THE IMPACT OF EDC'S MARKETING, SERVICE, AND INFRASTRUCTURE STRATEGIES ON THE GROWTH OF SAVINGS DEPOSITS AT BANK RAKYAT INDONESIA SURABAYA

ABSTRACT


Introduction
The banking industry has a crucial role in obtaining capital and carrying out financial transactions (Atambo, Munene, & Mayogi, 2013).In carrying out its operations, it strives to gain a competitive advantage by increasing income through interest on loans and non-interest income (fee-based income) such as transaction service fees.In addition, there are efforts to increase the number of deposits, especially low-cost funds (savings) in a way that is more dominant to the number of third-party funds, to reduce the cost of funds and is expected to generate an increase in the value of net interest margin (NIM) despite the current tight bank liquidity (Setiyono, Maramis, & Setianto, 2019).Looking at the ideal ratio between savings and deposits for banking business is 60%:40%, but at BRI Surabaya Pahlawan Branch, the ratio of savings and deposits is currently 51%:49%.Therefore, the BRI Surabaya Pahlawan Branch must have the right special strategy to accelerate the increase in the number of deposits with a focus on savings (Yoiz Shofwa, 2015).
Several strategies can be built and implemented by BRI Surabaya Pahlawan Branch to increase the number of deposits, especially savings, including marketing strategies, service strategies, and strategies in managing the bank's business supporting infrastructure (Pepper, Gore, & Crossman, 2013).According to (Febriyan & Sulistyowati, 2014), marketing strategy is a discipline that involves selecting a target market to get, retain, and increase the number of consumers.This is done through the process of creating, providing, and communicating value to customers to generate greater customer value (Didin Fatihudin, Wikanta, Hammadi Fauzi, & Firmansyah, 2023).
One example of a marketing approach used as a technology development in the banking industry is electronic data capture (EDC) (Ulum, 2016).The tool can be used as a medium in payment transactions using debit or credit cards (Prastyawan, 2022).According to Mr. Sunarso, Director of PT Bank Rakyat Indonesia, the use of EDC provides benefits for BRI in terms of increasing third-party funds, especially savings, and earning income from transaction fees charged for each transaction swiped through the EDC machine (Pahlawan, 2012).Thus, BRI must be able to carry out marketing activities and provide the best service, as well as optimize the use of EDC devices with adequate infrastructure support.With this background, the author tries to find out whether the marketing strategy, service strategy, and infrastructure of the EDC machine influence significant deposit growth, especially the number of savings deposits at PTi Banki Rakyati Indonesiai Cabangi Surabaya Pahlawani (Susan, Gakure, Kiraithe, & Waititu, 2012).
The purpose of this study is to evaluate the impact of marketing strategies, service strategies, and Electronic Data Capture (EDC) machine infrastructure on the growth of savings deposits at the Surabaya Pahlawan Branch of PT Bank Rakyat Indonesia.To identify these problems, researchers use a descriptive quantitative research approach.Data collection methods used include interviews, observations, questionnaires, and documentation.

Research Methods
The type of research used in this study is the quantitative research method.According to (Klassen, Creswell, Plano Clark, Smith, & Meissner, 2012), in quantitative research, researchers must be able to explain how variables can affect other variables.This study used a multiple linear regression analysis technique.This research is located in various stores or business places in the area around the PT Bank Rakyat Indonesia Surabaya Pahlawan branch that uses electronic data capture (EDC) tools.The research period will be from January to June 2023.The object of this research is EDC merchant PT Bank Rakyat Indonesia Surabaya Pahlawan branch.The subjects of the study were business actors who became EDC merchant customers and consumers of EDC merchant users of PT Bank Rakyat Indonesia Surabaya Pahlawan branch.To understand the condition of the company's program, this quantitative research will collect data through the use of questionnaires and subjective opinions from EDC BRI customers and EDC BRI consumers.This is to the characteristics and definitions of quantitative research that focus on objective aspects and data measurement.

Results and Discussion
The research was conducted to determine and analyze the effect of Marketing Strategy (X1), Service Strategy (X2), and Electronic Data Capture Infrastructure (X3) on Savings Deposit Growth (Y).Data on respondents' characteristics based on gender, last education, and length of work can be seen in the following table.The table of respondent characteristics above shows that the number of male respondents in the study consisted of 61 people (61%), while the number of female respondents was 39 people (39%).Based on these numbers, it can be concluded that the respondents who dominate the study are respondents with male gender.In terms of the latest education, as many as 12 people (12%) are high school graduates/equivalent.While respondents with Diploma III background as many as 3 people (3%).While respondents who graduated from Strata I (S1) and Strata II (S2) each consisted of 69 people (69%) and 16 people (16%).Based on this explanation, it is known that the most responses in the study were those with the last educational background of Strata I (S1).Based on the descriptive analysis above, it is known that the average value of the Marketing Strategy variable (X1) is 4.106 with the lowest value being 2 and the highest being 5.The standard deviation is 0.704.The average value of the Service Strategy (X2) is 3.767 with a value of as low as 1, as high as 5, and a standard deviation of 0.975.The Electronic Data Capture (X3) Infrastructure variable has an average value of 4.199 with the lowest value being 1 and the highest being 5.The standard deviation is 0.634.In the variable Growth of Savings Deposits (Y), the average value obtained is 4.219 with the lowest value of 2 and the highest of 5, while the standard deviation is 0.758.
Validity tests are carried out to determine the validity of research instruments.The validity test technique used is Product Moment Pearson Correlation.The number of research respondents was 100 people so the r value of the table with a significant level of 5% was 0.197.Here are the results of the validity test conducted.The reliability test aims to determine the consistency of research measuring instruments.The questionnaire was considered reliable if Cronbach's Alpha score was> 0.60.The reliability test results in the table above show that Cronbach's Alpha value of the Marketing Strategy variable (X1) is 0.706 > 0.60, the Service Strategy variable (X2) is 0.778 > 0.60, Electronic Data Capture Infrastructure (X3) is 0.870 > 0.60 and Savings Deposit Growth (Y) is 0.736 > 0.06.Given that the entire questionnaire has a Cronbach's Alpha value greater than 0.60, it can be concluded that the questionnaire used in the study is consistent or reliable.
The normality test was carried out to determine the distribution of research data.Good data is data that is normally distributed.The normality test of this study used the Kolmogorov-Smirnov Test.The normality test results can be seen in the following table.

N
Significance Information 100 0,057 Data Normal In the normality test results in Table 4.5 above, the significant value of Asymp.Sig (2-tailed) is 0.057 > 0.05.Based on these values, it can be concluded that the data used in the study are normally distributed.
The multicollinearity test is an assumption test that aims to determine the correlation between variables.The requirement for the multicollinearity test is that the tolerance value in all independent variables must be greater than 0.10 and the value of the Variance Inflation Factor is less than 10.Based on the test in Table 4.6 of the Collinearity Statistics section above, it is known that the Tolerance value of the entire variable is > 0.10 with a Variance Inflation Factor < 10.00.Given the Tolerance value of both variables > 0.10 and the value of the Variance Inflation Factor < 10.00, it can be concluded that there are no symptoms of multicollinearity in the regression model.
The heteroscedasticity test is performed by looking at the Scatterplot image pattern.The test results can be seen in the following figure.

Figure 1 Heteroscedasticity Test Results
Figure 1 shows that the dots spread randomly above and below the number 0. Given that the data is scattered randomly and without forming a special pattern, it can be concluded that there are no symptoms of heteroscedasticity in the research data.

Figure 2 Regression Analysis Results
The Impact Of Edc's Marketing, Service, And Infrastructure Strategies On The Growth Of Savings Deposits At Bank Rakyat Indonesia Surabaya Pahlawan Branch In the results of multiple linear regression analysis between independent variables and dependent variables, the regression equation can be arranged as follows: Y = 8.951 + 0.437 X1 + 0.142 X2 + 0.268 X3 (1) Based on the regression equation, it can be concluded that the constant value of 8.951 indicates the value of the variable Growth of Savings Deposits (Y) without being influenced by the independent variable.The value of the regression coefficient (β1) of 0.437 shows the influence of the Marketing Strategy variable (X1) on the Growth of Savings Deposits (Y).If the value of Marketing Strategy (X1) is increased by one unit, it will be followed by an increase in Savings Deposit Growth (Y) by the regression coefficient.The regression coefficient (β2) value of 0.142 shows the effect of Service Strategy (X2) on Savings Deposit Growth (Y).If the Service Strategy value (X2) is increased by one unit, it will be followed by an increase in Savings Deposit Growth (Y) by the regression coefficient.The regression coefficient (β3) value of 0.268 shows the effect of the Electronic Data Capture Infrastructure (X3) variable on Savings Deposit Growth (Y).If the value of Electronic Data Capture Infrastructure ( X3) is increased by one unit, it will be followed by an increase in Savings Deposit Growth (Y) by the regression coefficient.
Based on the test results in Figure 2 the significance value of the variable X1 is 0.000, X2 is 0.016, and X3 is 0.031.The significance values of the variables X1, X2, and X3 are known to be smaller or < 0.05.Based on these results, it can be concluded that the variables Marketing Strategy (X1), Service Strategy (X2), and Electronic Data Capture Infrastructure (X3) partially have a significant effect on the variable Growth of Savings Deposits (Y).These results also prove that hypotheses 1, 2, and 3 proposed in the study are accepted.

Figure 3 F Test Results
Figure 3 shows that the significance value obtained is 0.000 or < 0.05.Based on the results of the F test, it can be concluded that the variables Marketing Strategy (X1), Service Strategy (X2), and Electronic Data Capture Infrastructure (X3) simultaneously have a significant effect on the Growth of Savings Deposits (Y).

Figure 4 Results of Coefficient Determination
Based on the coefficient of determination test shown in Figure 4.5 above, it is known that the Adjusted R Square value is 0.595.This value means that the variables Marketing Strategy (X1), Service Strategy (X2), and Electronic Data Capture Infrastructure (X3) have an effect or can predict the Growth of Savings Deposits (Y) by 59.5%, while 40.5% is influenced by other variables that are not studied.
These findings imply that financial institutions or organizations looking to increase their savings base should focus on developing and implementing effective marketing and service strategies while also investing in electronic data capture infrastructure.As such, they have the potential to realize substantial growth in their savings base, which could lead to increased profitability and sustainability in the long run.However, it is important to note that these findings are based on specific studies, and other factors, such as economic conditions, regulatory environment, and competition, can also influence savings growth in different contexts.Therefore, financial institutions or organizations must consider their unique circumstances and adjust their strategies accordingly.This may involve conducting their research or analysis to identify the most effective marketing and service strategies for their target audience, as well as investing in a suitable electronic data capture infrastructure that meets their specific needs and requirements.In addition, institutions must constantly monitor the growth rate of their savings and adjust their strategies.

Conclusion
The study concludes that savings growth is a crucial factor for financial institutions, and marketing strategies, service strategies, and investments in Electronic Data Capture (EDC) infrastructure have a significant impact on this growth.Effective marketing strategies, through targeted advertising, branding, and promotional programs, can increase potential customer awareness and drive customer acquisition and retention.Service strategies that focus on customer satisfaction, including online banking, 24/7 customer support, and personalized financial advice, also help build customer loyalty and promote savings growth.Investment in EDC infrastructure brings efficiencies in account opening, reduces errors, and speeds up transactions, thereby improving customer experience and reducing operational costs.Overall, the study provides strong evidence that combining the right marketing strategies, services that meet customer needs, and EDC technology can drive better savings growth for financial institutions

Table 3 Validity Test Results
The questionnaire is valid if the calculated r value obtained is greater than the table r (0.197).Based on the test results in Table4.3above, it is known that the calculated rThe Impact Of Edc's Marketing, Service, And Infrastructure Strategies On The Growth Of Savings Deposits At Bank Rakyat Indonesia Surabaya Pahlawan Branch value of the entire questionnaire item is greater than the table r value.By the basic provisions of the validity test, namely r count > r table, it can be concluded that the questionnaire items used in the study have passed the validity test and are considered suitable for use.