Kotler, 1994).

THEORETICAL REVIEW
Marketing is an important part for an organization or company, one of the main activities it does is to maintain the viability of a company and the organization. Marketing in English: marketing is the activity and process of creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and the general public. Marketing begins with meeting human needs which then grow into human desires.
According to (Kotler & Armstrong, 2018) marketing is a social and managerial process by which a person or group obtains what they need and want through creating and exchanging products and value. Marketing is an overall system of business activities shown to plan, determine prices, promote, distribute goods and services that offer needs to both existing and potential buyers (Boyd, et al., 2000). It can be concluded that marketing is carried out by companies or organizations to benefit the perpetrators by conveying a value to consumers. And the company must maintain good relations with its customers. Therefore, knowledge regarding the marketing mix is needed. (Lupiyoadi, 2001) suggests that service quality can be defined as how far the difference between reality and consumer expectations for the service they receive or obtain. Meanwhile, according to (Lovelock, 2005) argues that service quality is the level of excellence expected and control over the level of excellence is to meet expectations.

Price
According to (Kotler & Armstrong, 2018) the amount of money charged for a product or service from the definition above can be concluded that price is the amount of money paid or exchanged to obtain goods or services to obtain benefits from owning or using goods and service.

Brand Image
According to (Dharma & Sukaatmadja, 2015) brand image is an opinion or assumption about a brand in the minds of consumers that must be maintained. Brand image also determines service quality (Ardiani, 2017) stating that brand image is the most important thing in determining service quality. Brand image is seen as an important factor in service evaluation according to (Zeithaml & Bitner, 1996).

Consumer Loyalty
Loyalty is a manifestation of the fundamental human need to belong, support, gain a sense of security, build attachment and create an emotional attachment. Meanwhile, consumer loyalty is a behavioral drive to make purchases repeatedly and to build consumer loyalty to products or services.
According to (Bambang & Heriyanto, 2017) brand trust will determine consumer loyalty to the brand and trust will have the potential to create highvalue relationships.

Conceptual Framework
The development of transportation progress has progressed quite rapidly from year to year, especially from 2-wheeled vehicles such as motorbikes. Yamaha Motor Workshop in Bekasi is a subsidiary company that works with all Yamaha networks. Yamaha Bali Indah is engaged in a service company that offers services and retail sales of spare parts for Yamaha motorbikes.
Yamaha Motor Workshop in Bekasi has become the choice of many Yamaha motorbike users because there is a lot of competition, therefore Yamaha Motor Workshop in Bekasi always tries to improve service quality, price quality and brand image in order to maintain its existence in the field of service companies. X 1 : independent variable (service quality) X 2 : independent variable (price) X 3 : independent variable (brand image) Y : dependent variable (consumer loyalty)

METHODOLOGY
The research approach used in this study is to use quantitative methods, other data can be processed using a tabulated questionnaire about the influence of service quality, price, and brand image on consumer loyalty. This method can also be called a scientific method because it meets scientific principles, namely concrete/empirical, objectively measurable, rational and systematic.
The quantitative approach is an approach in research proposals, processes, hypotheses, field work, data analysis and data conclusions up to writing using aspects of measurement, calculation, formulas and certainty of numerical data.
Population according to (Widiyanto, 2010) population is a combination or collection of objects that will be generalized from research results. Meanwhile, according to (Sugiyono, 2017) "population is a generalization consisting of objects/subjects that have certain qualities and characteristics set by researchers to study and then draw conclusions".
Sample according to (Arikunto, 2014) "sample is part or representative of the population studied. Meanwhile, according to (Sugiyono, 2017) the sample is part of the number and characteristics possessed by the population. So, in conclusion, the sample is part of the population to be studied and can represent a true picture of the population. If the population is large, it is impossible for researchers to study everything in the population. Due to limited time, funds and manpower, researchers can use samples taken from this population. The author uses a sample and population of consumers of Yamaha Motor Workshop in Bekasi.
In the sampling method used in this study namely using accidental sampling method and according to (Sugiyono, 2017) accidental sampling is taking respondents as a sample based on chance, that is, anyone who happens to meet the researcher can be used as a sample, if the person who happens to meet the researcher and is suitable as a source of data with the main characteristic is that person is a consumer or Yamaha Motorcycle Workshop customer in Bekasi (Variano, 2017).
The reason for using this method is because the population size is unknown. So this method is very appropriate in this study. This research was carried out when researchers submitted questionnaires when consumers were making transactions at the Yamaha Motor Workshop in Bekasi.
The measurement scale is the agreement that is used as a reference to determine the length and shortness of the intervals that are in the measuring instrument, so that if the measuring instrument is used in measurement it can produce quantitative data. In this section, researchers use data collection techniques on questionnaires, the author uses a Likert's Scale. The Likert's scale is used to estimate the attitudes, opinions and perceptions of each individual or group of individuals about social events. With a Likert's scale, the variables to be measured are translated into variable indicators. After that the indicators will be used as a starting point for compiling instrument elements which can be in the form of statements or questions. The answers to each element of the question using the Likert's scale have a gradation from very positive to very negative and are given a score of 1 to 5.

Validity Test
According to (Sujarweni & V. Wiratna, 2018) the validity test is used to test the validity of the instrument in the research results, so the corrected item total correlation is used with the help of SPSS application. Validity test should be used for each question in the validity test. The results of r calculation are compared with r table where df = n-2 with a significance of 5%. Basic validity testing is as follows: 1. If r count is positive and r count > r table, then the variable is valid.
2. If r count is negative and r count < r table, then the variable is invalid.

Reliability Test
According to (Sujarweni & V. Wiratna, 2018) reliability is a measure of the stability and consistency of respondents in answering matters related to the structure of the question structure which is a measure of a variable and is arranged in a questionnaire form. To test the reliability of the questionnaire, the Cronbach Alpha technique was used. The reliability of an instrument has a high level of reliability if the Cronbach Alpha coefficient is obtained > 0.60. The basis for reliability testing is as follows: 1. When the Cronbach Alpha value is > 0.60, the data tested is declared reliable. 2. When the Cronbach Alpha value is < 0.60, the data tested is declared not reliable.

Normality Test
One of the basic assumptions that must be met before carrying out a parametric statistical test is the Kolmogorov-Smirnov Normality Test, according to (Sujarweni & V. Wiratna, 2018) the normality test aims to test whether in the regression model, the grille or residual variables have a normal distribution. In this normality test there are 2 ways to detect whether the residuals are normally distributed or not, namely by the Kolmogorov-Smirnov Normality Test with the following criteria: 1. If Significance > 0.05, then the data is normally distributed. 2. If Significance > 0.05, then the data is not normally distributed.

Multicollinearity Test
The multicollinearity test has the goal of testing in the regression model to find out if there is a correlation between the independent variables, a good regression model should not have a correlation between the independent variables, if the independent variables are correlated then these variables are not orthogonal. Orthogonal variables are independent variables whose values among independent variables are equal to zero (Ghozali, 2018). In regression analysis, a model must be free from multicollinearity symptoms and to detect whether a model has multicollinearity is if the VIF value < 10 or the Tolerance value is > 0.01, then multicollinearity does not occur.

Heteroscedasticity Test
Basically, heteroscedasticity is testing the difference in residual variance from one observation period to another. The way to predict whether there is heteroscedasticity is if the data points spread above and below or around the number 0, these points do not form a wavy pattern widening then narrowing and widening again, where the spread of data points is not patterned (Sujarweni & V. Wiratna, 2018).

Multiple linear regression analysis test
Multiple linear analysis is a statistical analysis that combines two or more independent variables and according to (Sujarweni & V. Wiratna, 2018) multiple linear regression analysis is a regression that has one independent variable.

Simultaneous F Test
According to (Ghozali, 2018) the F test is used to determine whether all the independent variables included in the model have a joint effect on the dependent variable. The F test is used to prove whether there is an influence between the independent variables on the dependent variable simultaneously. To test the hypothesis H0 : b = 0 then the steps will be used to test the hypothesis is the F test as follows: 1. Determine H0 and Ha H0 = 0 (does not have a significant effect between the independent variable and the dependent variable). Ha = 0 (has a significant effect between the independent variable and the dependent variable).

Determine the level of significance
The significant level used is 5% or (α) = 0.05. 3. Take a look at the calculated F value by looking at the output (Anova  table) and compare with F table. 4. Determine the criteria for accepting and rejecting H0, by looking at the probability level, namely: a. If the significance value of F > 0.05, then H0 is accepted. That is, simultaneously the independent variable does not have a significant effect on the dependent variable. b. Conversely, if the significance value of F ≤ 0.05, then H0 is rejected and Ha is accepted.

Partial t Test
According to (Sujarweni & V. Wiratna, 2018) the t test is a test carried out to determine the relationship of the independent variable to the dependent variable partially with a significance level of 5%.
1. Determine H0 and Ha  H0 : has no significant effect between independent and dependent variables.  Ha : has a significant influence between the independent variable and the independent variable.

Determine the level of significance
The level of significance used is 5% or (α) = 0.05.

Determine the value of t count
Comparing the calculated t value with t table. 4. Determine the following H0 acceptance and rejection criteria if the significance is < 0.05 then H0 is rejected if the significance is > 0.05 then H0 is accepted.

Coefficient of Determination Test (R 2 )
According to (Ghozali, 2018), the coefficient of determination test (R²) is to measure how far the model can explain the variation of the independent variables. The value used in a coefficient of determination is how large it is from zero to one.

RESULTS & DISCUSSIONS Validity Test
Validity test is to determine the level of validity of instrument (questionnaire) used in data collection. This validity test was conducted to find out whether the questions presented in the questionnaire were truly able to express with certainty what would be studied. The results of r count (the results of the Correlated Item-Total Correlation column) are compared with r tables where df = n-2 with a significance of 5%. If r table < r count then declared valid.
The value of r table is determined using the formula: df (degree of freedom) = n (number of respondents) -2, with a significance level of the twoway test at a significance value of 0.05. So, the value of df = 150 -2 = 148, so that the r table value is 0.1603. Based on this, the questionnaire can be said to be valid if the results of the validity test of the questionnaire have a greater r count than the r table value. To find out the results of the validity test that has been tested can be seen in the following tables:  (2023) From the table 1 above, it can be seen that the R count value obtained by each variable question has a greater value than the R table which has a value of 0.1603, so it can be concluded that the five statement items or questions in the variable X1 is declared Valid. From table 2 above it can be seen that the calculated R count is obtained by each question the variable X2 has an R count value > the R table which has a value of 0.1603, so it can be concluded that the five statement items or questions in the X2 variable are declared Valid. From table 3 above it can be seen that the r count value obtained by each variable question has a greater R count value than the R table which has a value of 0.1603, so it can be concluded that the five statement items or questions in variable X3 declared valid. From table 4 above it can be seen that the R count value obtained by each question of variable Y has a greater R count value than the R table which has a value of 0.1603, so it can be concluded that the five statement items or questions in variable Y declared valid.

Reliability Test
The reliability test was carried out on the stated question items valid and whether an indicator can be trusted enough to be used as a data collection tool. The criteria for a research instrument are said to be reliable if the Cronbach Alpha value is > 0.70.

Normality Test
The normality test is a test of the distribution of the data to be analysed whether the results are normal or not and aims to determine the distribution of data in the variables that will be used in research. The good and feasible data that used in a study is a normal distribution data. In the normality test above, if the significance value is > 0.05 then the variable is normally distributed and vice versa if the significance is < 0.05 then the variable is not normally distributed. From the results of table 6 above it can be seen that the Asymp. Sig. (2-tailed) value is 0.068 > 0.05, this proves that the data is normally distributed.  Figure 2. Heteroscedasticity Test Figure 2 shows that the points spread randomly and spread well above and below the number 0 on the Y axis, and the points spread randomly without forming a particular pattern, meaning that there is no heteroscedasticity in the multiple regression model. So this regression model is feasible to use to predict Variable Y based on the variables that influence it, namely Variables X1 and X2.

Multiple Linear Regression Analysis
Multiple linear regression is used to obtain a mathematical relationship in the form of an equation between the independent variables and the dependent variable and is only based on a dependent variable. time there is an increase of 1 in the value of the X1 variable, it will also be followed by an increase in the Y variable of 0.425. 3. The coefficient value of the variable X2 is 0.282. This means that if every time there is an increase of 1 in the value of the X2 variable, it will also be followed by an increase in the Y variable of 0.281. 4. The coefficient value of the variable X3 is 0.107. This means that if every time there is an increase of 1 in the value of the X3 variable, it will also be followed by an increase in the Y variable of 0.107. From the results of table 9 above it can be seen for the variable (X1) that the t-count value is 7.953 > 1.655 (t table) with a significance of 0.000 < 0.05. Then the hypothesis is accepted which means that partially the variable (X1) has a significant effect on the variable (Y).

Hypothesis Test Partial t Test
Furthermore, for the variable (X2), a t-count of 5.645 > 1.655 (t table) is obtained with a significance of 0.000 < 0.05. Then the hypothesis is accepted which means that partially the variable (X2) has a significant effect on the variable (Y).
The variable (X3), a t-count of 2.052 > 1.655 (t table) is obtained with a significance of 0.042 < 0.05. Then the hypothesis is accepted which means that partially the variable (X3) has a significant effect on the variable (Y).  ) with a significance value of 0.000 < 0.05. So the hypothesis is accepted, which means that simultaneously and significantly (X1), (X2) and (X3) have an effect on (Y).  (2023) Based on table 11 above, the Adjusted R Square value is 0.527 or 52.7%. This means that variable Y can be explained by variations of the three independent variables, namely variables X1, X2 and X3. While the remaining 47.3% is caused by other factors that are outside the variables in this study.

CONCLUSIONS AND RECOMMENDATIONS
This study aims to determine the effect of service quality, service, price, and brand image on consumer loyalty at Yamaha motorcycle repair shops in Bekasi.
Based on data analysis and discussion of the research results, it can be concluded that: 1. Service quality has a positive and significant effect on consumer loyalty. 2. Price has a positive and significant effect on consumer loyalty. 3. Brand image has a positive and significant effect on consumer loyalty. The researcher realized that after conducting this research, the primary data was processed, so that there were deficiencies and weaknesses in the research. These deficiencies and weaknesses will be taken into consideration for future researchers if they wish to conduct a study with the same theme or title.

FURTHER STUDY
Every research is subject to limitations; thus, we need some suggestions that can make it better for the next research.