Analysis of E-learning user Acceptance using the Technology Acceptance Model (TAM) and end-User Computing Satisfaction (EUCS)

This research aims to analyse the acceptance of E-Learning among students of Universitas Informatika dan Bisnis Indonesia by using Technology Acceptance Model (TAM) and End-User Computing Satisfaction (EUCS) approaches, which are often used by researchers to examine user acceptance and satisfaction with technology. The results of this study indicate that the influence between the variables Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Content, Accuracy, Format, Timeliness, Ease and User Satisfaction obtained a total value of 29,140 and on the continuum line shows that it is in the Very Good category. The results in this study also prove that there are 6 (six) accepted hypotheses and 3 (three) hypotheses that are not accepted. This result can be used as a suggestion for E-Learning Universitas Informatika dan Bisnis Indonesia to evaluate shortcomings in user

This research aims to analyse the acceptance of E-Learning among students of Universitas Informatika dan Bisnis Indonesia by using Technology Acceptance Model (TAM) and End-User Computing Satisfaction (EUCS) approaches, which are often used by researchers to examine user acceptance and satisfaction with technology. The results of this study indicate that the influence between the variables Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Content, Accuracy, Format, Timeliness, Ease and User Satisfaction obtained a total value of 29,140 and on the continuum line shows that it is in the Very Good category. The results in this study also prove that there are 6 (six) accepted hypotheses and 3 (three) hypotheses that are not accepted. This result can be used as a suggestion for E-Learning Universitas Informatika dan Bisnis Indonesia to evaluate shortcomings in user satisfaction, as well as maintaining existing quality.

INTRODUCTION
user acceptance of new technology, namely factors that lead to ease of use (Perceived ease of use) and benefits that can be seen (Perceived usefulness). These two variables can explain aspects of user behaviour. The conclusion is that the TAM model can explain that the user's perception will determine his attitude towards the benefits of using Information Technology.
The model used next is End User Computing Satisfaction (EUCS), which is a model for measuring the level of user satisfaction of an information system. EUCS was proposed by Doll and Torkzadeh in 1998. In measuring the level of user satisfaction, there are five factors that can present user satisfaction. The five factors are content, accuracy, format, timeliness and ease. The object of this research is all students of Universitas Informatika dan Bisnis Indonesia. Previous TAM and EUCS research has been conducted by several researchers on the application of different technologies to test the accuracy of TAM and EUCS. The research is about Satisfaction Analysis of E-Learning Usage Using Technology Acceptance Model and End User Computing Satisfaction.

LITERATURE REVIEW
Information and communication technology has become one of the most important aspects of human life. No exception in the world of education where the use of information technology is a factor that can improve the quality of education. The occurrence of the coronavirus (COVID-19) pandemic in early 2020 has had a major impact on community activities, ranging from health, economy, social and education. The impact of the coronavirus in the world of education can be seen in the policies of the central and regional governments to provide policies to close all educational institutions ranging from early childhood education, primary and secondary schools to universities. This policy makes the world of education implement a distance learning system so that the process of learning activities can continue. Distance or online learning is a form of technology utilisation, where learning uses internet access to solve various tasks given by educators.

METHODOLOGY
The research stage is a process that will be carried out in conducting research in a structured manner using a method. The method used also goes through several stages such as literature study, describing problems, creating models and questionnaires, and analyzing existing data. The following research steps are described with a flowchart scheme as shown in Figure 1.

Pupulation & Sample.
Population is a collection of data that identifies phenomena [18]. A population with a certain number is called a finite population while a population that has an infinite number is called an infinite population [19]. It can be concluded that population is everything contained in the object of research, which is useful as a source of data in a study. Based on the description above, the population in this study are students of Universitas Informatika and Bisnis Indonesia who use E-Learning. According to sudre et al. [20] the sample is part of the number and characteristics of the population. Thus, the sample is not a population, but an estimate of the population. A sample must be planned as well as possible so that each element in the population can have the same opportunity because it will be selected as a sample whose chance value is not equal to zero. In determining the sample, Steve et al [21] suggests that the appropriate sample size in research is between 30 and 500. In this study, the sample size was selected through the population of E-Learning users of Universitas Informatika dan Bisnis Indonesia.

Variable Identification
The variables used in this study are as follows, Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Content, Accuracy, Format, Timeliness, Ease and User Satisfaction. From these variables, indicators can be described in measuring each variable and can be seen as in the following table 1.

Validity And Reability Testing
Validity testing is used to measure whether a questionnaire is valid or not. An instrument that is valid or valid has high validity. Conversely, a less valid instrument means it has low validity. If the instrument is said to be valid, it means that it shows that the measuring instrument used to obtain the data is also valid, so that it is valid in this case it means that the instrument can be used to measure what should be measured in a study. For testing the validity of the construction is done by factor analysis, namely by correlating between the instrument item scores with the Pearson Product Moment formula as follows (1). This part represents the product of the differences between each x value and its mean x and each y value and its mean y in each data pair. ∑ = ( − ̅) , ∑ = ( − ̅) These are the sum of squares of the differences between each x value and its mean ̅ and each y value and its mean ̅ across all data pairs. √∑ = ( − ̅) ∑ = ( − ̅) This part calculates the square root of the product of the two sums of squares mentioned above.
Reability testing is a tool to measure a questionnaire which is an indicator of a variable or construct. The reliability test can be used to measure the consistency of the measurement results of the questionnaire [28]. Reliability (reliability) comes from the word "reliable" which means trustworthy. Reliability is actually a tool for measuring a questionnaire which is an indicator of a variable or construct. A questionnaire can be said to be reliable if a person's/respondent's answer to a statement is consistent or stable over time. Reliability refers to an understanding that an instrument can be trusted enough to be used as a data collection tool because the instrument is good. Reliability points to the level of reliability of something [29].

Multi Linier Regression
Regression analysis consists of simple regression and multiple regression. Multiple Regression Analysis is the development of simple regression analysis. Its purpose is to predict the value of the dependent variable (Y) if the independent variable is at least two or more [30]. Multiple regression analysis is an analytical tool for forecasting the value of the effect of two or more independent variables on the variable. The number of independent variables studied is more than one, so it is said to be multiple regression. The relationship between these variables can be characterized through a mathematical model called a regression model.

RESEARCH RESULT AND DISCUSSION
The results of this study are part of the results of a study conducted based on information or data that has been collected as a result of the methodology applied. Which in this study is data processed through respondents through questionnaires as the data source.

Validity Test Results
The research questionnaire was organized into 9 (nine) groups according to the number of variables, with a total of 45 items. All questionnaire questions are on a Likert scale. An instrument is said to be valid if the research instrument is able to measure the variables of Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Content, Accuracy, Format, Timelines, Ease, User Satisfaction on the use of E-Learning technology in conducting the lecture process at Universitas Informatika dan Bisnis Indonesia. Validity testing in this research is done if r count > r table then the instrument is valid and vice versa if r count < r table then the instrument is invalid. The number of initial samples used in this validity and reliability test is 20 samples. From the test data and calculations with SPSS, the data obtained are as in the following table 2. Based on the table above, it can be seen that the correlation value of each statement item is greater than r table = 0.195. Based on this description, the results of this test identify that all statement items submitted on 9 variables produce valid status and are suitable for use as measuring instruments for research and can be analyzed at the next stage.

Reliability Test Results
The reliability test is carried out on items that have been declared valid. A variable is said to be reliable or reliable if the answers to questions or statements are always consistent. The reliability test was carried out using Cronbach Alpha. The results of the reliability analysis can be seen in the output of the SPSS program and shown the amount of alpha value (α). Decision making on the reliability of answers to a variable is determined with the assumption that if the Cronbach alpha value> 0.70 then the question items on the variable under study are reliable. The table 3 below is the result of the reliability test of the variables in this study.

Analysis of Respondents' Responses to E-Learning
To find out what responses are received from respondents regarding E-Learning applications, data analysis is carried out from the results of distributing questionnaires that have been distributed to respondents who use E-Learning and obtained 150 people. The statements contained in the questionnaire consist of 45 statements. The following are the results of questionnaire processing regarding the acceptance of E-Learning based on respondents' responses presented in the form of a frequency table on each statement as follows:

A. E-Learning Acceptance Refers to the Perceived Ease of Use Variable
Based on data processing, it can be seen that respondents provide statements about the use of E-Learning applications that refer to Perceived Ease of Use with each indicator which will be explained based on the processing results as follows: The indicator of easy to understand in use shows an Agree statement is in the highest position, which is 64.7%, while other indicators show low numbers. This shows that the easy to understand indicator has been applied to E-Learning. Flexible indicator shows Agree statement is in the highest position, which is 48%, while other indicators show low numbers. This shows that flexible indicator has been applied to E-Learning. Accelerate work indicator shows Agree statement is in the highest position, which is 59.3%, while other indicators show low numbers. This shows that the indicator of speeding up work has been applied to E-Learning. The user friendly indicator shows that the Agree statement is in the highest position, which is 53.3%, while other indicators show a low number. This shows that user friendly indicator has been applied to E-Learning. The indicator of making lecture interaction easier shows that Agree statement is in the highest position, which is 54%, while other indicators show low numbers. This shows that the indicator of facilitating lecture interaction has been applied to E-Learning.

B. E-Learning Acceptance Refers to the Perceived Usefulness Variable
Based on the results of data processing, it can be seen that respondents provide statements about the use of E-Learning applications that refer to Perceived Usefulness with each indicator which will be explained based on the processing results as Indicators supporting lectures show that the Agree statement is in the highest position, which is 65.3%, while other indicators show low numbers. This shows that the indicator of supporting lectures has been applied to E-Learning. The indicator of increasing efficiency shows that Agree statement is in the highest position, which is 53.3%, while other indicators show low numbers. This shows that the indicator of increasing efficiency has been applied to E-Learning. The indicator of increasing effectiveness shows that Agree statement is in the highest position, which is 51.3%, while other indicators show a low number. This shows that the indicator of increasing effectiveness has been applied to E-Learning. The indicator of making work/task easier shows that Agree statement is in the highest position, which is 52.7%, while other indicators show low numbers. This shows that the indicator of making work/task easier has been applied to E-Learning. Indicator of usefulness in providing information shows that Agree statement is in the highest position, which is 57.3%, while other indicators show low numbers. This shows that the indicator of usefulness in providing information has been applied to E-Learning.

C. E-Learning Acceptance Refers to the Variable Attitude Toward Using
Based on the results of data processing, it can be seen that respondents provide statements about the use of E-Learning applications that refer to Attitude Toward Using with each indicator which will be explained based on the processing results as The indicator of making users happy shows that the Agree statement is in the highest position, which is 63.3%, while other indicators show low numbers. This shows that the indicator of making users happy has been applied to E-Learning. User desire indicator shows Agree statement is at the highest position, which is 49.3%, while other indicators show low numbers. This indicates that the user desire indicator has been applied to E-Learning. Good idea indicator shows Agree statement is in the highest position, which is 58.7%, while other indicators show low numbers. This shows that good idea indicator has been applied to E-Learning. The indicator of maintaining a positive attitude shows that Agree statement is in the highest position, which is 58%, while other indicators show a low number. This shows that the indicator of maintaining a positive attitude has been applied to E-Learning. The indicator of positive impact shows that Agree statement is in the highest position, which is 60.7%, while other indicators show low numbers. This shows that the positive impact indicator has been applied to E-Learning.

D. E-Learning Acceptance Refers to Content Variables
Based on the results of data processing, it can be seen that respondents give statements about the use of E-Learning applications that refer to Content with each indicator which will be explained based on the processing results as Indicators in accordance with the needs show that Agree statement is in the highest position, which is 60%, while other indicators show low numbers. This shows that the indicator in accordance with the needs has been applied to E-Learning. Indicators are presented diversely shows that Agree statement is in the highest position, which is 55.3%, while other indicators show low numbers. This shows that the indicator presented diversely has been applied to E-Learning. The indicator of usefulness for lectures shows that Agree statement is in the highest position, which is 59.3%, while other indicators show low numbers. This shows that the indicator of usefulness for lectures has been applied to E-Learning. Good quality indicator shows Agree statement is in the highest position, which is 47.3%, while other indicators show low numbers. This shows that good quality indicator has been applied to E-Learning. Clearly presented indicator shows Agree statement is in the highest position, which is 50.7%, while other indicators show low numbers. This shows that the indicator presented clearly has been applied to E-Learning.

E. E-Learning Acceptance Refers to Accuracy Variable
Based on the results of data processing, it can be seen that respondents give statements about the use of E-Learning applications that refer to Accuracy with each indicator which will be explained based on the processing results as The accurate information indicator shows that the Agree statement is in the highest position, which is 56.7%, while other indicators show low numbers. This shows that accurate information indicators have been applied to E-Learning. Reliable information indicator shows Agree statement is in the highest position, which is 54.7%, while other indicators show low numbers. This shows that reliable information indicator has been applied to E-Learning. The appropriate output indicator shows that Agree statement is in the highest position, which is 60%, while other indicators show low numbers. This indicates that the appropriate output indicator has been applied to E-Learning. Standardized indicator shows Agree statement is in the highest position, which is 58%, while other indicators show low numbers. This indicates that appropriate output indicator has been applied to E-Learning. e. The overall indicator of accurate information shows that Agree statement is in the highest position, which is 56.6%, while other indicators show low numbers. This shows that the overall indicator of accurate information has been applied to E-Learning.

F. E-Learning Acceptance Refers to the Format Variable
Based on the results of data processing, it can be seen that respondents provide statements about the use of E-Learning applications that refer to the Format with each indicator which will be explained based on the processing results as Interesting indicators show that Agree statements are in the highest position, which is 58.7%, while other indicators show low numbers. This shows that interesting indicators have been applied to E-Learning. Easy to use indicator shows Agree statement is in the highest position, which is 55.3%, while other indicators show low numbers. This shows that easy to use indicator has been applied to E-Learning. Good information indicator shows Agree statement is in the highest position, which is 56.7%, while other indicators show low numbers. This shows that good information indicator has been applied to E-Learning. Good design and color indicator shows Agree statement is in the highest position, which is 57.3%, while other indicators show low numbers. This indicates that good design and color indicators have been applied to E-Learning. The overall interesting indicator shows that Agree statement is in the highest position, which is 58%, while other indicators show low numbers. This shows that the overall interesting indicator has been applied to E-Learning.

G. E-Learning Acceptance Refers to the Timeliness Variable
Based on the results of data processing, it can be seen that respondents give statements about the use of E-Learning applications that refer to Timeliness with each indicator which will be explained based on the processing results as Indicator of fast and precise information shows that Agree statement is in the highest position, which is 64%, while other indicators show low numbers. This shows that the indicator of fast and precise information has been applied to E-Learning. The indicator of current information shows that Agree statement is in the highest position, which is 57.3%, while other indicators show low numbers. This shows that the latest information indicator has been applied to E-Learning. Easy to download indicator shows Agree statement is in the highest position, which is 56%, while other indicators show low numbers. This shows that the easy to download indicator has been applied to E-Learning. The indicator of notification quickly shows that the Agree statement is in the highest position, which is 51.3%, while other indicators show a low number. This shows that quick notification indicator has been applied to E-Learning. Appropriate feedback indicator shows that Agree statement is in the highest position, which is 52%, while other indicators show low numbers. This indicates that the feedback indicator has been appropriately applied to E-Learning.

H. E-Learning Acceptance Refers to the Ease Variable
Based on the results of data processing, It can be seen that respondents give statements about the use of E-Learning applications that refer to Ease with each indicator which will be explained based on the processing results as Indicator of easy to understand feature shows Agree statement is in the highest position, which is 64.7%, while other indicators show low numbers. This shows that the easy to understand feature indicator has been applied to E-Learning. User friendly indicator shows that Agree statement is in the highest position, which is 58.7%, while other indicators show low numbers. This shows that the user friendly indicator has been applied to E-Learning. Flexible indicator shows Agree statement is in the highest position, which is 57.3%, while other indicators show low numbers. This shows that flexible indicator has been applied to E-Learning. Attractive format indicator shows Agree statement is in the highest position, which is 47.3%, while other indicators show low numbers. This indicates that the attractive format indicator has been applied to E-Learning. The indicator of easing the lecture process shows that Agree statement is in the highest position, which is 54.7%, while other indicators show low numbers. This shows that the indicator of easing the lecture process has been applied to E-Learning.

I. Acceptance of E-Learning Referring to the User Satisfaction Variable
Based on the results of data processing, It can be seen that respondents provide statements about the use of E-Learning applications that refer to User Satisfaction with each indicator which will be explained based on the processing results as The indicator of fulfilling needs shows that the statement of Agree is in the highest position, which is 63.3%, while other indicators show low numbers. This shows that the indicator of fulfilling needs has been applied to E-Learning. Efficient indicator shows that Agree statement is in the highest position, which is 59.3%, while other indicators show low numbers. This shows that efficient indicators have been applied to E-Learning. Effective indicator shows that Agree statement is in the highest position, which is 55.3%, while other indicators show low numbers. This indicates that effective indicators have been applied to E-Learning. Attractive format indicator shows Agree statement is in the highest position, which is 56.7%, while other indicators show low numbers. This shows that the interesting format indicator has been applied to E-Learning. The indicator of making lectures easier shows that Agree statement is in the highest position, which is 52%, while other indicators show low numbers. This shows that the indicator of facilitating lectures has been applied to E-Learning.

J. Normality Testing
The normality test aims to determine whether the value in the data distribution on a variable is normally distributed or not. Normality testing in this study uses the Normal Probability Plot. The normality test using the Normal Probability Plot (P-Plot) displays the results in the form of a histogram graph. The following is the basis for knowing whether a data can be said to be normal using P-Plot. If the data spreads around the diagonal line, and follows the direction of the histogram line or graph, then the data distribution can be said to be normally distributed. Conversely, if the data spreads far from the line, and does not follow the direction of the histogram line or graph, then the data distribution is said to be not normally distributed. Normality testing is very important to do as a first step in conducting various tests so that errors do not occur if normality is met. Because a good regression model is to have normally distributed residuals. The normality test can be seen in Figure 2.

K. Determination Coefficient Test
The coefficient of determination test is used to measure the suitability of multiple regression on data. If the adjusted R is higher, the better the regression model will appear. According to , the coefficient of determination serves to determine the extent to which all independent variables can explain the dependent variable. If the coefficient of determination is getting bigger, then the influence of the independent variable on the dependent is getting stronger. In this study, the coefficient of determination test used IBM SPSS 26 and the following are the results can be seen in table 5.

CONCLUSIONS AND RECOMMENDATIONS
Based on the results of research that has been conducted regarding the acceptance of E-Learning Universitas Informatika dan Bisnis Indonesia using the Technology Acceptance Model (TAM) and End-User Computing Satisfaction (EUCS) methods, we conclude that the Perceived Ease of use variable has a significant effect partially on Perceived Usefulness in the use of E-Learning Indonesian University of Informatics and Business. Perceived Usefulness variable has a partially significant effect on Attitude Toward Using on the use of E-Learning at the University of Informatics and Business Indonesia. The Perceived Ease of use variable has no significant effect partially on Attitude Toward using in the use of E-Learning at the University of Informatics and Business Indonesia. Content variable has a partially significant effect on Attitude Toward using in the use of E-Learning at the University of Informatics and Business Indonesia. Accuracy variable has a partially significant effect on Attitude Toward using in the use of E-Learning at the University of Informatics and Business Indonesia. Format variable has no significant effect partially on Attitude Toward using on the use of E-Learning of Indonesian University of Informatics and Business. Timeliness variable has a partially significant effect on Attitude Toward using on the use of E-Learning of Indonesian University of Informatics and Business. Ease variable has no significant effect partially on Attitude Toward using in the use of E-Learning at Indonesian University of Informatics and Business.. The Attitude Toward using variable has a partially significant effect on user Satisfaction in the use of E-Learning at the University of Informatics and Business Indonesia.

ADVANCED RESEARCH
Still doing further research to find out more about E-learning User Acceptance Analysis using the Technology Acceptance Model (TAM) and end-User Computing Satisfaction (EUCS)