This study was aimed at determining the factors that could influence a person’s decision to use mobile banking. In this study, perceived usefulness, perceived ease of use, and perceived credibility were considered exogenous variables, and social factors as mediators. This research used quantitative methods. The population in this study were Indonesian Sharia Bank customers who used BSI mobile banking services in the Jakarta, Bogor, Depok, Tangerang and Bekasi areas. A sample of 200 people was obtained using the purposive sampling method. The analysis technique used was the inner model, outer model, and hypothesis testing using SmartPLS 3.2.9. The results obtained in this study showed that perceived usefulness had a significant effect on decisions to use mobile banking, perceived ease of use had no significant effect, and perceived credibility had a significant effect. In addition, this study has also shown that social factors did not succeed in mediating other variables in the decision to use mobile banking.
independently. Needless to say, having good service quality will encourage customers to continue to trust the digitalized banking companies (Mawarni, 2021). One of the digital services currently offered by banks is mobile banking, which is an innovation resulting from optimizing information technology. Mobile banking allows one to connect with the service provider, the bank with the mobile banking business management system from one’s mobile phone and one can access the most efficient banking transactions by independently managing one’s bank account (Ningrum et al., 2021). In addition, the mobile banking users benefit the most as the new transactions are time saving and this has become a new paradigm and a new strategy for banking in facing new challenges in the digital era. This mobile banking service minimizes the costs incurred by both the bank and the customer, such as the cost of printing a prospective customer form to open an account or make transactions. Mobile banking users will get other benefits, such as information related to their banking transactions that will be received quickly and effectively, customers do not waste time conducting numerous transactions. There are some banks in the world that offer technology with the help of banks such as Bank Syariah Indonesia (BSI). Bank Syariah Indonesia is the outcome from the merger of Islamic State-owned banks in Indonesia. As of July 2021, BSI mobile service users have reached 2.5 million users, with total transactions from January to June 2021 amounting to 41.99 trillion rupiah. If you are interested in using mobile banking, please contact BSI Mobile for a digital transaction with 83.56 people using this feature (Pasaribu, 2021). However, when compared to customers who have an account with Bank Syariah Indonesia (BSI), this figure is still very large. The number of accounts at the BSI is calculated to range from 14.5 million to 15.5 million, after the completion of the migration carried out (Walfajri & Perwitasari, 2021). Thus, it can be seen that there is a gap between the number of customers who have accounts and the number of users of the BSI mobile service, which is thought to be caused by other aspects. The credibility aspect is also one of the benefits that will be received by mobile banking users. In the aspect of credibility, there are two factors important for consideration, namely the security and privacy of customer data for mobile banking users (Putri et al., 2020). This aspect is very important because it is something that customers need to pay attention to before deciding to use mobile banking services. Credibility, which includes security, is overshadowed by recent cases related to fraud and data breaches that have occurred to customers who use mobile banking. Banks have an important role to play in maintaining the security of customer data of mobile banking users. In the context of mobile banking, a lack of credibility will cause customer concerns that their personal data and funds may be sent to other parties without their knowledge (Gupta et al., 2019). In addition, social factors lead to the assumption that a person’s attitude in accepting new technology can be influenced by the social environment, which is one important aspect that can critically influence a consumer’s decision. Social influence can be interpreted as the pressure that exists in one’s environment to dictate whether or not to do something in question (Deameta, 2019). Another factor that can influence customer decision to use mobile banking is the customer’s understanding of the use of the technology and its applications. The use of mobile banking is also an indication of one’s status in society (Adzima & Ariyanti, 2018). Some studies have used similar variables as those in the present study. According to a research conducted by Dewi et al. (2018) the variables that have been found to influence customers to use mobile banking were convenience, efficiency and security (Dewi et al., 2018). However, the research conducted by Latif pointed out that the convenience aspect is not part of the reasons for customer decisions to use mobile banking services (Latif, 2017). Another research conducted by Adiwijaya (2018) showed that convenience and the success rate offered were able to increase customer interest in making transactions using mobile banking (Adiwijaya, 2018). Styarini and Riptiono (2020) emphasied in their research that perceived usefulness was a very important aspect in one’s decision to use mobile banking. They also pointed out that one of the reasons that could hinder customers from using mobile banking was the perceived risk that would be generated (Styarini & Riptiono, 2020). In addition, the study by Rahayu (2016) found that perceptions of usability and credibility were factors important in attracting interest in using mobile banking. Meanwhile, the perception of convenience was felt to have no effect because the service often experienced system errors (Rahayu, 2016). Research conducted by Hadi and Novi (2015) revealed that variables such as accessibility, security and risk variables would influence customer decisions. However, the ease of use of services had not been included in the aspects assessed by customers (Hadi & Novi, 2015). In light of the foregoing discussions of findings from previous research, it is clear that there are differences in the views regarding the influence of variables on the use of mobile banking services. For this reason, the researcher intends to further examine matters relating to the factors determining decision making to use mobile banking services. In this study, the focus of the analysis was on the following variables: perceived usefulness, the perceived ease of use, perceived credibility and other social factors. LITERATURE REVIEW Mobile Banking Mobile banking is one of the digital services offered by financial institutions (Tam & Oliveira, 2017). Mobile banking is a digital service that offers convenience in transactions, such as transfers between accounts, checking balances and other banking transactions. However, at this time the convenience provided in mobile banking services is not only about banking, but also extends to e-commerce such as e-wallet top up, paying for electricity and water, and even paying zakat can be done through these services. With the benefits obtained from this service, it makes it easier for customers to transact, and being less time consuming as compared to conducting conventional transactions (Fadlan & Dewantara, 2018). Iriani (2019) stated that mobile banking has been defined as a service that provides convenience and speed of access, making it easier and faster to obtain information about banking and financial transactions (Iriani, 2019). Service options available in mobile banking include accessing balance information, interbank transfer services, electricity and water payments, insurance bill payments, purchase of credit and tickets, e-wallet top ups and even zakat payments, as well as several other service options (Ningrum et al., 2021). With these various services, it can be said that the services offered are not confined only to the banking sector, but also in other fields. If so, these advantages not only make it easier for customers to carry out various types of transactions, but also benefits banks by helping to increase customer satisfaction, improve service operations and cost effectiveness (Tam & Oliveira, 2017).
Purchase decisions have been defined as a method of solving problems beginning with identifying problems, seeking information, evaluating a number of alternatives, making purchase decisions and ending with post-purchase attitudes (Kotler & Keller, 2016). Decision making by consumers is defined as the process of solving a problem and composing a collaboration between knowledge and evaluation of two or more available alternatives (Peter & Olson, 2010). With the action of decision making, consumers have targets and behaviors that need to be achieved by themselves in order to receive satisfaction from the chosen action. In decision making, consumers play an important role in solving the problems they have. Relationships that occur from decision-making actions are included in the category of reciprocal relationships that are intertwined around environmental factors and the resulting behavior (Firmansyah, 2018). Several indicators influence one in using a product or service. According to Mongi (2014), the need to use a product or service is the main reason one makes a purchase or uses it. The need for a product or service makes a person know the actions that need to be taken to meet those needs. In today’s all-digital environment, the need for practical and efficient services often increases among the people. The service in question is a service that provides convenience in carrying out activities. One aspect that a person considers in deciding to buy is the quality of a product or service. If the product or service to be used has good quality, then one will not hesitate in deciding to buy. For that quality will be a priority when one decides to buy a product or use a service. A person’s decision to buy or use a product or service affects the behavior that will be generated afterward. If someone is satisfied with the quality of the product or service that will be used, it becomes a consideration in the future to reuse the product or service. On the other hand, if the product or service is not able to fulfill a person’s sense of satisfaction, there is the likelihood that there is no re-use of the product or service. Technology Acceptance Model According to Davis (1989), the theory in the Technology Acceptance Model (TAM) contains a basic theory that explains a person’s behavior in accepting the novelty of information. The Technology Acceptance
Model or commonly abbreviated as TAM, is a development of psychological theory and has several foundations, namely attitudes, beliefs, desires and user behavior (user behavior relationship). The TAM mentions two factors that make a person accept the novelty of information systems, namely the theory of perceived ease of use and the theory of perceived usefulness. The model is a development of the Theory of Reasoned Action which aims to determine the influence of external variables such as beliefs, attitudes and intentions of a person to use a new technological system. The difference between TAM theory and the previous theories is that it shows more specific characteristics related to technology acceptance (Wu et al., 2011). According to Wu and Song (2021), although the TAM can well document and predict user attitudes in accepting technology, there are shortcomings in its theory. For example, most significantly, it cannot explain all the driving factors that influence user attitudes because the model used is very common and very simple (Wu & Song, 2021). Perceived Usefulness Perceived usefulness has been defined as a view related to the use of a new technology that is believed to provide benefits to its users (Davis, 1989). Similarly, Thompson et al. (1991) have also stated that the advantages of an increasingly developing information technology are clearly the expectations desired by its users in carrying out the desired activities. Thompson and Howell also explained the reasons individuals use information technology, namely being very much aware of the positive impacts from the use of the technology (Thompson et al., 1991). Basically, one will use something if one knows the benefits of the technology offered. It is hoped that the advent of the latest information technology can bring benefits to everyone who uses it (Ernawati & Noersanti, 2020). Perceived Ease of Use Perceived ease of use is defined as a feeling of trust in the technology, that it is not troublesome to understand and easy to use. Perceived ease of use is included in the determinants of individuals accepting an information technology (Jogiyanto, 2007). Assessment of the ease of use of technology is recognized if the technology is easy to understand for new users, therefore they are very likely to adopt the said technology (Kristianti & Pambudi, 2017). Davis (1989) states that there are five indicators which are related to the perceived ease of use of technology. First, mobile banking is not difficult to understand for individuals who are using the service for the first time. Offering this convenience to new users, it allows the user to immediately understand the features available in the service. Second, mobile banking is easy for users to operate. The convenience offered is not only in terms of understanding the existing features, but also because it offers ease of operation (Davis, 1989). Furthermore, mobile banking can be operated according to the wishes of the user. This means that mobile banking always runs the system easily, and according to what the user wants. The advantages offered are clear and it is clear that users do not need much effort to carry out their banking activities. This can be seen because it does not take much time and there are no queues to make transactions because it is only done through smartphones. Lastly, the use of mobile banking is flexible. In any mobile banking service on offer, flexibility is an inherent feature, namely the ease of using the service anywhere and anytime without wasting one’s precious time. Perceived Credibility Perceived credibility is one of the benefits that will be received by mobile banking users. The credibility component put forward by Wang et al. (2003), is that one believes that there is security of transactions and personal data. One can carry out all banking activities and the online banking system is well maintained. These factors will certainly influence the acceptance of the information technology used. The perception of credibility held by the public regarding systems that help complete financial transactions safely and with guaranteed confidentiality will greatly affect how customers voluntarily accept mobile banking services. Thus the perception of credibility is predicted to have the ability to explain customers’ intentions to use mobile banking (Hanudin et al., 2007). In conclusion, credibility is defined by users’ trust in companies that have been able to provide products/services and meet consumer needs easily by optimizing technological novelty.
Social factors are defined as the influence from a person or group of people on other people and the individual is then willing to imitate their habits (Kotler & Keller, 2016). Social factors come from external parties which include the family, social groups and the role and social status of other people who encourage them to take action on purchasing decisions. Kotler and Keller (2016) have stated that there are three indicators of social factors as follows. In accordance with what was stated by Kotler and Keller (2016) that there were several aspects that needed to be considered, namely family, social group, and status. Regarding family, it can be said that the closest environment a person begins with is the family environment. The family contains individuals who can influence other members in the group. So it can be said that family members have a strong influence in impacting consumer behavior. In addition, families are included as the main targets by marketers and this has been studied in depth. It can be exemplified that marketers are interested in attracting family members, both husband and wife, and their children to buy a product or service being offered. Then there is one’s social group which has a direct influence on members who are part of the group. There are two categories of groups described by Kotler and Keller (2016), namely primary/regular groups and secondary/irregular groups. The primary group contains individuals who interact quite a lot, but can be seen as informal, for example, such as family, neighbors, friends and schoolmates or coworkers. It is different from the secondary group which contains individuals who can interact formally, such as recitation groups, community groups, certain organizations, and so on. In each secondary group there are individuals who serve as leaders in giving opinions and influences. This individual is not simply chosen without any criteria, but the selection can be made because of the personality, skills, knowledge and other characteristics of the individual. Finally, roles and status also play an important role in social factors. In a collection of individuals, for example in families, organizations and communities, there will be someone who has an important role in the group. The role and status can indicate the position held by the person. So it takes someone who can reflect the group to the general public through the required role and status. Therefore, group members often decide to buy products or services that can help reflect their group in society. METHODOLOGY Data The type of data used in this research was the quantitative data generated from the online questionnaires that were distributed. Quantitative data is defined as numerical data which can be in the form of ordinal, ratio, or interval data. The ordinal numerical data from this study was obtained from a Likert scale used in the study. Sources of data in this study came from primary and secondary data sources. The primary data was from the responses obtained from online questionnaires to prospective respondents who were targeted. The secondary data used in this research were sourced from scientific articles or companies or parties related to this research. The method of collecting data in this study was to use a questionnaire. Gathering information is necessary for the research to obtain valid and actual items, based on facts. The questionnaire is a research instrument aimed at collecting data from respondents using a prepared set of questions. In this study, the sample used was the 200 respondents who were using the BSI mobile services. The present research used descriptive and quantitative methods in its analysis. The descriptive method was used to explain the data obtained from online questionnaires that have been filled out by respondents. The quantitative method used was the Partial Least Square (PLS) method, with the help of the SmartPLS 3.2.9 analytical tool. The Partial Least Square is included in the Structural Equation Model (SEM) method. SEM is often used in research in the humanities and social sciences. This is because the SEM method can explain path analysis on the latent variables used. In addition, the SEM method has high flexibility compared to other analytical methods. Model Development This study used the following exogenous variables, namely perceived usefulness (X1), perceived ease of use (X2), and perceived credibility (X3) and these variable will be tested for its influence on the endogenous variables affecting the decision to use mobile banking services (Y). In addition, in this study there was a mediating variable, namely the social factors (M) which would play a role in determining the effect of mediating variables on exogenous variables. The Influence of Perceived Usefulness on Decisions to use Mobile Banking Services Perceived usefulness is defined as the view that the use of a new technology is believed to provide benefits to its users (Davis, 1989). Perception of usability is the main factor for consideration in adopting the latest information technology. A study conducted by Mohd Thas Thaker et al (2019) stated that perceived usefulness has a significant influence on the use of mobile banking. Based on this, the following hypotheses have been proposed. H01 = Perceived usefulness does not significantly affect the decision to use mobile banking services Ha1 = Perceived usefulness significantly influences the decision to use mobile banking services The Influence of Perceived Ease of use on Decisions to use Mobile Banking Services Perception of ease of use is included in the determinants of individuals adopting information technology (Jogiyanto, 2007). If one has a sense of trust in information technology, then there are no qualms in carrying out a financial transaction through a payment system that has been modified so that it is easy to operate. A study conducted by Alalwan et al. (2016) stated that the perception of ease of use has a significant influence on the use of mobile banking. Based on this, the following hypotheses have been proposed. H02 = Perceived ease of use does not significantly affect the decision to use mobile banking services Ha2 = Perceived ease of use significantly influences the decision to use mobile banking services The Influence of Perceived Credibility on Decisions to use Mobile Banking Services The perception of credibility put forward by Wang et al. (2003) is that one tends to believe that when the security of transactions and personal data are well maintained, it can influence one to accept the information technology used. Perceived credibility is an assessment of security and privacy issues when discussing the credibility of mobile banking services. Studies related to the acceptance of technology offered by banks have been noted by many other researchers. A study conducted by Wicaksono et al. (2021) stated that the perception of credibility has a significant influence on the use of mobile banking. Based on this, the following hypotheses have been proposed. H03 = Perceived credibility does not significantly influence the decision to use mobile banking services Ha3 = Perceived credibility significantly influences the decision to use mobile banking services The Influence of Social Factors on Decisions to Use Mobile Banking Services Social factors are defined as the influence exerted by a person or group of people on others to want to imitate their habits. Social factors come from external parties which include family, social groups and the role and social status of others that encourage them to take action on purchasing decisions (Kotler & Keller, 2016). A study conducted by Gupta et al. (2019) stated that social factors have a significant influence on the use of mobile banking. Based on this, the following hypothesis have been proposed. H04 = Social factors do not significantly influence the decision to use mobile banking services Ha4 = Social factors significantly influence the decision to use mobile banking services The Influence of Social Factors in the Mediation of Perceived Usefulness, Perceived Ease of Use and Perceived Credibility in Decisions to Use Mobile Banking Services In light of the foregoing discussions, the present study has also proposed the following hypotheses: H05 = Social factors mediate perceived usefulness, perceived ease of use and perceived credibility on decisions to use mobile banking services Ha5 = Social factors do not mediate perceived usefulness, perceived ease of use and perceived credibility on the decision to use mobile banking services
The present research uses descriptive and quantitative methods in carrying out its analyses. The descriptive method was used to explain the data obtained from online questionnaires that have been filled out by respondents. The quantitative method used was the Partial Least Square (PLS) method, which has recourse to the SmartPLS 3.2.9 analytical tool. Partial Least Square is included in the Structural Equaition Model (SEM) method. The Partial Least Square (PLS) analysis method is one of the methods incorporated in SEM. When compared to the other SEM methods, the PLS is stronger because there are not many underlying assumptions. Not only that, the data used in the PLS test of the sample tested does not have to be on a large scale and the data does not have to be normally distributed. The PLSSEM analysis consists of two sub-models, namely the measurement model (measurement model) or commonly called the outer model and the structural model (structural model) or the inner model. RESULTS Data Respondents Based on Table 1, it can be seen that the respondents based on gender are divided into two categories, namely men and women. Of the 200 respondents, female respondents dominated, namely there were 129 respondents or a percentage of 64.5 percent, and the rest were male, there were 71 respondents with a percentage of 35.5 percent. It is therefore, clear from the results that women use mobile banking more in transactions.
| Gender | Frequency | Percentage |
|---|---|---|
| Male | 71 | 35.5% |
| Female | 129 | 64.5% |
| Total | 200 | 100.0% |
Based on Table 2, it can be seen that the respondents based on gender were divided into four categories, namely 12 to 23 years, 24 to 39 years, 40 to 55 years, and 56 to 74 years. Of the 200 respondents, respondents aged 12-23 years (generation z) dominated as there were 122 respondents or a percentage of 61 percent, this was followed by 45 respondents aged 24-39 years, constituting a percentage of 22.5 percent, 29 respondents aged 40-55 years giving a percentage of 14.5 percent, and the remaining 4 respondents were aged 56 – 74, or 2 percent of the total respondents. It is clear that the data showed the dominance of respondents in the age range of 12 – 23 years. It is people in this age group who are included in the category Generation Z, and they are more sensitive to technological developments as that they are more willing adopt mobile banking services.
| Age | Frequency | Percentage |
|---|---|---|
| 12 - 23 years (Generation Z) | 122 | 61.0% |
| 24 - 39 years (Millenial Generation) | 45 | 22.5% |
| 40 - 55 years (Generation X) | 29 | 14.5% |
| 56 - 74 years (Baby Boomer Generation) | 4 | 2.0% |
| Total | 200 | 100.0% |
Percentage 61.0% 22.5% 14.5% 2.0% 100.0%
Convergent validity is a test to determine the value of the construct of each latent variable indicator. Generally, the construct value can be said to be ideal if it meets the criteria above 0.70, but actually the construct value range from 0.40 to 0.70 is acceptable. Based on the test carried out, there was one indicator that produced a construct value of less than 0.40 so it had to be removed. In order to get good results it was necessary to do some gradual removal. As a result, the PU1, PU6, PEOU4 and UD2 indicators were abolished in order to get results that were in accordance with the provisions. Discriminant Validity Discriminant validity aims to find out every question on the indicator does not confuse the answers given by the sample. Discriminant validity can be seen from the cross loading and the Average Variance Extracted (AVE) value.
| Perceived Perceived | Perceived | |
|---|---|---|
| Social Factor Use Decision | ||
| Usefulness Ease of Use Credibility | ||
| PU2 0.666 | ||
| PU3 0.795 | ||
| PU4 0.766 | ||
| PU5 0.680 | ||
| PU7 0.667 | ||
| PU8 0.695 | ||
| PEOU1 | 0.734 | |
| PEOU2 | 0.791 | |
| PEOU3 | 0.738 | |
| PEOU5 | 0.708 | |
| PEOU6 | 0.716 | |
| PEOU7 | 0.641 | |
| PC1 | 0.726 | |
| PC2 | 0.730 | |
| PC3 | 0.799 | |
| PC4 | 0.799 | |
| PC5 | 0.753 | |
| PC6 | 0.742 | |
| SF1 | 0.756 | |
| SF2 | 0.860 | |
| SF3 | 0.816 | |
| SF4 | 0.879 | |
| SF5 | 0.808 | |
| UD1 | 0.621 | |
| UD3 | 0.683 | |
| UD4 | 0.789 | |
| UD5 | 0.815 | |
| UD6 | 0.756 | |
| UD7 | 0.680 | |
PC1
PC2
PC3
PC4
PC5
PC6
SF1
SF2
SF3
SF4
SF5
UD1
UD3
UD4
UD5
UD6
UD7
| Average Variance Extracted (AVE) | Description | ||
|---|---|---|---|
| Perceived Usefulness | 0.509 | Valid | |
| Perceived Ease of Use | 0.522 | Valid | |
| Perceived Credibility | 0.575 | Valid | |
| Social Factor | 0.681 | Valid | |
| Usage Decision | 0.529 Based on the results of the processing of the data above, the results of the Average Variance Extracted (AVE) value were found to be above 0.50; it can then be concluded that the variables Perceived Usefulness, Perceived Ease of Use, Perceived Credibility, Social Factors and | Valid | |
| Usage Decisions had values above | 0.50, which means that all the | ||
| variable data are valid. | |||
| Reliability | |||
Based on the results of the processing of the data above, the results of the Average Variance Extracted (AVE) value were found to be above 0.50; it can then be concluded that the variables Perceived Usefulness, Perceived Ease of Use, Perceived Credibility, Social Factors and Usage Decisions had values above 0.50, which means that all the variable data are valid. Reliability
| Composite Reliability | Description | |
|---|---|---|
| Perceived Usefulness | 0.861 | Reliable |
| Perceived Ease of Use | 0.867 | Reliable |
| Perceived Credibility | 0.890 | Reliable |
| Social Factor | 0.914 | Reliable |
| Usage Decision | 0.870 | Reliable |
In Table 5 above, it can be seen that the Composite Reliability value for all variables was more than 0.70, which shows that all the variables in this test have met the requirements. From this value, it can be concluded that the Composite Reliability value can be said to be good for each construct. R-Square (R2) The R-square test aims to see the ability of a model to explain a dependent variable. The R-square test in this study is as shown in
| R-Square on Endogenous Variable |
| R-Square |
| 0.515 |
Table 6 shows the value of R2 on the endogenous and mediating variables tested in this study. Based on the R2 value shown in Table 6 above, the decision to use variable shows good results with a value of 0.515, or it can be concluded that the exogenous variables, namely perceived usefulness, perceived ease of use, perceived credibility are able to explain the use decision variable by 51.5 percent and the rest is explained by other factors which are outside the scope of this research. F-Square (F2) Measurement of F-square or effect size aims to assess the relative impact of an exogenous variable on endogenous variables. The F-square test in this study is as shown in Table 7.
| Perceived |
| Usefulness |
| PU |
| PEOU |
| PC |
| SF |
| UD |
| Perceived of |
| Ease of Use |
Usage Decision 0.200 0.041
The conclusion of the F-Square test results in this study can be seen in Table 7 above. It shows that the effect size of the perceived ease of use variable on social factors and the effect size of the perceived credibility variable on the decision to use mobile banking services were included in the low effect category with values of 0.026 and 0.041, respectively. Hypothesis Test Hypothesis testing is used to test the truth of a statement. To make decisions from hypothesis testing, it can be seen from the t-statistic and p-value.
| Original | Sample | Standard | |||
|---|---|---|---|---|---|
| T-table | T- Statistics | P-Values | |||
| Sample | Mean | Deviation | |||
| Perceived Usefulness | |||||
| 0.469 | 0.468 | 0.079 | 1.97 | 5.959 | 0.000 |
| - Usage Decision | |||||
| Perceived Ease of | |||||
| 0.117 | 0.117 | 0.085 | 1.97 | 1.374 | 0.170 |
| Use - Usage Decision | |||||
| Perceived Credibility | |||||
| 0.194 | 0.204 | 0.081 | 1.97 | 2.389 | 0.017 |
| - Usage Decision | |||||
| Social Factors - | |||||
| 0.060 | 0.052 | 0.061 | 1.97 | 0.972 | 0.331 |
| Usage Decision | |||||
The results of the hypothesis testing of the perceived usefulness variable showed a positive and significant effect. The coefficient value on the decision to use mobile banking services was 0.469. Thus, it can be concluded that H1 in this study, that the perceived usefulness variable has a positive and significant effect on decisions to use mobile banking services can be accepted. Meanwhile, the perceived ease of use variable on the decision to use mobile banking services has a path coefficient value of 0.117. The t-statistic value <t-table with a comparison of 1.374 <1.97, at the significance level the p-value (0.170)> 0.05 which did not meet the significance criteria. Thus, it can be concluded that H2 in this study, that the perceived ease of use variable has a positive but not significant effect on decisions to use mobile banking services should be rejected. The test results indicate that the perceived credibility variable on the decision to use mobile banking services has a positive and significant relationship, based on the criteria that have been met. In the test conducted, the perceived credibility has a coefficient value of 0.194. The significance value obtained was 0.017 <0.05, which has met the significance criteria. Thus, it can be concluded that H3 in this study, that the perceived credibility variable has a positive but not significant effect on decisions to use mobile banking services should be accepted. Mediation Test The test results show that social factors have no effect whatsoever on the relationship between perceived usefulness, perceived convenience and perceived credibility on the decision to use BSI mobile services. Thus, it can be said that the last hypothesis in this study, that social factors could not mediate perceived usefulness, perceived ease of use and perceived credibility in making decisions about using mobile services, was rejected. This is because the majority of the BSI mobile users in Jabodetabek did not decide to use the BSI mobile services due to the recommendations from friends, family, relatives and others. People decide to use the BSI mobile services due to their awareness of the need for these services.
| Original | Sample | Standard | |||||
|---|---|---|---|---|---|---|---|
| T-table | T-Statistics | P-Values | |||||
| Sample | Mean | Deviation | |||||
| Perceived Usefulness - | |||||||
| Social Factors - Usage | 0.011 | 0.010 | 0.014 | 1.97 | 0.775 | 0.438 | |
| Decisions | |||||||
| Perceived Ease of | |||||||
| Use - Social Factors - | 0.013 | 0.013 | 0.017 | 1.97 | 0.787 | 0.431 | |
| Usage Decision | |||||||
| Perceived Credibility - | |||||||
| Social Factors - Usage | -0.004 | -0.004 | 0.009 | 1.97 | 0.426 | 0.670 | |
| Decision | |||||||
The results of this study are in line with the previous research conducted by Styarini and Riptiono (2020). They have pointed out that the better the perceived usefulness of the user, the greater the possibility of the decision to use mobile banking services. Transactions using mobile banking services are faster so that urgent transaction needs can be resolved quickly without having to go to an ATM or bank. The research conducted by Haider et al. (2018) also found that perceived usefulness had a significant influence on the use of mobile banking services. The results of this study are related to the research conducted by Makanyeza (2019), which revealed that the perception of ease of use has no influence on one in deciding to use mobile banking services. Their findings are however, in contrast to the research conducted by Putri (2020) and Wardani (2021) which found that the perception of ease of use had an influence on decisions to use mobile banking services (Wardani, 2021). The results of present study are in line with the previous research conducted by Wicaksono (2021), Styarini (2020) and Koksal (2016)
which showed consensus in the finding that the perception of credibility would have an influence on decisions to use mobile banking services. One of the most important findings of the present study is that users agree that the BSI mobile is equipped with a professional security system so that the security and confidentiality of transactions are guaranteed. The responses given by BSI mobile users in this study were related to external influences in making decisions to use the BSI mobile. The majority of respondents gave responses that indicated that decisions to use BSI mobile were not influenced by external parties such as friends, relatives, family and others. The results of the present study are in line with the research conducted by Rita and Fitria (2021), which showed that there was no relationship between decisions to use mobile banking and social factors. This finding is different from the conclusions reached in the research conducted by Makanyeza (2017), Koksal (2016) and Putri (2020), which all confirmed that social factors could influence the decision making in using mobile banking. The test results of the present study have shown that social factors had no effect whatsoever on the relationship between perceived usefulness, perceived convenience and perceived credibility on the decision to use BSI mobile services. Thus, it can be said that the mediation hypothesis in this study, which stated that social factors could not mediate perceptions of usability, perceived ease of use and perceptions of credibility in making decisions about using mobile services was rejected. This is because the majority of the BSI mobile users in Jabodetabek did not decide to use the BSI mobile services due to the recommendations from friends, family, relatives and others. People decide to use the BSI mobile services due to their awareness of the need for these services. CONCLUSION Based on the results of the analysis carried out and foregoing discussions, it is concluded that in this study the factors that influence a person’s decision to use mobile banking. Based on the analysis, it can be concluded that perceived usefulness has a significant influence on decisions to use mobile banking. Meanwhile, the perceived ease of use does not have a significant influence on the decision to use mobile banking.
Social factors do not affect a person’s consideration of using mobile banking services because the decision is adjusted to the required needs. The analysis on social factors as mediation in the decision to use mobile banking shows that the mediating variable is not able to mediate the variables of perceived usefulness, perceived ease of use and perceived credibility. Social factors do not affect a person’s consideration of using mobile banking services because the decision is adjusted to the required needs. Analysis related to social factors as mediation in the decision to use mobile banking shows that the mediating variable is not able to mediate the variables of perceived usefulness, perceived ease of use and perceived credibility of the decision making to use mobile banking services. Social factors do not affect a person’s consideration of using mobile banking services because the decision is adjusted to the required needs. ACKNOWLEDGMENT This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.