Factor Analysis of Sharia Mobile Banking Using the Utaut2 Model in Millenial Generations

The rapid development of technology has had an impact on a variety of fields, one of which is banking. All banks compete in making services digitally. Shariah Bank provides mobile banking app services for use by millennial-dominated customers. The aim of this research is to identify the factors that influence millennials use of mobile sharia banking using the UTAUT2 model. This research is quantitative research, where the research instrument is a questionnaire with a Google Form to obtain primary data from respondents. The population in this study is the millennials in the Jabodetabek region; the number of samples used was as high as 200 respondents. The sampling method is non-probability sampling with purposive sampling. The analytical method used is PLS-SEM. The results of this study show that performance expectancy, social influence, facilitating condition, price value, and habit influence behavioral intention. Use behavior is influenced by facilitating conditions, habits, and behavioral intentions. The conclusion of this study is that it proved that the construction of UTAUT2, consisting of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit, and price value, has important roles in determining the intentions and attitudes of mobile banking use.


Introduction
In the current era of globalization, the use of technology facilitates people's daily lives (Infomatika, 2015).Technology is becoming an essential necessity in life to socialize, work, and transact (Anandia & Aisyah, 2023).The rapid development of technology has had an impact on a variety of fields, one of which is banking.All banks compete in making services digitally available; one of them is Shariah Bank, which provides mobile banking applications to users dominated by the millennial generation to provide ease in making transactions online.
The millennials are also the majority of Internet users that are widely used by the inhabitants of the island of Java, which is 81.83%.The provinces of Jakarta and West Java are the regions with the most Internet users, especially in the regions of Jakarta, Bogor, Depok, and Tanggerang (Jabodetabek), which is a metropolitan city with ease in accessing the Internet.Therefore, mobile banking at the sharia bank has a huge opportunity to be used by the millennial generation in the Jabodetabek region due to the very high level of smartphone and internet usage.Based on the financial inclusion rate of 2022, the Shariah Financial Inclusion Index is still small, reaching only 12.12%, but the financial index generally reaches 85.10% (Otoritas Jasa Keuangan, 2021).This shows that there is still a low level of public interest in Sharia financial products and services.There are several factors that are believed to be the cause of the low public interest in Sharia financial products and services; one of them is the low sharia financial literacy rate, which is still low and will reach only 9.14% by 2022.The lower level of sharia financial inclusion in Indonesia than the level of financial inclusion generally indicates that there are still many Indonesians who have access to conventional banking services rather than sharia banks (Sukmawati et al., 2021).This means that the quality of mobile banking services in sharia banks must always be developed and improved so that the number of sharia bank customers and users in the millennial generation has improved, of course by looking at the factors that can influence the generation of millennials to use mobile sharia banking.To measure the usage factor of a system, you can use the UTAUT2 model.Studies conducted by Mufingatun et al., (2020), Dhingra and Gupta (2020), Parayil Iqbal et al., (2022), Mohd Thas Thaker et al., (2022) show that variables in UTAUT2 such as performance expectancy, effort expectanity, social influence, facilitating conditions, hedonic motivation, habit, and price value influence behavioral intention and use behavior on the use of a technology or application system.Then it became the motivation for his research on the factors that influenced the millennial generations in Jabodetabek to use mobile banking services in Shariah using the UTAUT2 theoretical model.

The Effects of Performance Expectancy on Behavioral Intention
Performance expectancy is the degree of a person's confidence that the use of the system can help him obtain performance gains in his or her activity (Venkatesh et al., 2003).Performance expectations are an important variable because previous research has shown that these factors influence a person's acceptance of technology.This view is empirically supported by research carried out by Chaidir et al.,(2021), Rita and Fitria (2021), Maharani (2021), Anjani and Mukhlis (2022), Mufingatun et al.,(2020).shows that performance expectations have a positive influence on interest in mobile banking usage.Based on the above description, the researchers formulate the hypothesis as follows: H1: Performance expectancy influences behavioral intention in the use of mobile sharia banking.

The Effect of Effort Expectancy on Behavioral Intention
Effort expectation is defined as the ease of use of a system that can reduce effort, energy or time a person spends doing an activity (Venkatesh et al., 2003).A person's perception of ease in using a system becomes something that tends to influence one's desire to use the system.This is demonstrated by a study by Mufingatun et al., (2020), whose results show that effort expectancy has a significant influence on behavioral intention.In other research conducted by Yuliana dan Aprianingsih (2022), the test results show that business expectations have proven to be the primary predictor of consumer behavior intentions.Based on the above description, the researchers formulate the hypothesis as follows: H2: Effort expectancy influences behavioral intention in the use of mobile sharia banking.

The Effect of Social Influence on Behavioral Intention
Social influence is the degree to which one believes that it is best to use a system.Social influence also explains that a person uses technology because of the impulses of the people around him (Andrianto, 2020).Studies conducted by Mufingatun et al.,(2020) and Putri (2023) show that social influence influences the behavioral intentions of mobile banking users.Based on the above description, the researchers formulate the hypothesis as follows: H3: Social influence influences behavioral intentions in the use of mobile sharia banking.

The Effect of Facilitating Conditions on Behavioral Intention
A facilitating condition is the degree to which one believes that the organizational and technical infrastructure exist in support of the use of the system (Venkatesh et al., 2003).Generally, users with low levels of facilitating conditions will have a lower intention to use technology.According to Mohd Thas Thaker et al., (2022), the results of the study show that conditions that facilitate variables have a positive influence on behavioral intentions and the adoption of internet banking.Based on the above description, the researchers formulate the hypothesis as follows: H4: Facilitating conditions influence behavioral intentions in the use of mobile sharia banking

The Effect of Facilitating Conditions on Use Behavior
According to Andrianto (2020), facility support explains a person's perception that infrastructure is a device or knowledge that supports the use of a system or technology.Support condition is influenced by use behavior when using mobile sharia banking (Anandia & Aisyah, 2023).This study is also in line with the EM-2023-5155

Population and Sample
The population in this study is the millennial generation that uses mobile banking in Shariah and is in the Jabodetabek region.In this study, the sampling technique used is non-probability sampling with purposive samplers, where the criteria are the Millennial generation of users of mobile app banking who are domiciled in Jabodetabek and have at least once used mobile application banking.The number of samples used is 200.

Measurement
In this study, the variables performance expectancy, effort expectance, social influence, facilitating conditions, hedonic motivation, habit, price value, behavioral intention, and use behavior were measured using a 5-point Likert scale.The question item used in the questionnaire was adapted from research byVenkatesh et al., (2012), Maharani (2021), Dhingra and Gupta (2020).

Data analysis
In this study, partial least squares structural equation modeling (PLS-SEM) data analysis techniques and SmartPLS 3.2.9software were used to test the hypotheses in the study.

c) Reliability Test Results
The predictor is reliable when Cronbach's alpha value is > 0.6 or composite reliability is > 0.7.Here are the reliability test results: Based on Table 4, it is known that the Cronbach's alpha value of the entire variable has been met at > 0.6 and the composite reliability value of all the variables has also been met < 0.7.This proves that the measurement at this intersection is reliable.

Inner Model Results
An internal model analysis is an analysis step to test a model or a hypothesis, also called structural analysis.

a) Test Results: Coefficient of Determination (R2)/R-Square
The calculations obtained for the R2 test are as follows: The results of the Q-Square test in Table 6 showed a value of 0.571 for behavioral intention and use behavior, which means that they have great predictive capabilities.Both the behavioral intention variables and the use behavior have Q-square values greater than 0, so this indicates that the entire model in this study already meets the relevant and accurate predictor relevance.

Hypothesis Test
In this study, data analysis was carried out for the testing of hypotheses using the bootstrapping method with the help of the SmartPLS 3.2.9program.The following table is the result of the hypothesis test: The criteria applied in this study are t-statistics > 1,972 with a p-value significance rate < 0.05 and a positive path coefficient.

The Effect of Habits on Behavioral Intentions
Based on statistical calculations, it can be concluded that habits have a positive and significant influence on behavioral intentions.The results of this study are in line with previous research by Yuliana and Aprianingsih (2022), the results of which indicate that habits influence behavioral intentions, and the habits variables prove to be the primary predictor of consumer behavior intentions.

The Effect of Habits on Use Behavior
Based on statistical calculations, it can be concluded that habits have a positive and significant influence on use behavior.This study is consistent with the results of previous research conducted by Shafly (2020), the results show that habit has a significant effect on the use behavior variable.This study was also supported by Pratama dan Renny (2022), whose findings show that habit and behavioral intention have a positive influence on use behavior.

The Effect of Behavioral Intention on Use Behavior
Based on the results of statistical calculations, it can be concluded that behavioral intentions have a positive and significant influence on use behavior.The results of this study are consistent with the previous results of the study conducted by the Hakim (2023), the results show that behavioral intentions positively and significantly influence use behavior in Indrive application users in Bandung.

Conclusions
Based on the results of research and discussion, the following conclusions can be drawn: 1. Performance expectancy influences behavioral intention to use Sharia mobile banking.

Implications
Based on the results of the research, it was proven that the construction of UTAUT2, consisting of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit, and price value, has important roles in determining the intentions and attitudes of mobile banking users.This implies that Sharia banking can pay attention to several factors that can influence the use of Sharia mobile banking, such as performance expectation factors, social influence, facility conditions, price values, and habits.Sharia Banking as a provider of mobile banking services Sharia banking should be able to develop its application to improve the convenience and pleasure of customers by providing promos that are able to attract other customers to use the mobile application.Social influence has become one of the factors that dominate society's use of mobile sharia banking, so it is important to do literature related to sharia so that people are better aware of it.Sharia banking can further improve the service communication network through socialization and Sharia financial education in various communities.Through the implementation of the Shariah financial literacy program, the public will become more aware of the existence of shariah products, which can be used as a source of financing, the empowerment of the people's economy, and the use of mobile banking, which can provide ease for users in conducting digital transactions.

Recommendations
1. Sharia Banking as a mobile banking service provider, is expected to add useful features for users to improve productivity and help in everyday activities, such as by creating easy-to-use features for making transactions.2. For the public, it is expected that in the future there will be more use of mobile sharia banking services as an online transaction medium, especially for the younger generation who have followed the current technological developments, so that society can be more practical and efficient in carrying out various transactions and can increase the inclusion of sharia financial services in Indonesia with the use of mobile sharia banking.3.For future researchers, it is expected to be possible to add variables that were previously not present in this study, such as trust variables, perceived credibility, and perceived self-efficacy, that can affect the use of a technology system.The population in this study was only the millennial generation of mobile sharia banking users in Jabodetabek.To get the most results, the researchers could further expand the area of dissemination of the questionnaire that covers various regions in Indonesia or in other countries to get results that more accurately describe the use of mobile sharia banking in general.

2 .
Effort expectancy has no effect on behavioral intention to use Sharia mobile banking.3. Social influence influences behavioral intention to use Sharia mobile banking.4. Facilitating conditions influence behavioral intentions to use Sharia mobile banking. 5. Facilitating conditions influence use behavior in the use of sharia mobile banking.6. Hedonic motivation has no effect on behavioral intention to use sharia mobile banking.7. Price value influences behavioral intention to use Sharia mobile banking.8. Habit influences behavioral intention to use Sharia mobile banking.9. Habit influences use behavior when using Sharia mobile banking.10.Behavioral intention influences use behavior when using Sharia mobile banking.

Table 1 . Overview Of Respondents (Advanced)
There are three criteria in the use of data analysis techniques with SmartPLS to evaluate external models: convergent validity, discriminant validity, and reliability.a) Convergent Validity The validity test is viewed based on the average variance value extracted (AVE).Here's the AVE output:

Table 2 . AVE Validity Testing
From table 2, you can see that the AVE value of each variable is greater than 0.5, which means that the latent variables all meet the convergence validity requirement.b)Discriminant Validity The validity of the discrimination is determined using cross-loading values.The cross-load values of this study can be seen in the following table:

Table 5 . R-Square test results
Based onTable 5, it is known that the R-square value for the Behavior Intention variable (BI) is 0.819.It suggests that Performance Expectancy (PE), Effort Expectance (EE), Social Influence (SI), Facilitating Condition (FC), Hedonic Motivation (HM), Price Value (PV), Habit (HT) can explain or influence Behavioral Intention (BI) by 81.9%, with the remaining 18.1% being influenced by other factors outside the study model.Then the R-square value for the Use Behavior (UB) variable is 0.775.This shows that Facilitating Conditions (FC), Habit (HT) and Behavioural Intention (BI) are able to explain or influence use behavior (UB) by 77.5%, with the remaining 22.5% is influenced by other factors outside the research model.