Analysis of Factors Affecting Interest and Behaviour in using E - SPT 21/26 application for Corporate Tax Payers: A UMEGA Model Perspective

. E-SPT PPh Article 21/26 reports on employee income tax, where article 21 regulates Indonesian employees, and article 26 regulates foreign employees domiciled in Indonesia. After distributing questionnaires to 121 respondents experienced in using the e-SPT 21/26 application, the results show that the e-SPT 21/26 application from the aspect of efficiency, effectiveness, and performance improvement does not affect the tendency to use the e-SPT application. Significantly encouraging the use of the E-SPT application are environmental influences, incentives to fulfill tax obligations, and risk aspects that can be more suppressed.


Introduction
At this time, the development of information technology is very rapid, which encourages changes in various sectors of human life, one of which is in terms of public administration.At first, a service is considered convoluted, then becomes more efficient.This encourages public administration to innovate in providing more service to the community (Anshar, 2012;Kurniawan, 2007).Therefore, to improve public services, the government began to participate in utilizing the use of information systems technology that is currently better known as Electronic-Government.E-Government is becoming a good thing to implement because it is effective, efficient, transparent, and accountable, encouraging improving government performance in providing better services to society.E-Government is a digital transformation carried out by the government.The existence of this digital transformation can realize the Sustainable Development Goals (SDGs) or sustainable development programs.The digital transformation in administration processes, especially E-Government, supports local government efforts in obtaining information by collecting data using computer enabling strategy formulating in providing better services to the community so that they which in line with SDGs (ElMassah & Mohieldin, 2020).The existence of e-Government is one of the 16th SDG implementations, which is providing access to justice for all and building effective institutions, accountable and inclusive at all levels.Such transformation aims to build accountable and transparent institutions at all levels.Among the various online services provided by the government, e-SPT is one of the breakthroughs made by the Directorate General of Taxes of the Ministry of Finance to facilitate taxpayers submitting SPT.On the other hand, a digital tax system, such as e-SPT, is also a complex process and requires adaptation from the community so that the implementation of this policy can go according to plan and improve tax payment performance (Šestáková, 2018).There are several previous studies related to digital tax payments.Surmayanti and Roekhudin (2017) stated that because state revenue from taxes is the highest income for the state compared to non-tax revenues, the digital transformation of tax services is required.To increase the tax ratio, it is prudent to improve the tax system, including tax policy and administration.This digitalization can boost taxpayer convenience and deliver good service.e-SPT generally improves the tax filing process while at the same time lowering monetary costs for both taxpayers and the government (Nugroho et al., 2022;OECD, 2004;Statistics and Countries, 2017;Surmayanti et al., 2017).Veeramootoo et al. (2018) found that despite the benefits and popularity of e-SPT, some people have highlighted concerns about its underuse.If users do not use it regularly, the full benefits may not be realized.As the number of people who use e-SPT grows, tax authorities must design strategies to ensure that users continue to use the system.As a result, studying the factors that influence taxpayer interest and behavior concerning e-SPT is a commendable undertaking and an important component of a valuable research agenda.The findings can be utilized to encourage the continued use of e-SPT for the benefit of both taxpayers and governments.e-SPT is the electronic version of Surat Pemberitahuan Tahunan (SPT) (annual tax return).According to Haning et al. (2018), prior to 2008, SPT was reported using a paper-based system.That condition was no longer regarded as effective.e-SPT replaces the traditional form of SPT and performs the same functions.There are several advantages of using e-SPTs, including guaranteed data security, organized taxation data, computerized calculations that improve data accuracy, simplified tax reporting, and paperless.Based on those previous studies, the research gap from this research is that there is no study that discusses the factors that influence interest and behavior in the use of e-SPT using UMEGA.This will be the state of the art of this research.This research will make a practical contribution as a study for the government to find out community behavior related to the use of e-SPT and as a research contribution in the application of UMEGA to analyze the use of e-SPT as tax payments.

Objectives
This research intends to discover which factors influence taxpayers' interest and behavior in using e-SPT, particularly business taxpayers, using the Unified Model of Electronic Government Adoption (UMEGA).UMEGA was chosen because there are not many studies that discuss taxpayers' interest and behavior factors towards the use of e-Government.Most of the research focuses on the acceptance model (TAM).The UMEGA approach is a popular method for determining public approval of e-Government applications.UMEGA has seven variables with five main variables: effort expectancy, social influence, performance expectancy, facilitating conditions, and perceived risk.Attitude variable as a mediating variable and the user's behavioral intention as the influenced variable.

Literature Review
Several models used in research find the behavior and interest of users to use IS/IT interventions.IS/IT can function as an intellectual component and infrastructure used by organizations with reference to resources in drawing business conclusions.Thus, business actors can enable the achievement of efficient use of resources and still achieve goals.IS/IT can also support management decision-making, reduce costs, and meet business capability requirements.Thus, IS/IT can consistently provide satisfaction to clients.In this study, e-SPT is an example of an IS/IT intervention carried out to produce digital tax payment services for the public (Maguire & Ojiako, 2007).However, based on the analysis results, most of these models perform below expectations because the possibility of IS/IT interventions in e-Government is different (Venkatesh et al., 2003).Therefore, we need a model used specifically for technological intervention in e-Government, which is called the e-Government specific-unified model.The basis for developing this model is the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003)

Performance Expectations and Intentions
Venkatesh et al. (2003) define performance expectations as a person's level of belief that a system he uses will help improve his performance.The basis of this concept is perceived usefulness, extrinsic motivation, job suitability, relative advantage, and expected outcomes.Performance expectations using perceived benefits were found to have the power to explain the intention to use product technology.Handayani (2007) states that performance expectations are a strong predictor of interest in the use of information technology in voluntary or mandatory settings.These results are in accordance with the research conducted by Venkatesh et al. (2003).There the following hypothesis arises.H1: Performance expectancy has a significant effect on Attitude

Efforts Expectations
Based on previous research, effort expectation or business expectation is the level of simplicity in using the system (Al Awadhi & Morris, 2008; Venkatesh et al., 2003).The concept of business expectations is formed by three constructs, namely perceived ease of use, complexity, and ease of use (Venkatesh et al., 2003).This construct will be positive at the initial use of a system but becomes ineffective if used continuously (Agarwal & Prasad, 1999;Venkatesh et al., 2003).Handayani's research (2007) shows that business expectations are the main factors that influence interest in using information systems.Several studies conducted by (Chiu, Sumak, and Park, 2003) showed that there was a positive and significant relationship between perceived ease of use and an individual's attitude.Therefore, the following hypothesis was formulated: H2: Business expectancy has a positive significant effect on attitude

Social Influence
According to Venkatesh et al. (2003), social influence is the extent to which an individual feels that other people who are important to them believe that he or she should use a system.Social factors are indicated by the amount of support from colleagues, superiors, and organizations.This social influence is influenced by subjective norms, social factors, and image.Social influence can be in the form of beliefs, roles, experiences, behaviors, and values held (Ajzen & Fishbein, 1980).Previous research has found a positive relationship between the use of information technology and social influence (Gupta, Dasgupta, and Gupta, 2008).Saleh and Laxman (2014) also point out the importance of social factors in terms of acceptance and use of information technology among teachers in Brunei Darussalam.Social support factors are coworkers, senior managers, leaders, and organizations (Thompson, Higgins, and Howell, 1991).Leaders who support the use of information technology in an organization will have a positive effect on the use of technology.This support will be very meaningful in the early stages of using information technology (Teo & Pok, 2003).Several studies show that social influence positively influences attitude toward using technology (Park et al., 2007); some are across different age groups and varying levels of internet experience (Chiu et al., 2012).It is believed that societal influence from people of proximity has a positive impact on an individual's attitude toward E-Government application (Dwivedi et al., 2017).The following hypothesis can be made: H3: Social influence has a positive significant effect on attitude

Facilitating Conditions
According to Venkatesh et al. (2003), facilitating conditions are defined as the level to which a person believes that an organizational and technical infrastructure is available to support the use of a system.It depends on the application service provider, technology generation, and device.Previous studies showed that facilitating conditions could influence behavioral control and intention (Vaenkatesh et al., 2012).We make the following hypothesis: H4: Facilitating conditions has a significant positive effect on behavioural intention

Facilitating conditions influence effort expectancy
Schaper et al. ( 2007) discovered a positive and significant relationship between facilitating conditions and effort expectancy when studying ICT acceptance and utilization by Australian occupational therapists.In addition, Urumsah et al. (2011) discovered that the good-quality technological infrastructures and assistance offered by the airlines influenced a consumer's access to and use of the e-services of Indonesian airlines.As a result, we came up with the following hypothesis: H5: Facilitating conditions influence effort expectancy

Perceived Risk
Recent research also shows that an individual's perception regarding the risk inhibits IS/IT reformation adoption.People are reluctantly sharing their personal information or identities on the web (Rana et al., 2015;Schaupp & Carter, 2010).Perceived as a subjective expectation of suffering loss while pursuing the desired outcome (Gefen et al., 2003).Several researchers conducted on e-commerce adoption showed that perceived risk has a significantly negative association with users' attitudes (Sulaiman et al.,2012).Hence, the following hypothesis can be made: H6: Perceived risk has a significant negative effect on attitude

Attitude influence behavioral intentions
Several researchers (e.g., Hung et al., 2009Hung et al., , 2013;;Lu et al., 2010) in the field of public administration and e-Government have substantiated the association between attitude and behavioral intention.Hung et al. (2013) found attitude to be a crucial element in understanding and predicting mobile users' behavioral intentions when they studied users' acceptance of mobile e-Government services in Taiwan.The following hypothesis was formulated in recognition of its importance in IS/IT adoption research in general and e-Government adoption in particular: H7: The attitude towards using the system has a positive relationship with behavioral intention

Methods
The method in this research is quantitative with a sampling method.The data collection technique used a survey method with the distribution of questionnaires.The population in this study are tax consultants and workers in companies who are responsible for reporting corporate taxes as many as 102 respondents.Researchers suspended the questions in the questionnaire with a Likert scale which were divided into six categories, namely Strongly disagree, Disagree, Quite agree, Agree, Totally agree, and Totally agree so much.Researchers do data processing with partial Least Square SEM (SEM-PLS) on the Smart-PLS application.SEM PLS is due to a strong analytical method where data with a small number of samples can be analyzed (Ghozali, 2014), to assist in a more in-depth analysis of research results from respondents related to e-SPT using a sample of 102 respondents.This study also uses a random sampling method with an area sampling technique that focuses on the coverage of companies who are responsible for reporting corporate taxes and obtains 102 respondents as a sample.

Data Collection
Data were collected primarily through Google Form with a total of 102 respondents.The respondents were male, with a total of 59 people (57.84%), and female respondents were 43 people (42.16%).The age distribution of respondents is dominated by those aged over 35 years with 34 people (33.33%), followed by ages 26-30 with 24 people (23.53%), and ages 20-25 and 30-35 with the same number of respondents 22 people (21.57%).The main respondent's education level is undergraduate (S1), with a total of 61 people (59.80%).The second level of education is the diploma (D3) with a rating of 17 (16.67%).Most of the respondents who took part in this study were domiciled in the province of Lampung, 59 people (57.84%) and 31 people from Jabodetabek (30.39%).Although not significantly contributed, there were several respondents who came from other areas such as West Java, East Java, North Sumatra, and North Sulawesi.The domicile of the respondents is only used as demographic data, while this study includes respondents who have a work background as tax consultants and workers in companies who are responsible for reporting corporate taxes.

Results and Discussion
This study uses a structural equation modeling approach based on partial least squares or SEM-PLS to test the proposed hypothesis.Prior to the analysis, a descriptive analysis of the respondents' answers is presented, including the outer loading value of each indicator (question) as one of the validity parameters.Most of the respondents' answers have a median value between 4 and 5. ).Some of these indicators include FC2, FC3, and PR3.To meet the convergent validity aspect, the simulation process is carried out with the aim of eliminating indicators that have an outer loading value of less than 0.70.This is important to do to show that the indicator can measure the variable in question.
The simulation process produces FC2, FC3, FC5, FC6, FC7, and PR3 indicators, which need to be included in the model.After releasing these indicators, all of the values of the outer loading were more than 0.70.After the outer loadings, the next evaluation of convergent validity is to look at the average variance extracted (AVE) value.The assessment criteria are the AVE value of the variable must be more than 0.50.Based on Table 2, all the AVE values of the variables have been more than 0.50 as a sign that the convergent validity aspect has been completely fulfilled.2, it can be seen that all variables have values on the three reliability parameters of more than 0.70, so it can be concluded that all variables have met the reliability aspect.Based on the results of this study, it can be seen that the use of e-SPT as a digital tax system can be supported by social influence because people's attitudes will slowly be influenced to follow the use of e-SPT for tax payments.In addition, there is a need for facilitating conditions that can help the community to implement behavioral intentions in the use of e-SPT.Facilitating conditions can also support effort expectancy, where e-SPT can be a solution for implementing a digital tax system that makes it easier for the community.Perceived risk also supports attitude patterns because people will estimate the opportunities and risks from using e-SPT as tax payments, which will also support people's behavioral intention to use e-SPT.

Conclusion
Based on the test results in this study, it was concluded that 5 of the 7 hypotheses proposed were significant.Performance Expectancy and Effort Expectancy, based on the data obtained, did not significantly affect Attitude.For respondents, the benefits offered by the E-SPT 21/26 application, such as aspects of efficiency, effectiveness, and performance improvement, did not affect the tendency to use the E-SPT application.Also, the ease of use aspect represented by the user manual and the relatively low cost are also not significant in encouraging the use of the E-SPT application.What is significant in encouraging the use of the E-SPT application are environmental influences, incentives to fulfill tax obligations, and risk aspects that can be more suppressed.Attitude, which is significantly influenced by the variables of Social Influence and Perceived Risk, has the strongest and greatest influence on Behavioral Intention.This shows that the intensity of the use of E-SPT in this study is strongly influenced by the benefits obtained by users in using it.Users who have a good understanding of using the application and who find it useful will use E-SPT more often and tend to recommend it to other parties.

Table 1 .
Descriptive analysis and outer loading indicators

Table 2 .
The results of testing the validity and reliability of variables

Table 4 .
Hypothesis testing results -stat value of 5.670 (p-value <0.05).Thus, Hypothesis 5 is accepted, which means that Facilitating Conditions have a significant effect on Effort Expectancy.Hypothesis 6, the relationship between PR and AT is positive and significant with a tstat value of 2.048 (p-value <0.05).Thus Hypothesis 6 is accepted, which means Perceived Risk has a significant effect on Attitude.Hypothesis 7, the relationship between AT and BI is positive and significant with a t-stat value of 15.482 (p-value <0.05).Thus, Hypothesis 7 is accepted, which means that Attitude has a significant effect on Behavioral Intention.