The Impact of Service Performance on Customer Satisfaction and Customer Loyalty During Covid-19 Pandemic: A Case Study of Bank BTN

This study is to analyze the impact of service performance and customer satisfaction as a moderating variable on customer loyalty of Bank BTN during COVID-19 Pandemic. The object of this research is the customers of Bank BTN. This research was conducted on 200 respondents using a quantitative descriptive approach. Determination of sample size using purposive sampling technique, purposive sampling technique is a technique of determining the sample with certain considerations. Methods of data collection using survey methods, with the research instrument is a questionnaire. The approach used in this research is the Structural Equation Model with the Smart-PLS analysis tool. This study proves that service performance has a positive and signi�icant impact on customer satisfaction, service performance has a positive and signi�icant impact on customer loyalty, and customer satisfaction has a positive and signi�icant impact on customer loyalty. The implication of this study is to encourage the banking industry to improve and maintain their service performance especially during this pandemic to increase their customer satisfaction and customer loyalty level. Copyright © 2022 Authors. This is an open access article distributed under the Creative Commons Attribution License (CC-BY-SA 4.0) which permits use, distribution and reproduction in anymedium, provided the original work is properly cited & ShareAlike terms followed.


INTRODUCTION
The extraordinary development of the use of information technology which has now opened the world's eyes to a new world change, a new marketplace, the current era of globalization has a broad impact on the growth of the banking world in Indonesia. With the proliferation of banking products today, it is an indication that every bank is trying to bring out its superior products. which is followed by various ease of service facilities. This is marked by the establishment of many private banks, both local and foreign investors, as well as conventional and Islamic banks. All of this is inseparable from the various successes of development and Indonesia's rapid economic growth (Tumbel, 2016).
The use of bank services nowadays has become common place, especially for people who live in urban areas. As banking competition becomes more intense, it becomes increasingly dif�icult for the Bank to maintain customer service so as not to move to another bank. To increase and retain customers, the Bank must maintain a good image in front of customers. This encourages the Bank to provide the best service and offer products and services to attract and retain customers (Siagian, 2020).
Customer behavior is not easy to predict, maybe they are very satis�ied with the bank's services, but they will still move if another bank provides service performance in accordance with expectations, especially if the customer is in the top economic class who has the potential to become a geek customer. Customer satisfaction is only one of several causes for the formation of customer loyalty, improving the relationship between service performance, product quality, institutional image, and customer satisfaction, which is re�lected through loyalty, by using customer satisfaction as a moderating variable in this relationship, so that customer satisfaction becomes a factor that can affect and strengthen customer loyalty (Anjani, 2018).
In terms of maintaining and increasing customers, Banks need to provide excellent service quality where customers feel it is right to choose the Bank in using the Bank's banking services. There are also services for customers who have loans or credit, if they want to make installment payments, they can transact through a bank account that has collaborated with the bank. This statement is supported by (Siagian, 2020) stating that customer satisfaction is something that can be determined by customers based on the service and provision of Bank products to customers. In addition, as said by (Tumbel, 2016), when the Bank offers products and services with good service, makes it easier for customers to transact, offers high savings and deposit interest rates, and provides low interest rates on loans, customers feel satisfaction and increase customer loyalty, on the other hand, if the service provided by the Bank is not good, does not provide bene�its for the customer, then the customer's feeling of dissatisfaction with the Bank will arise.
Customer satisfaction is the feeling (feeling) that buyers feel from the company's performance that meets their expectations. However, viewed from the perspective of consumer behavior, 'customer satisfaction' then becomes something complex. Behavior after purchase will lead to a satis�ied or dissatis�ied attitude in consumers, then consumer satisfaction is a function of buyer expectations for products or services with perceived performance (Dharmayanti, 2006). This research was conducted at Bank BTN, which is engaged in banking, which according to researchers from Bank BTN scored extraordinary achievements during a pandemic as the following table of �inancial performance achievements in 2020: Based on the data in Table 1 above, the company made extraordinary achievements by earning more than 6 times pro�its from the previous year from 209 billion to 1,60 trillion, this is an extraordinary achievement considering that we are currently still in a pandemic condition. This means that in the �inancial industry, such as banking, it is necessary to pay attention to various aspects such as the services provided by Bank BTN and customer satisfaction to improve aspects of customer loyalty. Loyal customers will make new transactions and recommend to others so that they will print greater pro�its.
It has been more than a year that almost all countries in the world have been attacked by a deadly virus, namely COVID-19, COVID-19 itself is a virus that causes disease in humans and animals. In humans, it usually causes respiratory tract infections, ranging from the common cold to serious diseases such as Middle East Respiratory Syndrome (MERS) and severe acute respiratory syndrome (SARS). A new type of coronavirus found in humans since an extraordinary event appeared in Wuhan, China, in December 2019, was later named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2) and caused Coronavirus Disease-2019 . COVID-19 is caused by SARS-COV2, which belongs to the same large family of coronaviruses that caused SARS in 2003, only with a different type of virus. The symptoms are like SARS, but the death rate for SARS (9.6%) is higher than for COVID-19 (less than 5%), although the number of cases of COVID-19 is much higher than that of SARS. COVID-19 also has a wider and faster spread to several countries than SARS. Covid-19 entered Indonesia in early March. Then the Government took a wise step by issuing PP No. 21 of 2020 for handling Covid-19 by implementing PSBB (Large-Scale Social Restrictions).
PSBB is a restriction on certain activities in an area suspected of being infected with COVID-19. This of course will affect the community's economy, especially the customers of Bank BTN. Such as the use of Online Banking as one of the services provided by Bank BTN when there are restrictions on residents and the extent of customer satisfaction felt by consumers, especially during the current COVID-19 pandemic. Based on the above phenomenon, the author is interested in studying "The Impact of Service Performance on Customer Satisfaction and Customer Loyalty During Covid-19 Pandemic: A Case Study of Bank BTN". The purpose of this casual research is to identify the following problems: 1. Does Service Performance affect Customer Satisfaction during the COVID-19 pandemic? 2. Does Service Performance affect Customer Loyalty during the COVID-19 pandemic? 3. Does Customer Satisfaction affect Customer Loyalty during the COVID-19 pandemic?

LITERATURE REVIEW Service Performance
Service performance is the performance of the service received by consumers themselves and assesses the quality of the service they really feel (Cronin and Taylor, 1994). Among the researchers who disagree with Parasuraman, Zeithaml, and Berry are Cronin andTaylor (1992, 1994) who stated that the measurement of service quality as proposed by the SERVQUAL (Service Quality) model has caused confusion and ambiguity. This author states that performance-based measures will better re�lect the quality of services. In addition, researchers also admit that the measurement of service quality with the SERVQUAL (Service Quality) model forms a less strong paradigm (Bitner, Bolton, and Drew, 1992) because consumer expectations of service quality refer to consumer expectations of service providers in general, while perceptions of service performance leads to a more speci�ic service company. Kotler and Keller (2007) de�ined satisfaction as a person's feelings of pleasure or disappointment that arise after comparing the expected performance (outcome) to the expected performance (outcome). If performance is below expectations, the customer is dissatis�ied. If the performance meets expectations, the customer is satis�ied and if the performance exceeds expectations, the customer is very satis�ied or happy. Customer satisfaction is the customer's response to the evaluation of the perceived discrepancy between initial expectations before purchase and the actual performance of the product felt after using it. Indicators of consumer satisfaction, namely: willingness to repurchase or continue to use the product/service, state positive things about the product/service, willingness to convince friends or family to use the product/ service, and willingness to continue using the product/service. these services even though there are many other similar products/services (Tjiptono, 2000).

Customer Loyalty
Customer loyalty has an important role in a company, retaining them means improving �inancial performance and maintaining company viability, this is the main reason for a company to attract and retain customers. The concept of customer loyalty is more directed to behavior compared to attitude and a loyal customer will show buying behavior which can be interpreted as a pattern of regular and long-term purchases, which are carried out by decision-making or decision-making units. (Grif�in 2002).

RESEARCH METHOD
In the preparation of this study, the researcher used the casual analysis method, where this method aims to test the hypothesis about the effect of one or several independent variables on the dependent variable. Casual analysis is a causal relationship. The research was conducted to determine the effect of one or more independent variables (independent variables) on the dependent variable (dependent variable). The independent variable is the variable that affects or causes the change or emergence of the dependent (bound) variable while the dependent variable is the variable that is affected, or which is the result of the independent variable. So in causal research there are independent variables that in�luence and dependent variables that are in�luenced (Sugiyono, 2014).
The approach used in this research is a quantitative approach. The theory proposed by Noor (2011) explains that the quantitative approach is a method for testing certain theories by examining the relationship between variables. Of these variables are usually measured with research instruments so that data consisting of numbers can be analyzed based on statistical procedures.
The research variables used in this study are independent variables and dependent variables. In this case, the independent variables are Service Performance and Customer Satisfaction as for the dependent variable is Customer Loyalty.
Kindly please refer to below �igure 1 for more details: Based on Figure 1 above it comes to some hypotheses to be analyzed in this research as below: 1. H1: Service Performance has a positive and signi�icant impact on Customer Satisfaction. 2. H2: Service Performance has a positive and signi�icant impact on Customer Loyalty. 3. H3: Customer Satisfaction has a positive and signi�icant impact on Customer Loyalty. Sugiyono (2014) explains that population is a generalization area consisting of objects or subjects that have certain qualities and characteristics that have been determined by researchers to be studied. The population is also not just the number that exists in the object or subject being studied but includes all the characteristics or properties possessed by the object or subject and then a conclusion is drawn. From the above de�inition, it can be concluded that the population is an observation made by researchers to �ind conclusions or results from the study. The population in this study is Bank BTN customers.
International Journal of Business Studies Vol. 6, Special Issue 1, January 2022 According to Sugiyono (2014) the sample is part of the number and characteristics possessed by the population. If the population is large and the researcher is not able to study everything in the population such as limited manpower, funds, and time, the researcher can use samples taken from the population. What is learned in the sample, the conclusions will be applicable to the population. Researchers used non-probability sampling technique in sampling in this study because the probability of the element being selected as a subject is unknown. The sampling method was carried out using the convenience sampling method. Convenience sampling is a technique in selecting research samples, researchers have no other considerations except based on convenience, someone is taken as a sample because that person happens to be in the place or happens to recognize the person. Ferdinand (2006) explains that if the sample size is too large, the model becomes very sensitive, so it is dif�icult to get a good goodness of �it. For this reason, it is recommended that the sample size is 5-10 times the number of manifest variables (indicators) of all latent variables. In this study, there are 30 research indicators so that the minimum sample size is 5 times the number of indicators or 5 x 30 = 150 and the maximum sample is 10 x 30 = 300.
In this study, the researcher used a convenience sampling technique, this was done considering the large number of samples, so the determination of the number of samples and the selected samples in the study was carried out by distributing questionnaires to respondents at random who were accidentally encountered by the researcher.
The type of data used by researchers in this study is primary data. According to Sugiyono (2014) primary data is a data source that directly provides data to data collectors. Examples of primary data are data collected through questionnaires, direct observation in the �ield, interviews, and through an experiment. In this study, the questionnaire as a tool used to conduct a survey.

The researcher also uses PLS (Partial Least Square) which is a method of Component analysis or Variance Based Structural Equation
Modeling where the data processing is a Partial Least Square (Smart-PLS) version 3.0 program. PLS (Partial Least Square) is an alternative model of covariance-based SEM. PLS is intended for causal-predictive analysis in situations of high complexity and low theoretical support (Ghozali, 2014). The purpose of PLS is to �ind the optimal predictive linear relationship in the data. Although PLS (Partial Least Square) can also be used to con�irm the theory, it can also be used to explain whether there is a relationship between latent variables. As stated by Wold in Ghozali (2014) Partial Least Square (PLS) is a powerful analytical method. Therefore, it is not based on many assumptions, so the data does not have to be normally distributed, and the sample does not have to be large.
Inner model testing is a model development based on theoretical concepts to analyze the relationship between exogenous and endogenous variables that have been described in a conceptual framework. The purpose of the structural model test is to see the correlation between the constructs measured, which is the t-test of the partial least square itself.
Structural or inner model can be measured by looking at the R-square value of the model which shows how much in�luence between variables in the model. Then the next step is the estimation of the path coef�icient which is the estimated value for the path relationship in the structural model obtained by the bootstrapping procedure with a value that is considered signi�icant if the t-statistic value is greater than 1.96 (signi�icance level 5%).

R-Square Value
The R-Square value is a goodness-�it model test. The second test can be seen from the R-Square results for endogenous latent variables of 0.67, 0.33, and 0.19 in the structural model indicating that the model is "good", "moderate", and "weak".

Goodness Of Fit Model
Goodness of Fit the structural model in the inner model uses the predictive-relevance (Q2) value. R-square value > 0 which indicates that the model has a predictive-relevance value.

Testing (Path Coef�icient Estimation)
The estimated value for the relationship between the paths in the structural model should be signi�icant. This signi�icance value was obtained by bootstrapping procedure. Looking at the signi�icance of the hypothesis by looking at the parameter coef�icient values and the signi�icance value of t-statistics in the bootstrapping report algorithm, the t-statistical signi�icance value must be more than 1.96. (Ghozali, 2014).

RESULT AND DISCUSSION
This chapter contains the results of research. The results can be presented in the form of text, tables, images, maps and accompanied interpretation associated with the results that have been reported. The arguments and �indings are suf�iciently described in this section. After the estimated model meets the Outer Model criteria, the next step is to test the structural model (Inner Model). Inner model testing is the development of concept and theory-based models in order to analyze the relationship between exogenous and endogenous variables that have been described in a conceptual framework. The testing stages of the structural model (inner model) are carried out with the following steps:

R-Square (R²) Value
Looking at the R-square value which is a goodness of �it model test From the data above, it can be concluded that the R-Square value is 0.912 and 0.901, which means that the variability of customer satisfaction and customer loyalty can be explained by the three independent variables in the model, namely service performance of 91.2% and 90.1 and the rest is explained outside this research model.

Goodness of Fit Model
Testing the Goodness of Fit Structural model on the inner model uses predictive relevance (Q2). The Q-Square value is greater than 0 (zero) indicating that the model has predictive relevance. The R-Square value of each endogenous variable in this study can be seen in the following calculations 1: Q2 = 1 -(1 -R1) Q2 = 1 -(1 -0.901) Q2 = 1 -0.099 Q2 = 0.901 (1) The calculation results above show the predictive relevance value of 0.901> 0. It means that 90.1% of the variation in the customer loyalty variable (dependent variable) is explained by the variables used, thus the model is said to be feasible to have relevant predictive values and research models. This can be stated as having a good goodness of �it.

Hypothesis Testing Results (Estimated Path Coef�icient)
The estimated value for the path relationship in the structural model must be signi�icant. This signi�icant value can be obtained by bootstrapping procedure. Seeing the signi�icance of the hypothesis by looking at the parameter coef�icient values and the t-statistical signi�icance value in the bootstrapping report algorithm. To �ind out whether it is signi�icant or not, it can be seen from the t-table at alpha 0.05 (5%) = 1.96. Then the t-table is compared with the t-count (t-statistics). For further information, kindly please refer to Figure 2 below for the Boostrapping Test Results.
Based on the results of the PLS (Partial Least Square) analysis, this section will discuss the results of the calculations that have been carried out by the researchers. This study aims to determine the factors that in�luence online buying interest. Testing is shown through existing hypotheses so that they can �ind out how the in�luence of each variable on the other variables.

The Impact of Service Performance on Customer Satisfaction
Based on the hypothesis test in this study, the T-Statistic result was 59.851, the original sample value was 0.946, from the P value 0.000. The T-statistic value is greater than the T-table value of 1.96, the original sample value shows a positive value, and the P Values value shows less than 0.05. From these results it can be concluded that the �irst hypothesis is accepted, it could be concluded that Service Performance had a positive and signi�icant impact on customer satisfaction during the COVID-19 pandemic. The higher the Service Performance, the higher customer satisfaction. This is evidenced by research conducted by Nurjannah Daulay (2017) showing that Service Performance has a positive and signi�icant impact on customer satisfaction. In line with research conducted by Silvia Cendana Ratih Elok Wijaya (2017) shows that Service Performance has a positive and signi�icant effect on customer satisfaction.

The Impact of Service Performance on Customer Loyalty
Based on the hypothesis test in this study, the results of the T-Statistic were 3.576, the original sample value was 0.459, from the P value 0.000. The T-statistic value is greater than the T-table value of 1.96, the original sample value shows a positive value, and the P Values value shows less than 0.05. From these results it can be concluded that the second hypothesis is accepted means that Service Performance had a positive and signi�icant effect on customer loyalty during the COVID-19 pandemic, thus the higher the Service Performance, the higher the customer loyalty. This is evidenced by research conducted by Kuspriyono and Ela Nurelasari (2018) which shows that service performance has a positive and signi�icant impact on customer loyalty. In line with research conducted by Xia Liu, Hyunju Shin and Alvin C. Burns (2021), it shows that service performance has a positive and signi�icant effect on customer loyalty.  (2013) showing that satisfaction has a signi�icant positive effect on customer loyalty. In line with research conducted by Nurjannah Daulay (2017), it shows that customer satisfaction has a positive and signi�icant impact on customer loyalty.

CONCLUSION
Based on the formulation of the problem along with the data analysis and discussion presented in the previous chapter, some conclusions can be drawn as follows: 1. Service performance had a positive and signi�icant impact on customer satisfaction during the COVID-19 pandemic. This shows that service performance plays a very important role in customer satisfaction. The higher the service performance, the higher the customer satisfaction.
2. Service performance had a positive and signi�icant impact on customer loyalty during the COVID-19 pandemic. This shows that service performance plays a very important role in customer loyalty. 3. Customer Satisfaction had a positive and signi�icant impact on customer loyalty during the COVID-19 pandemic. This shows that customer satisfaction plays a very important role in customer loyalty. The higher the customer satisfaction it will increase customer loyalty.

Suggestions
For further researchers, judging from the R-Square test obtained 90.1% of the in�luence of Service Performance and Customer Satisfaction on Bank BTN customer loyalty, suggestions that can be considered in further research are that further researchers can expand the research area with different characteristics of respondents so that the research sample is more accurate, and can examine other variables that are not examined in this study. And lastly, researchers must be careful in looking at the problem and observant in determining the variables to be studied. Furthermore, suggestions for Bank BTN based on this research are that bank BTN should maintain the performance by asking more feedbacks from customers to improve the service quality, evaluating the complaints from customers, and creating new standards based on the customers' needs to improve the customer loyalty and customer satisfaction.