Integration of UTAUT 2 and Delone & McLean to Evaluate Acceptance of Video Conference Application

— This article explores how college students adopt video conferencing software for distance education. This research aims to examine the factors that influence the spread of video conferencing programs in Indonesia. A video conferencing application is a multimedia program that generates audio and visual content to facilitate real-time, two-way communication between its users. Because of COVID-19, classes of all kinds are now being taken online. As a result, more people are turning to tools like video conferencing. Therefore, learning how to access student video conferencing software is crucial. The UTAUT 2 and Delone & McLean models will be integrated into the analysis. A total of 327 people answered the survey. Next, we used the PLS-SEM technique in smart pls 3.0 to analyze the data collected from the respondents. The R-Square value of 26.2% for the retention intent variable and 62.3% for the user satisfaction variable demonstrate that independent variables in the study can explain endogenous variables and that the remaining variance is influenced by factors external to the survey.


I. INTRODUCTION
At the beginning of March 2020, the spread of COVID-19 prompted all Indonesian universities to implement online learning systems utilizing video conferencing applications [1].
Video conferencing software facilitates online communication between teachers and students [2].
Because of this, services such as Zoom, Google Meet, Microsoft Teams, Google Classroom, and so on have become increasingly popular. Despite more available information on video conference app downloads, there is still a shortage of studies on the widespread use of such tools for online education [3]. Some of the problems found when using video conferencing applications, namely resources, technology and infrastructure costs that do not support and lack of technical support, are considered problems when using video conferencing applications [4] [5]. From some of these things, knowing how to accept video conferencing applications for online learning is essential.
Numerous research models have been constructed to determine the factors contributing to an application's success. The Unified Theory of Acceptance and Use of Technology and the Delone-McLean model are two of the most popular (UTAUT). UTAUT 2 is an updated version of the original model that considers three additional factors-hedonic motivation, price value, and habit-that influence users' propensities to take specific actions when interacting with a computerized system [6]. The model created by Delone and McLean in 1992 was revised in 2003.
Delone and McLean's model considers these six factors: data quality, system quality, service quality, intent to use, user satisfaction, and net benefits. It was found that bringing together the UTAUT and the Delone and McLean models provided a comprehensive explanation of user acceptance [7][8] [9].
This research aims to evaluate how students at State and Private Universities in Indonesia have adopted video conferencing applications for distance education. General rating based on the UTAUT 2 and Delone & McLean integration model. There have been multiple studies along these lines, including work by Alzahrani & Seth [1]. Using an amalgamation of the Delone & McLean and TAM models, they analyzed LMS users' perspectives on satisfaction and future sustainability in the United Kingdom. COVID-19 data shows that student satisfaction is more strongly influenced by factors like the quality of the information provided and the student's sense of competence than by the quality of the learning management system itself. Furthermore, the findings indicate that prior experience and social influences, but not self-efficacy or user satisfaction, influence an individual's expectations of outcomes. The results of this study also provided new tools that developers of learning management systems could use to attract more participants to their plans during COVID-19. information quality, and service quality all play a role in determining how satisfied they are with the app. As a result, the overall gain has shifted since then. It's safe to assume that students widely adopted the zoom app for distance learning during the COVID-19 timeframe. Users are more content with an information system if they have faith in it [11]. More system development on the zoom application must be carried out, such as the level of security and privacy of users who are still vulnerable to hacker attacks. This causes the need for more investment in the development of zoom applications to the fullest [12].
Studying how people ranked different information systems, Sorongan [13] [14] using SmartPLS 3.0 and the PLS-SEM processing method, based on the UTAUT 2 model, assessed the extent to which students in Jakarta adopted the Gmeet messaging app. This research results that the Gmeet application is successfully used for online learning, which can be seen from performance expectations, social influences, hedonic motivation, habits, and user interests.
Sarosa [15] also researched the application system's acceptability using the UTAUT model.
Students' acceptance of iPads is analyzed at a university. Methods from the Structural Equation Model and the Partial Least Squares were used in the analysis. The findings indicate that only anxiety and self-efficacy are associated with intent to use. However, iPad use is affected by both user intent and the surrounding environment. Gender plays a moderating role in the correlation between self-efficacy and plans to use. Knowing how to use the iPad well can make a difference in the strength of the link between intention and action. Ramadan et al. [16] also evaluated an ERP system embedded in a PC  [20] is required to assess both user acceptance and the overall success of an information system. The UTAUT 2 model and the Delone and McLean model complement each other well when evaluating the success and acceptance of an information system, as shown in studies [21], [22], and [23]. This study will integrate the UTAUT 2 and Delone and McLean models by looking at the topic from the perspective of those who utilize video conferencing tools.

II. RESEARCH METHOD
Google form, Instagram, WhatsApp, Line, Microsoft Excel, and the SmartPLS application were used to collect, organize, and analyze the data for this study; in addition, we will use Partial Furthermore, the material needed in this study is respondent data, namely students from public and private universities who use video conferencing applications for online teaching and learning.
This research was conducted quantitatively by processing the results of a Likert scale questionnaire so that the data generated was in the form of numbers. The data needed include demographic data and data on respondents' statements. Information collected included The proposed model used in this investigation is depicted in Figure 1 and is an amalgamation of the UTAUT 2 and Delone & McLean models.   Table 1. The latent variables in this research are as follows: The variable performance expectation is stated in Table 1. TAM's usefulness variable is linked to users' hopes that the system will boost their efficiency, measured by their performance expectancy [23].

EE1
In my opinion, how to use video conferencing applications is easy to learn and understand EE2 During the current COVID-19 pandemic, it is simple to communicate with professors and friends via the video conferencing app.

EE3
The video chat program's language is straightforward, in my opinion.

EE4
In my opinion, the features available in the video conferencing application are easy to use

EE5
In my opinion, the video conferencing application interface is easy to understand An explanation of the work expectancy variable is provided in Table 2. The effort expectancy is based on the system's performance as a result of the effort, any resulting imbalance, and the ease with which the system can be operated or used [24].  The price value in Table 4 is the user's perception of the costs incurred in using information systems for the benefits obtained [6].  Table 5, habit is the level of users using information systems automatically (because of learning), and it is a predictor of intention and use of technology [6].  Table 6 is a statement of the information quality variable. Information quality refers to the information provided by the video conferencing application to users and whether users get clear and understandable information. The quality of the information provided is often cited as a significant predictor of customer happiness [22].  Table 7 is a statement of the system quality variable. The system quality variable is a combination of hardware and software in a system and focuses on system performance and refers to how well the capabilities of the hardware, software, policies, procedures, and designs are permanently attached to the system itself [26].

SyQ1
The response of the video conferencing application to users is fast, according to what I asked for

SyQ2
The video conferencing application provides facilities to contact a technician (help desk) quickly if there is a problem with the application SyQ3 I feel safe using video conferencing applications for online learning because each user has a different password Service quality provides an overview of the quality of the services provided in accordance with the user's perception or point of view when using information systems [26].

US1
In the wake of the recent COVID-19 pandemic, I realized the importance of using video conferencing tools to support educational initiatives.

US2
The educational goals of the video conferencing application are consistent with the need to facilitate online education during the COVID-19 pandemic.

US3
Overall, I am satisfied with using video conferencing applications for online teaching and learning purposes US4 In my opinion, using an application for online teaching and learning as a substitute for lectures in class during the COVID-19 pandemic is a good idea Based on Table 9, User satisfaction is a response in the form of feelings of pleasure and satisfaction from users in using information systems [21].

CI1
After the COVID-19 pandemic ends, I will continue to use video conferencing applications regularly CI2 I will continue to use video conferencing applications as I do now

CI3
If the COVID-19 pandemic is over, I will suggest that my friends continue using the video conferencing application to discuss the material studied in class.
The use of continuity intention variables to determine the sustainability of the use of an information system influences the acceptance and success of an information system [27]. Table 10 is a statement of the continuance intention variable.

III. RESULT AND DISCUSSION
Validate the data, it takes profile data of respondents who are students who use video conferencing applications in Table 11. Respondents in this study amounted to 327 people who came from students of various ages and students who lived in 25 provinces. Respondents in this study were also students with different educational levels, namely D3, D4/S1, S2, and S3. As well as in online learning activities, students used several other video conferencing applications such as google classroom, google meet, ms teams, and zoom.
It was testing on the outer aims to determine the regression value of a latent variable with its indicators by using two tests, namely validity and data reliability.

Data Validity Testing
When evaluating a questionnaire's efficacy as a research tool, validity testing employs convergent and discriminant validity. The outer loading and AVE values are compared first to ensure concurrent validity.  Table 12 shows that an outer loading value greater than 0.5 indicates a pass in the concurrent validity test. Similarly, the external loading value of 0.497 suggests that the H4 indicator stating that users have used video conferencing applications before has a high degree of reliability.
Consequently, the H4 indicator should not be relied upon as a reliable way to gauge the habitual variable. This is why we aren't using the H4 indicator as part of our measurement model for this research. Thirty-nine more indicators make up the measurement model and are listed in Table 13.    The AVE square root value in the latent variable has a higher value than the correlation between other variables, so the results in Table 15 are supported by the discriminatory validity testing in Table 16. Therefore, the discriminant validity generated in this study is of high quality and is considered applicable.

Data Reliability Testing
Cronbach's alpha and composite reliability > 0.7 are used to assess the precision, consistency, and accuracy with which indicators measure the underlying variables. Analysts turn to inner model analysis to foretell how latent variables are connected. The internal model can be tested in three ways: by using the R-Squared statistic, the Q-Squared statistic, or by testing the null hypothesis. Q-Square test: > 0 indicates predictive, 0 means not predictive; R-Square test: 0.67 or higher indicates strong, 0.33 or higher indicates moderate, and 0.19 or lower indicates weak. In addition, the P-Values, T-Statistics, and Original Sample values for hypothesis testing are generated through a bootstrapping procedure. The recommended study uses a 5% significance level of error for P-values. The T-Statistic is said to be significant if the resulting value is > T- Table (T-Statistic 1.96) and not significant if the resulting value is < T- Table. Testing the relationship between latent variables will show a positive influence relationship between variables if the Original Sample value is> 0 and negative between variables if it < 0.  This study shows that the video conferencing application has succeeded in meeting user expectations regarding performance expectancy, as seen from H1. Students believe that online teaching and learning video conferencing applications benefit and improve their learning performance. Nonetheless, the study results show that H2 is incorrect and that user satisfaction with video conferencing applications is unrelated to users' effort expectancy. This is because students must exert much effort when using video conferencing programs in the classroom.
In addition, students also feel that the infrastructure for video conferencing applications does not support online learning activities such as networks, Wi-Fi, internet, technology, and university assistance, which can be seen from the rejection of H3. H4 was rejected in this study because students felt that using video conferencing applications for online studying requires no small cost to purchase internet or Wi-Fi quotas compared to when students learn directly from class. The charge is essential because students themselves must facilitate supporting media used in teaching and learning activities.
Conversely, the accepted H5 suggests that routine positively and significantly impacts user happiness. At the same time, all students at State and Private Universities were mandated to use video conferencing applications for online study during the COVID-19 pandemic, leading to an increase in the intensity of the use of video conferencing applications and their continuous service, which made it a natural thing and accustomed students to using them.
In addition, H6 was accepted because students felt that the information provided by the video conferencing application followed student expectations, such as the information provided was clear, accurate, and always presented up to date. However, students felt that the system's quality was not a determining factor for satisfaction because the performance of the video conferencing application was not in line with student expectations, which made H7 rejected. On the other hand, the services provided by the video conference application affect user satisfaction because the quality of the video conference application follows student expectations.
This study also shows that the video conferencing application is successful and can be well received by students for online teaching and learning. The highest T-statistic of 10,890 indicates that users' satisfaction positively affects their intent to keep using the service, supporting Hypothesis 9. Suppose students are happy with the results of using video conferencing applications. In that case, they are more likely to use them again in the future, which is why user satisfaction plays a crucial role in the evolution of an information system.

IV. CONCLUSION
The study only confirmed five of the nine hypotheses tested while disproving the other four.
The factors that affect whether or not a user will keep using a video conferencing app are the app's ability to meet the user's needs, the user's familiarity with the app, the user's habits, the quality of the information provided, and the quality of the User satisfaction is positively correlated with effort expectancy, enabling conditions, price value, and system quality; however, the correlation is weak. The study results show that those who use video conferencing applications are interested in doing so again in the future for educational purposes, suggesting that the applications are well received and provide a satisfactory experience for their users.
The study results back up the researcher's suggestion to increase the scope of the survey. This study's survey data were primarily collected from Java-based students; ideally, future research will access a more globally dispersed sample of respondents. The timing of this study, conducted while students were required to use video conferencing applications due to the COVID-19 pandemic, set the stage for subsequent research to be completed after the end of the pandemic, with revised research designs and additional factors.