The Effect of Brand Awareness and Service Quality on Customer Satisfaction and Its Implications for Container Terminal Customer Loyalty

: The purpose of this study was to determine the effect of brand awareness and service quality on customer satisfaction and the implications for customer loyalty in container terminals. Object research in Port of Tanjung Priok, PT. Jakarta International Container Terminal (JICT). This study uses quantitative research, with a sample size of 150 respondents from 500 population. Data collection techniques using questionnaires and data analysis using path analysis. The results of this study indicate: There is a significant positive (unidirectional) effect of Brand Awareness on Customer Satisfaction when T-Statistics value (3.171) > T table value (1.976) and P-value (0.002) <0.05, next there is a significant positive (unidirectional) effect of Brand Awareness on Consumer Loyalty when T-Statistics value (6.185) > T table value (1.976) and P-value (0.000) <0.05, then our research finding significant positive (unidirectional) effect of Service Quality on Customer Satisfaction when T-Statistics value (4.512) > T table value (1.976) and P-value (0.000) <0.05. There is a significant positive (unidirectional) effect of Service Quality on Consumer Loyalty when T-Statistics value (5.494) > T table value (1.976) and P-value (0.000) <0.05. For the last there is a significant positive (unidirectional) effect of Consumer Loyalty on Customer Satisfaction when T-Statistics value (4.895) > T table value (1.976) and P-value (0.000) <0.05. Based on the results of this study, it was found that brand awareness is very influential. Hence, container terminal management in the future can continue to improve branding-based business models that create the ability for them to win the competition.


INTRODUCTION
The development of technology and industry has an impact on human life, especially in today's business world.In addition, the current era of competition between businesses is getting higher, followed by an increase in the number of business players offering the same product.The emergence of increasingly fierce business competition, the company must be able to develop and survive so as not to lose to its competitors.One of the important things for companies to do and pay attention to is to retain existing customers, by continuing to innovate so that consumers do not leave the company and choose other products (Nofriyanti, 2017).Currently, the development of the business world in Indonesia is increasing and intense competition requires companies to have the ability to compete in the market so that they can continue to grow and develop well in the long term.The business sector that has a high level of competition is in the service sector.In line with these developments, one of them is the service business sector at the container terminal which has promising business opportunities.Given that the majority of import and export activities in Indonesia and the world today use container mode or in other words containerization.Meanwhile, the growth of other container terminals has made business competition more open between container terminals, especially in the Tanjung Priok Port working area, there are 5 (five) international container terminals.Each terminal has a Terminal Operating System / TOS system that is recognized as having its own reliability, a variety of the latest and modern loading and unloading equipment and reliable digital services.Whatever strategy is used, the goal is to have high brand awareness, the best quality of service which of course can satisfy customers and ultimately can increase the loyalty of its terminal users.

METHODS
The research conducted is quantitative research.Sugiyono (2010: 13) states that quantitative research is research based on the philosophy of positivism, used to research on certain populations or samples, sampling techniques are generally carried out randomly, data collection using research instruments, data analysis is quantitative statistics with the aim of testing predetermined hypotheses.This research includes correlation research.Correlation research is research conducted by researchers to determine the level of relationship between two or more variables, without making changes, additions, or manipulations to existing data (Arikunto, 2010: 4).
The population in this study were 500 people and they were users of JICT container terminal services consisting of shipping companies, depots, exporters, importers, forwarding and trucking companies.The sampling technique used a purposive sample.This technique is a way of taking subjects not based on strata, random, or area but based on a specific purpose (Arikunto, 2010: 183).The number of samples in this study were 150 respondent samples.The data collection technique used in this study was to use a questionnaire either carried out directly personally, the JICT customer service team or the 3rd party (three) who was directly appointed in research activities in conjunction with CSI 2022.The questionnaire is a data collection technique that is carried out by giving a set of questions or written statements to respondents to answer.
The method used in this research is path analysis.Path analysis is used by using correlation, regression and path so that it can be known to arrive at the intervening variable.After the basic assumptions mentioned above can be fulfilled as the basis for research on the path analysis method, the initial stage in applying the path analysis model is to formulate a structural model equation and path diagram based on a terrorist study.This path analysis technique will be used in testing the amount of contribution (contribution) indicated by the path coefficient on each path diagram of the relationship between variable X and Y and its impact on Z. Correlation and regression analysis are the basis for path analysis calculations.There are two simultaneous statistical hypotheses formulated in this study, as follows:

RESULT AND DISCUSSION
In this study, hypothesis testing used the Structural Equation Modelling (SEM) analysis technique with the Smart PLS v.3 program.Combining all SEM components into a complete model of the measurement model and structural model, depicted in a path diagram to make it easier to see the causal relationships to be tested can be seen in the following figure:

Indicator Validity Test
To test the validity of indicators, the outer loading value or loading factor is used.An indicator is declared to meet the criteria or in a good category if the outer loading value is> 0.7.Based on the table above, it is known that of the total 36 indicators in this study, all have an outer loading value> 0.7 with values ranging from 0.801 to 0.942, it means that these 45 indicators have a good correlation with their constructs or all indicators can be said to be valid because they have met the requirements for indicator validity.

Internal Reliability Test
The reliability test is carried out by calculating the Composite Reliability value which tests the reliability value of the indicators on a variable.In addition, the reliability test can be strengthened by using the Cronbach alpha value.According to Ghozali, a variable can be declared to meet composite reliability if the composite reliability value is> 0.6 and meets Cronbach's alpha if the Cronbach's alpha value is> 0.7.Based on the table above, it can be seen that the composite reliability value for all research variables is greater than 0.6 with values ranging from 0.950 to 0.962 and the Cronbach's alpha value for all variables is greater than 0.7 with values ranging from 0.940 to 0.956.These results indicate that all variables in the study have met the criteria, so it can be concluded that all variables have a good level of reliability.In addition, the average variance extracted (AVE) value is also used for each variable where the AVE value must be> 0.5 for a good model.Based on the table above, it is known that the AVE value on all variables is greater than 0.5 with values ranging from 0.704 to 0.723.Thus it can be stated that each variable has good convergent validity.

Discriminant Validity Test
From the AVE value that has been obtained, a discriminant validity test is carried out which explains that an indicator is declared to meet discriminant validity if the square root of the AVE in the variable is the largest compared to the correlation of that variable with other variables or by looking at the cross-loading value between the indicator and the latent variable which is greater than the other variables.Based on the table above, it can be seen that the cross-loading value in bold green has the highest value on the variable it forms compared to the value on other variables with a cross loading value of more than 0.7, which ranges from 0.801 to 0.942.So it can be concluded that all indicators have met the criteria and can be said to be good for further analysis.

Inner Model Evaluation Coefficient of Determination (R2)
Evaluation of the Coefficient of Determination (R2) is used to show how much effect or influence the independent variable has on the dependent variable.

Q-Square (Predictive Relevance)
Q-Square predictive relevance measures how well the observed values are generated by the model and also the parameter estimates generated using the blindfolding procedure by looking at the Q square value of the dependent variable.If the Q square value > 0 then it can be said to have a good predictive relevance value.Based on the output above, the Q2 value is 0.633 for the Brand Awareness variable (X1), the Q2 value is 0.635 for the Customer Satisfaction variable (Z), the Q2 value is 0.646 for the Service Quality variable (X2), and the Q2 value is 0.611 for Consumer Loyalty (Y).So it can be concluded that this study has a good observation value because the Q2 value obtained is greater than 0.

F-Square (Effect Size)
The f-square value explains the minimum size that is considered meaningful.The value of 0.02, 0.15 and 0.35 can be interpreted whether the latent variable predictor has a weak, medium, or large influence at the structural level (Ghozali, 2015).Table 7.Effect Size Based on the output above, the F2 value is obtained as follows: 1.On the effect of Brand Awareness (X1) on Customer Satisfaction (Z), an F2 value of 0.072 is obtained, which is between 0.02 to 0.15, which means that statistically the effect of Brand Awareness on Customer Satisfaction has a weak effect.2. On the effect of Service Quality (X2) on Customer Satisfaction (Z), an F2 value of 0.131 is obtained, which is between 0.02 to 0.15, which means that statistically the effect of Service Quality on Customer Satisfaction has a weak influence effect.3. On the effect of Consumer Loyalty (Y) on Customer Satisfaction (Z), an F2 value of 0.188 is obtained, which is between 0.15 and 0.35, which means that statistically the effect of Consumer Loyalty on Customer Satisfaction has a medium effect.4. On the effect of Brand Awareness (X1) on Consumer Loyalty (Y), an F2 value of 0.282 is obtained which is between 0.15 to 0.35, which means that statistically the effect of Brand Awareness on Consumer Loyalty has a medium effect.5. On the effect of Service Quality (X2) on Consumer Loyalty (Y), an F2 value of 0.282 is obtained which is between 0.15 to 0.35, which means that statistically the effect of Service Quality on Consumer Loyalty has a medium effect.

Hypothesis Test
Based on the data processing that has been done, the results can be used to answer the hypothesis in this study.Hypothesis testing in this study was carried out by looking at the T-Statistics value where the research hypothesis can be declared accepted if the T-Statistics value> T table.Hypothesis: H0: There is no influence between the independent variable on the dependent variable partially H1: There is an influence between the independent variable and the dependent variable partially Decision Criteria: -If the T-Statistics value < T table (t(0.05,148) = 1.976) then H0 is accepted.
-If the T-Statistics value> T table (t(0.05,148) = 1.976) then H1 is accepted.) and the P-value (0.000) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that there is a significant positive (unidirectional) effect of Brand Awareness (X1) on Customer Satisfaction (Y).This explains that the higher or better the value of Brand Awareness, the higher or better Customer Satisfaction will be.Likewise, on the contrary, if the value of Brand Awareness is lower or worse, Customer Satisfaction will be lower or decrease.2. Relationship between Brand Awareness (X1) and Consumer Loyalty (Y) A positive path coefficient value of 0.510 was obtained.It is also known, the T-Statistics value (6.185)> T table value (1.976) and the P-value (0.002) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that there is a significant positive (unidirectional) effect of Brand Awareness (X1) on Consumer Loyalty (Y).This explains that the higher or better the value of Brand Awareness, the higher or higher Consumer Loyalty will be.Likewise, on the contrary, if the value of Brand Awareness is getting lower or worse, Consumer Loyalty will be lower or decrease.3. Relationship between Service Quality (X2) and Customer Satisfaction (Z) A positive path coefficient value of 0.342 was obtained.It is also known, the T-Statistics value (4.512)> T table value (1.976) and the P-value (0.000) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that there is a significant positive (unidirectional) effect of Service Quality (X2) on Customer Satisfaction (Z).This explains that the higher or better the value of Service Quality, the higher or better Customer Satisfaction will be.Likewise, on the contrary, if the value of Service Quality is lower or worse, Customer Satisfaction will be lower or decrease.4. Relationship between Service Quality (X2) and Consumer Loyalty (Y) A positive path coefficient value of 0.461 was obtained.It is also known, the T-Statistics value (5.494)> T table value (1.976) and the P-value (0.000) <0.05, so the hypothesis H0 rejects and H1 is accepted.This means that there is a significant positive (unidirectional) effect of Service Quality (X2) on Consumer Loyalty (Y).This explains that the higher or better the value of Service Quality, the higher or higher Consumer Loyalty will be.Likewise, on the contrary, if the value of Service Quality is lower or worse, Consumer Loyalty will be lower or decrease.5. Relationship between Consumer Loyalty (Y) and Customer Satisfaction (Z) A positive path coefficient value of 0.461 was obtained.It is also known, the T-Statistics value (5.494)> T table value (1.976) and the P-value (0.000) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that there is a significant positive (unidirectional) effect of Consumer Loyalty (Y) on Customer Satisfaction (Z).This explains that the higher or better the value of Consumer Loyalty, the higher or better Customer Satisfaction will be.Likewise, on the contrary, if the value of Consumer Loyalty is lower or worse, Customer Satisfaction will be lower or decrease.) and the P-value (0.000) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that indirectly there is a significant positive (unidirectional) effect of Service Quality (X2) on Customer Satisfaction (Z) through Consumer Quality (Y).

CONCLUSION
In the container terminal industry competition, an overview of the research results is obtained, the higher or better the value of Brand Awareness, the higher or higher Customer Satisfaction will be.Likewise, on the contrary, if the value of Brand Awareness is lower or worse, Customer Satisfaction will be lower or decrease.The above also applies to Brand Awareness to Customer Loyalty, Service Quality to Customer Satisfaction, Service Quality to Customer Loyalty and Customer Loyalty to Customer Satisfaction.Furthermore, container terminal management should focus on increasing brand awareness because it is proven to be the most influential in customer loyalty.
0 Hypothesis testing rules using the F table, with rules: 1.The Fcount value is greater than the F table value (Fcount ≥Ftabel) thus Ho is rejected and Ha is accepted.2. Fcount value is greater than the F table value (Fcount ≤Ftabel) thus Ho is accepted and

Table 8 .
Hypothesis Test Based on the table above, we found that: 1. Relationship between Brand Awareness (X1) and Customer Satisfaction (Z) A positive path coefficient value of 0.259 is obtained.It is also known, the T-Statistics value (3.171)> T table value (1.976

Table 9 .
Indirect Effect Based on the table above, we found that: 1.The relationship between Brand Awareness (X1) to Customer Satisfaction (Z) through Consumer Loyalty (Y).A positive path coefficient value of 0.196 is obtained.It is also known, the T-Statistics value (3.994)> T table value (1.976) and the P-value (0.000) <0.05, so the H0 hypothesis is rejected and H1 is accepted.This means that indirectly there is a significant positive (unidirectional) effect of Brand Awareness (X1) on Customer Satisfaction (Z) through Consumer Quality (Y). 2. Service Quality Knowledge (X2) on Customer Satisfaction (Z) through Consumer Loyalty (Y).A positive path coefficient value of 0.177 was obtained.It is also known, the T-Statistics value (3,550)> T table value (1,976