THE INTENTION TO USE MOBILE BANKING DURING THE COVID-19 PANDEMIC: MODIFICATION OF THE UTAUT MODEL

This study wants to examine society's intentions towards mobile banking sharia in the ease of solving their financial problems. The increase in the use of smartphones makes the banking industry provide services mobile banking to facilitate and increase customer productivity, especially during the Covid-19 pandemic. Intention to use sharia mobile banking measured using the Unified Theory of Acceptance and Use of model Technology (UTAUT. Type this research uses quantitative research that is supported by data qualitative. The sampling technique used purposive sampling which was tested using the SEM-PLS analysis technique with an analytical tool, namely Warp-PLS 5.0 and exploratory analysis using SPSS 23. Results of SEM analysis shows that there is a good intention by the society in using mobile banking and the public finds it easy to operate to increase productivity. The implications of this research as input for the banking sector in terms of improving the quality of mobile banking so that people can produce during the Covid-19 pandemic.


Introduction
The financial services industry, especially in the banking sector, has experienced significant development from year to year, where this development is certainly inseparable from innovation resulting from consideration of the interaction between competitive pressures, customer needs, and technological innovation, where this is a rapid progress in the economic field. However, at this time the world has been shocked by an unprecedented situation with the emergence of a virus named "SARS-CoV-2" or also known as Coronavirus. Coronavirus is an infectious disease caused by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease was first discovered in December 2019 in Wuhan, the capital of Hubei Province, China. Since being discovered in December 2019, the virus has continued to spread globally and has caused the disease to spread to all countries in the world. The World Health Organization (WHO) declared the 2019-2020 coronavirus outbreak an International Health Emergency (PHEIC) on 30 January 2020, and a pandemic on 11 March 2020 (Supriatna, 2020).
Covid-19 is a global outbreak that has a negative impact on the human and social dimensions. After spreading from China, the pandemic quickly spread to 210 countries including Indonesia. The pandemic causes disruptions to global, domestic supply chains, financial market volatility, disruption of consumer demand and negative impacts in key sectors such as the banking sector (Sugihamretha, 2020). Referring to this, the banking sector is currently reducing services to customers directly with the urgency of suppressing the transmission of the COVID-19 virus (Khatun, Mitra, and Sarker, 2021). When the pandemic hit several countries around the world, the central banks of several countries such as China and Bangladesh have issued statements relating to the limitation of cash transactions and encouraging customers to use mobile banking, internet banking or other banking instruments to reduce the spread of the covid-19 virus (Khatun, Mitra, and Sarker, 2021). This has caused the use of mobile banking to increase in a number of countries.
Technology supports the banking sector in terms of service to customers in the form of innovations that connect customers with technology-based banking where the benefits are in the form of minimal transaction costs, can reach wider customers and increase convenience (Farquhar and Panther, 2007). This technology-based innovation is what we usually call Mobile Banking (M-Banking) which offers a platform for efficient transactions in banking. M-Banking is a banking service that offers increased value to customers by providing access "anytime and anywhere" (Lee and Chung, 2009).
Mobile banking refers to Islamic banking financial activities such as checking balances, account transactions, bill payments, and other forms of transactions. Mobile banking services are currently experiencing very significant developments throughout the world because they can reach customers with three channels through SMS-based, web-based, and mobile applications (Valentine, 2011). Previous research has estimated that the Asia-Pacific region is one of the important mobile banking markets, because the contribution of users of the Asia-Pacific region is more than half of the total user business (Goh, Suki, and Fam, 2014). The development of this mobility is an output of advanced innovation as well as a strategy for banks to increase and sell and retain customers (Goh, Suki, and Fam, 2014). Based on this, Islamic banks are also active in creating innovative technology strategies, including the use of mobile banking technology in achieving competitive advantage (Poon, 2008;Riquelme and Rios, 2010;Sadeghi and Hanzaee, 2010).
Recent research shows that the COVID-19 pandemic has led to an increase in the adoption of digital banking activities, one of which is mobile banking among consumers. Previous research also shows that 45% of respondents in America use mobile payment platforms and 31% of respondents switch from cash transactions to mobile banking (Khatun, Mitra, and Sarker 2021). This of course can be a strategy for Islamic banking in Indonesia in terms of marketing and expanding customer reach, so that Islamic banking can achieve a competitive advantage.
Islamic banking is defined as a banking system that strictly implements the principles and is guided by Fiqh Muamalah. The guidelines implemented by Islamic banking are guidelines based on the holy book Al-Qur'an and Sunnah (teachings, deeds and sayings of the Prophet Muhammad) and other secondary sources of Islamic law. In contrast to conventional banks, Islamic banking offers financial instruments that are consistent with Islamic values. This is one of the benefits that consumers get, in addition to the benefits of technology acceptance that are so significant for consumers (Goh, Suki, and Fam, 2014). In the self-harmony theory Sirgy (1985) reveals that the religious context embedded in mobile banking services can contribute to social stimuli that can provide positive interactions between consumers and service providers (Solomon, 1983) In a previous study by Goh, Suki, and Fam (2014) revealed that the presence of religious factors can be a form of self-expression where consumers are concerned with how consumption based on religion will affect and create their own identity. However, so far studies on technology acceptance in sharia-based mobile banking have not considered other, deeper factors (Islam, Kim Cheng Low, and Hasan 2013; Sulaiman, Jaafar, and Mohezar, 2007) Therefore, the researcher uses the UTAUT model where the model can be used to understand the acceptance and use of information technology such as mobile banking in the field of Islamic banking. Where this model was chosen because of its strong enough ability to predict the acceptance and use of technology (Venkatesh, Thong, and Xu, 2012). In this study the researchers divided into two studies. The researcher's first study aims to analyze the use of technology, namely mobile banking in Islamic banking during the Covid-19 pandemic. The second study of researchers aims to find problems and provide policy advice to improve Islamic banking mobile banking services during the Covid-19 pandemic.

Literature Review Theory Mobile Banking
Mobile Banking is a term in the banking industry in Indonesia to fulfill services between banks and customers. Mobile banking is not only limited to SMS banking but includes all activities using modern operations based on digital technology (Riza and Hafizi, 2020). Mobile banking allows customers to perform financial transactions such as account transfers, bill payments, and other financial services in a secure application that can be accessed using a smartphone. Therefore, the hope of mobile banking is to facilitate transactions with only internet and smartphone channels (Tam and Oliveira, 2017).

UTAUT
The Unified Theory of Acceptance and Use of Technology (UTAUT) is a comprehensive theoretical model in researching the use of a technology introduced by Vankatesh. UTAUT is the result of a combination of eight theories, namely TRA, TAM, T Motivational Model, TPB, C-TAM-TPB, MPCU, IDT, and T Social Cognitive Theory taken from four constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions moderated by gender, age, experience, and voluntary use. UTAUT can explain 70% of technology adoption decisions and represents a more complete set of constructs for explaining and predicting user behavior. In other words, the UTAUT model is very strong for predicting an individual's intention to accept information technology (IT) and is suitable for explaining and predicting a person's behavior related to the continued use of information systems (Rita and Fitria, 2021).

Hypothesis Development 1. Performance Experience affects Behavior Intention
Performance expectancy can be interpreted as the level of user confidence that in using a system and will be able to improve work performance. When users increasingly trust the system provided, users will feel comfortable using the system (Kumala, Pranata, and Thio 2020). Previous research conducted by Gunawan (2019) concluded that performance expectancy has a significant positive effect on behavioral intention, which means that the performance expectancy that users have of a system can lead to behavioral intention. Therefore, the researcher hypothesizes that, H1: Performance Experience has an effect on Behavior Intention 2. Effort Expectancy affects Behavior Intention Effort expectancy is a level of ease that a person gets when using a system that shows how much effort is made by the user to use the system. The ease of using the system will cause a feeling of interest in a person that the system has a use and it creates a sense of comfort when using it (Ivan and Karina 2018). In a study conducted by Wibowo, Mursityo, and Herlambang (2019) stated in his research that there was a significant effect of the effort expectancy variable on behavioral intention. In this case, it is closely related that if the developer of a system develops its application so that it can be easily used by people of various ages, the level of use of the application can be higher (Wijaya and Handriyantini, 2020). Therefore, the researcher hypothesizes that, H2: Effort Expectancy has an effect on Behavior Intention 3. Social Influence affects Behavior Intention Social influence is defined as the degree to which a person feels it is important for others to believe that he or she is using a system that conforms to the expectations of others. This behavior is influenced by the opinions of people around such as family, co-workers and other parties (Rema and Setyohadi, 2016). In previous research conducted by Mediyanto and Mahendra (2017) concluded that social influence affects the behavioral intention of users, meaning that users always take advantage of the system and always receive support from other users. Thus, the researchers hypothesized that, H3: Social Influence affects Behavior Intention

Facilitating Conditions affect Behavior Intention
Facilitating conditions can be defined as a person's level of confidence in the infrastructure and supporting facilities owned to support the use of a system. Conditions that facilitate users of a system are one of the factors that will affect the utilization of the system (Sa'idah, 2017). In a previous study conducted by Fauzi, Widodo, and Djatmiko (2018), he concluded that facilitating conditions affect behavioral intention significantly and positively, meaning that the interest of application users is influenced by the resources or devices owned by the user. To use a system, it is necessary to have adequate infrastructure such as an Android-based smartphone and an internet network (Indah and Agustin, 2019). Therefore, the researcher hypothesizes that, H4: Facilitating Condition affects Behavior Intention

Habit affects Behavior Intention
Habit is a behavior that is done routinely. The intensity of time in doing a habit will produce a different level of habit (Nugraha, 2020). In this case, the habit in question is about how a person uses a system in his daily life (Arianto, 2020). Habit can build perceptions that reflect the results of previous experiences. Previous use can be used as a predictor in the use of a system in the future. Conceptually, habit is more related to behavior that is automatically formed on the basis of knowledge, experience and skills from time to time (Septiana, Salim, and Daulay, 2020). In a previous study conducted by Sutanto, Ghozali, and Handayani (2018) it was concluded that there was a significant positive effect of habit on behavioral intentions. The more often users use a system, the stronger the intention to use it. Therefore, the researcher hypothesizes that, H5: Habit affects Behavior Intention 6. Trust has an effect on Behavior Intention Trust can be interpreted as a person's desire to be sensitive to the actions of others based on the expectation that others will perform certain actions on people who trust them without depending on their ability to monitor and control them. Trust can also be defined as the overall knowledge possessed by consumers or users and all conclusions made by consumers about an object and its benefits, this knowledge will encourage someone to do something because the object they trust is in line with expectations (Syafaruddin 2016). In a study conducted (Chiu, Bool, and Chiu, 2017), it is stated that trust has a significant effect on behavioral intention. Trust that affects intention means that the more users trust a system, the greater the user's desire to reuse the system (Wilson and Keni, 2018). Therefore, the researcher hypothesizes that, H6: Trust has an effect on Behavior Intention 7. Satisfaction affects Behavior Intention Satisfaction is the extent to which the perceived performance of the product can meet user expectations. Users who are satisfied will cause a desire to use repeatedly because it can have a positive impact and provide good value (Indrata and Susanti 2017). Not only that, satisfied users will recommend an object they use to others and are less likely to have eyebrows on another object. Satisfaction involves cognitive and affective components that affect the formation of satisfaction. The cognitive in question can be in the form of personal experience, while the affective component refers to the user's feelings towards an object, for example whether the user likes the object or not (Tandijaya, 2018). Satisfaction is the final condition that users want in using something and is not just about assessing the quality of the experience but is also influenced by other factors (Mayliza, 2019). In a study conducted by Purwianti and Tio (2017) stated that customer satisfaction has a significant effect on behavioral intention. This means that a product or object is able to meet customer needs at a certain level. Thus, the researchers hypothesized that, H7: Satisfaction affects Behavior Intention

Research Methods
This research is included in quantitative research supported by qualitative data. The first study is quantitative because it involves data in the form of numbers that are processed by testing hypotheses through empirical statistics. While the second study uses qualitative data to see if there is convenience in using mobile banking during the Covid-19 pandemic. In this study, data collection used a survey method with a questionnaire instrument using open questions and closed questions. The questionnaire consists of 8 variable constructs by adopting the UTAUT theory with 39 question items using a Likert scale of 1 to 5. The sampling technique in this study is purposive sampling, meaning that there are certain criteria for respondents to be able to answer questions in the questionnaire. Meanwhile, the population in this study was the Indonesian people, amounting to 501 respondents. The respondent's criteria are Indonesian people who use Islamic bank mobile banking. The research model was tested empirically using a statistical approach by adopting the Structural Equation Modeling (SEM) model. Furthermore, to confirm the standard theory, the researcher uses the SEM model based on Partial Least Square or more popularly known as SEM-PLS. The analytical tools used are Warp-PLS 5.0 and SPSS 23

Study 1: Closed Question Analysis
Validity Test and Reliabillity Test Ghozali (2005) explains that the indicator of the variable is said to be valid if the value of the loading factor and Average Variance Extracted (AVE) > 0.5 and is said to be reliable if the Cronbach alpha and Cronbach reliability values are > 0.6. Based on the results of data processing, it is found that all items have a loading factor that has a value of > 0.5 and has a Cronbach alpha value of > 0.6. Therefore, the questions asked by the author are valid and reliable, so that they can be continued to the next stage of analysis.  In this study, the fit value with the Tenenhaus GoF model has a value of 0.745 (> 0.36 = Large), APC value of 0.716 P < 0.001 (P value < 0.005), ARS value of 0.783 P < 0.001 (P value < 0.005), AARS value 0.780 P < 0.001 (P value < 0.005), AVIF value 2.365 (< 3.3 = ideal), AFVIF value 2.524 (accepted < 5), and RSCR value of 1,000 (ideal = 1). Therefore, this study can be said to be fit and further analysis can be carried out.

H1. Performance Expectancy => Behavior Intention
Based on data processing, it was found that performance expectancy on behavior intention has a P value of < 0.01. This shows that H1 is accepted because it has fulfilled the requirements for P value < 0.01. Therefore, hypothesis 1 can be accepted, namely performance expectancy has a direct effect on behavior intention.
This study states that performance expectancy has a direct effect on the behavior intention of sharia m-banking users. This shows that respondents have an advantage in using sharia m-banking, namely respondents feel more effective and efficient in transactions so that they can increase work productivity when using sharia m-banking, so that respondents have good intentions in using sharia mbanking. This research is in line with research from Gunawan (2019) which says that performance expectancy has a significant positive effect on behavioral intention, which means that the performance expectancy that users have of a system can lead to behavioral intention.

H2. Effort Expectacy => Behavior Intention
Based on data processing, it was found that the effort expectacy of behavior intention had a P value of < 0.01. This shows that H2 is accepted because it has fulfilled the requirements for P value < 0.01. Therefore, hypothesis 2 can be accepted, effort expectancy has a direct effect on behavior intention.
This study states that effort expectancy has a direct effect on the behavior intention of sharia m-banking users. This shows that respondents find it easy to learn and operate m-banking as a whole, so that respondents have good intentions in using Islamic m-banking. This study is in line with research from Wibowo, Mursityo, and Herlambang (2019) which states in his research that there is a significant effect of the effort expectancy variable on behavioral intention.

H3. Social Influence => Behavior Intention
Based on data processing, it is found that social influence on behavior intention has a P value of < 0.01. This shows that H3 is accepted because it has fulfilled the requirements for P value < 0.01. Therefore, hypothesis 3 can be accepted, social influence has a direct effect on behavior intention.
This study states that social influence directly affects the behavior intention of sharia m-banking users. This shows that the influence of the surrounding environment of the respondents (family, friends, community) provides good support for using sharia m-banking, so that respondents feel influenced to use sharia m-banking. This research is in line with research from Mediyanto and Mahendra (2017) concluding that social influence affects the behavioral intention of users, meaning that users always take advantage of the system and always receive support from other users.

H4. Facilitating Condition => Behavior Intention
Based on data processing, it was found that facilitating condition on behavior intention has a P value of < 0.01. This shows that H4 is accepted because it has fulfilled the requirements for P value < 0.01. Therefore, hypothesis 4 can be accepted, facilitating conditions directly affect behavior intention.

H5. Habit => Behavior Intention
Based on data processing, it was found that habit on behavior intention had a P value of < 0.01. This shows that H5 is accepted because it has fulfilled the requirements for P value < 0.01. Therefore, hypothesis 5 can be accepted, habit has a direct effect on behavior intention.
This study states that habit has a direct effect on the behavior intention of sharia m-banking users. This shows that respondents have habits, skills, and interests in using sharia m-banking for their daily activities/work, so this makes respondents have good intentions in using sharia m-banking. This study is in line with research from Sutanto, Ghozali, and Handayani (2018) which concludes that there is a significant positive effect of habit on behavioral intentions. The more often users use a system, the stronger the intention to use it

H6. Trust => Behavior Intention
Based on data processing, it was found that trust on behavior intention has a P value of < 0.01. This shows that H6 is accepted because it has met the requirements of P value < 0.01. Therefore, hypothesis 6 can be accepted, trust has a direct effect on behavior intention.
This study states that trust has a direct effect on the behavior intention of states that trust has a significant effect on behavioral intention. Trust which has an effect on intention means that the more users trust a system, the greater the user's desire to reuse the system.

H7. Satisfaction=> Behavior Intention
Based on data processing, it is found that satisfaction with behavior intention has a P value of < 0.01. This shows that H7 is accepted because it has met the requirements of P value < 0.01. Therefore, hypothesis 6 can be accepted, satisfaction has a direct effect on behavior intention.
This study states that satisfaction has a direct effect on the behavior intention of sharia m-banking users. This shows that respondents are satisfied with the use of m-banking because their activities/works feel helped, so this makes respondents have good intentions in using Islamic m-banking. This study is in line with research from Purwianti and Tio (2017) which states that customer satisfaction has a significant effect on behavioral intention. This means that a product or object is able to meet customer needs at a certain level.

Study 2: Analysis of Open Questions
Based on Study 1, it can be seen that people have good intentions in using sharia m-banking in their daily lives. These intentions are influenced by performance expectations, business expectations, social influences, facilitating conditions, habits, beliefs, and satisfaction which ultimately affect them in using sharia m-banking. However, researchers have the assumption that not only these factors affect user acceptance. Therefore, in study 2, the researcher tries to explore by asking open-ended questions to see the factors that influence people in using sharia m-banking. The results of this open analysis the author uses SPSS 26 in helping to process the data. From the data processing, it was found that as many as 501 respondents said that the presence of sharia m-banking could support the ease of doing business or work of the respondents.

Conclusion
This study found that respondents feel more effective and efficient in transactions so that they can increase their work productivity using m-banking, besides that respondents find it easy to learn and operate m-banking as a whole, on the other hand respondents have good knowledge and have access to using mbanking. This is also reinforced by data on respondents who have habits, skills, and interests in using m-banking. With this, respondents have high trust and respondents feel satisfied, so respondents have good intentions to use m-banking in helping business or just supporting their daily work.
In addition to finding the fact that sharia m-banking provides benefits and the community has the intention to use it, the researchers found other factors outside the UTAUT variable. Researchers found 9 other factors that made respondents believe in using sharia m-banking in carrying out their daily activities during the Covid-19 pandemic. Thus, digitalization of banking through m-banking is expected to meet customer satisfaction and maintain loyalty during the pandemic.
In the research it has been concluded that consumers feel significant benefits from the existence of mobile banking. Respondents find it easy to learn and operate mobile banking, and the use of mobile banking is considered more effective and efficient in Islamic banking transactions. Therefore, the proposed practical action for the banking sector is to always maintain and improve the quality in terms of technical accessibility of usage. Furthermore, banks also need to add extra features that further provide preference and user satisfaction, which can increase user interest and habits in using mobile banking.
In Indonesia, the infrastructure to support mobile banking, such as the availability and ease of internet access, cheap electronic payment devices, and others not yet evenly distributed, giving rise toeffort morein the use of mobile banking.
Therefore, for policy makers in Indonesia, the distribution of new technology supporting infrastructure and inclusive f inancial literacy must be the main focus.
Furthermore, the government needs to accommodate policies to ensure the security of user data. It is hoped that mobile payment the implementedcan support profitability and increase competitiveness to the competitive advantage of Islamic banking in entering the new era of society 5.0.