Electronic Receipt of Document Control System using Technology Acceptance Model
Frieyadie1, Faisal Muharam2,*
Fakutas Teknologi Informasi, Sistem Informasi, Universitas Nusa Mandiri, Jakarta, Indonesia Email: 1frieyadie@nusuamandiri.ac.id, 2,*faisal.muharam@voksel.co.id
Correspondence Author Email: faisal.muharam@voksel.co.idm Submitted 28-03-2023; Accepted 30-04-2023; Published 30-04-2023
Abstract
The document control system in a company is the company's effort to provide a means to find information and documents related to the company. Implementing a manual system for the documentation system (still in the form of physical paper stored in document shelves/cabinets) takes a long time in the work process, making it difficult for the employee in charge to control the document. The variables used in this study are the ease of use and effectiveness using the Technology Acceptance Model (TAM) method. In collecting the data, the researchers made observations, interviews, literature studies, and questionnaires. Of the 273 population of employees using the document control system, a sample of 73 correspondents was taken based on the formula. Sampling using a simple random sampling technique. The data analysis method used is quantitative analysis with multiple linear regression analysis. In calculating the data, researchers used the SPSS data processing application version 27. Based on the results of the study, it was found that 13.5% of employees accepted the existence of electronic document control technology based on the ease and effectiveness of the electronic document control system. The results of the three hypotheses tested found that two hypotheses were accepted and 1 hypothesis was rejected.
Keywords: Electronic Document Control; System Acceptance; Technology Acceptance Model (TAM)
1. INTRODUCTION
Information systems and technological advances are critical [1] in supporting everyone's activities. Because information systems and technology can simplify and speed up [2] activities and time efficiency [3]. The development of information has now changed in the digitalization era, namely information that has changed from traditional and simple management to computer technology. The main reason for using information technology in a business is to support information processing tasks [4]. Information processing tasks include capturing, conveying, creating, storing, and communicating [5]. The development of information technology and systems is needed to support the operational activities of receiving information faster in the industrial world at PT. Voksel Electric Tbk ensures validation, identification, revision and controlled destruction of organizational documents, required documentation and document control procedures. These requirements can become incredibly inconvenient for companies with complex products and interacting processes if the organization's standard procedures are revised frequently. Another obstacle is often having problems distributing documents, which takes a relatively long time. The impact of the unkindness will drop the company's performance and reputation so that clients do not trust it. However, information technology is utilized to create a document control system that is more practical and easy, which promises accurate and real-time information distribution without being influenced by the location of resources and users.
Documents are essential because vital information is in them, so proper management is needed [6]. PT Voksel Electric Tbk is an Indonesian company engaged in the cable industry. With continuous and measurable efforts to achieve superior quality, the company uses the ISO 9001:2015 quality management system, which requires documented document/information control.
PT Voksel Electric Tbk previously also implemented a manual system [7] For the documentation system (still in the form of physical paper stored in a document shelf/cabinet), so it takes a long time to process [8]. But with advances in technology and paper-saving programs for nature's preservation. Requires companies to implement Electronic Document Control [9] to facilitate document search, document validation, and document revision and deletion purposes.
According to [10], several advantages of electronic document control: 1) Discovery and presentation of information that is processed thoroughly and quickly, 2) Access and use of multi-user information or more than one user simultaneously.
3) Information storage is more centralized, and 4) Storage has high accuracy.
In previous research on the use of TAM that was compiled, including research from Aprilianti and Ilham in 2022 [11], many obstacles occurred in combining conventional learning processes with learning processes using eLearning. In addition to unsupported infrastructure such as free wifi, which is sometimes unstable and not properly connected, slow internet speed, and limited laboratory conditions because computers and internet devices do not fully support learning.
The results of his research combine the Unified Theory Of Acceptance And Use Of Technology (UTAUT) and Technology Acceptance Model (TAM) approaches according to the characteristics of the existing problems. Research by Sofyan et al. [12] in 2018 found that the E-KTP service still had problems, including population data errors, officers only distributed E-KTPs, and activation was carried out at a later date so that residents living far from the office were reluctant to activate, and in the process of receiving KTPs often takes quite a long time, from weeks to months.
The result is that electronic information systems are pretty effective in population administration services. Gap analysis can be taken and seen from three dimensions as measured by three indicators, namely 1) perceived benefits for
employees can facilitate work and improve performance and high work productivity, 2) ease of use where employees can operate computers and information and communication technology devices efficiently, and 3) acceptance of information technology for employees.
The objectives of this research include finding and presenting information that is processed quickly and thoroughly. It can also be accessed and used by multiple users or more than one user simultaneously. So that information storage and control become centralized.
This study aims to analyze and measure the ease and effectiveness of using electronic document control systems and how much employee acceptance of electronic document control systems is.
2. RESEARCH METHODOLOGY
2.1 Research Stages
Based on the approach, there are generally two types of research: quantitative and qualitative. In this study, the author uses a quantitative approach to measure the acceptance of use in terms of effectiveness, convenience, and user attitudes towards electronic document systems at PT. Voksel Electric Tbk. Based on a predetermined approach, the research stages consist of several stages. The first stage is to conduct a literature study on electronic document control at PT. Voksel Electric Tbk as a medium for documenting company documents and Technology Acceptance Model (TAM) methods to be used. Figure 1 flowchart of research stages as follows:
Figure 1. Flowchart of Research Stages
The following is an explanation of Figure 1, which has several stages of the activities carried out in this study. The first stage of problem identification is how to identify problems that occur at PT. Voksel Electric Tbk. The second stage of the Problem Statement is formulating the identified problem to become more apparent. The third stage is purpose and scope, which determines the research objectives and scope so that it becomes more focused in this research. This study's fourth data collection stage collects related data needed for research. The fifth stage is making a questionnaire by filling out a Likert scale. The first filling stage is ease of use, the second is effectiveness, and the third is an attitude—the sixth stage with data processing with the TAM method. The seventh stage is to get the data processing results using the TAM method, and the last stage is to get conclusions and suggestions from the research.
The literature study results will be the basis for conducting an analysis. The second stage is to collect data. At this stage, they are creating a questionnaire with the help of Google Forms as a data measurement tool. PT. Voksel Electric Tbk provides questionnaires specifically for users of electronic document control systems. The third stage is to analyze the data on the questionnaire results using the help of SPSS software. The last stage is to conclude the results of the data analysis.
A research instrument is a written guideline on interviews, observations, or a list of questions prepared [13] to obtain information from respondents. The instrument is called the Observation Manual, Interview Manual, Questionnaire, or Documentary Guideline, according to the method used [14]. In this case, the author needs to compile an instrument preparation design by making constructs that affect the acceptance of the electronic document control system at PT.
Voksel Elektric Tbk. These constructs include the perception of ease of use, effectiveness and user attitude. The indicators for measuring each oldest construct are in table 1 below:
Table 1. Research Instruments No Research Variables Code Indicators
1 Perceived Ease of Use (Convenience) X1.1 1. Ease of accessing documents X1.2 2. Ease of uploading documents X1.3 3. Ease of downloading documents X1.4 4. Ease of requesting documents
X1.5 5. Ease of accessing the information on Internal and External Audit activities
X1.6 6. Ease of document approval
2 Perceived Usefulness (Effectiveness) X2.1 1. Speed up submission of new documents X2.2 2. Speed up document revision
X2.3 3. Accelerate document obsolescence
X2.4 4. Speed up obtaining document history information X2.5 5. Performance
3 Behavioural Intention to Use (Attitude)
Y1.1 1. Fine Y1.2 2. Fast
Y1.3 3. Like using E-doc Y1.4 4. Enjoyable
Table 1 contains research instruments that have three main variables, namely Perceived Ease of Use (Convenience), Perceived Usefulness (Effectiveness), and Behavioural Intention to Use (Attitude)—provision of all code indicators to facilitate assessment.
2.2 Data Collection Methods
This study took a sample of 73 respondents of permanent employees who use electronic document control systems at PT.
Voksel Electric Tbk. Research using a questionnaire using a Likert scale. Table 2, Table 3, and Table 4 is Questionnaire data recap.
Table 2. Convenience Questionnaire (X1)
Respondent No. X1.1 X1.2 X1.3 X1.4 X1.5 X1.6 X1 Total
1. 4 4 4 4 4 3 23
2. 4 4 3 5 5 5 26
3. 4 4 4 5 5 4 26
4. 4 3 3 3 3 3 19
5. 4 4 5 5 5 4 27
… … … …
… … … …
71. 4 5 4 4 5 5 27
72. 5 4 5 4 4 4 26
73. 4 4 5 5 5 4 27
Table 2 displays the results of filling out the Perceived Ease of Use (Convenience) questionnaire, with 73 respondents and as many as six instruments. In this case, not all respondents are displayed, only the top five respondents and the bottom three respondents.
Table 3. Effectiveness Questionnaire (X2)
Respondent No. X2.1 X2.2 X2.3 X2.4 X2.5 X2 Total
1. 4 4 4 4 4 20
2. 5 4 3 3 4 19
3. 4 4 3 3 3 17
4. 4 4 4 4 4 20
5. 5 4 4 5 4 22
… … … …
… … … …
71. 5 4 5 5 4 23
72. 4 3 5 4 4 20
73. 4 5 5 4 3 21
Table 3 displays the results of filling out the Perceived Usefulness (Effectiveness) questionnaire, in which there were 73 respondents, and as many as five instruments. In this case, not all respondents are displayed, only the top five respondents and the bottom three respondents.
Table 4. Attitude Questionnaire (Y)
Respondent No. Y1.1 Y1.2 Y1.3 Y1.4 Y Total
1. 4 4 4 4 16
2. 4 3 4 3 14
3. 5 4 3 4 16
4. 5 5 5 5 20
5. 4 4 4 4 16
… … … …
… … … …
71 4 4 5 4 17
72 4 4 5 5 18
73 4 4 5 5 18
Table 4 displays the results of filling out the Behavioural Intention to Use (Attitude) questionnaire, in which there were 73 respondents and as many as four instruments. In this case, not all respondents are displayed. Only the top five respondents and the bottom three respondents.
2.3 Population Research
The research population used in this study amounted to 273 permanent employees who used an electronic document control system at PT. Voksel Electric Tbk. According to [16], how to determine the number of sample elements/members of a population using the Slovin Formula.
𝑛 = 𝑁
1+(𝑁×𝑒2) (1)
Information:
n = number of sample elements/members
N = number of elements/members of the population
e = Error level (note: generally used 1% or 0.01, 5% or 0.05, and 10% or 0.1. Error level can be selected by the researcher) The number of samples taken on the Slovin formula with an error level of 10%. As follows:
𝑛 = 273
1 + (273 × 0,12)= 73,19
Fulfilled to 73 respondents. So the number taken as a sample was 73 people 2.4 Data Analysis Methods
Data is information material about an object of research obtained at the research location [17]—analysis of data processing after collecting all data from respondents or other sources.
a. Linear Regression
This study uses quantitative analysis with multiple linear regression analysis, where two or more variables are interconnected. These variables are:
1. Independent variable, usually symbolized by variable X. Independent variable is a variable that affects other variables.
2. The dependent variable (bound) is usually symbolized by variable Y. Dependent variable is a variable that is influenced by another variable [18]
Before analyzing data using multiple linear regression formulas, it is necessary to test classical assumptions.
Classical assumption tests aim to determine the presence or absence of residual normality: multicollinearity and heteroscedastic on regression. Fulfilment of classical assumptions to obtain unbiased regression estimates and testing can be trusted. The primary objective in regression analysis is to infer the population's regression function based on the sample's regression function as precisely as possible. Regression equations measure employee attitudes toward accepting electronic document control systems.
To determine the effect of several independent variables on the dependent variable. Below is a general multiple linear regression formula that uses as follows:[19]:
𝑌 = 𝑎 + 𝑏1𝑥1+ 𝑏2𝑥2+ ⋯ + 𝑏𝑛𝑥𝑛 (2)
Information:
Y = Acceptance Attitude Variable (Acceptance Attitude Variable) X1 = Ease of Use Variable (Independent variable)
X2 = Effectiveness Variable (Independent variable)
a = Predicted value when the independent variable does not affect (Constant) b = value of increase/decrease (Regression Coefficient)
b. Validity Test
The Validity Test is a product of validity. Validation is a process carried out by the compiler or user of an instrument to collect data empirically to support the conclusions produced by the instrument score. At the same time, validity is the ability of a measuring instrument to measure its measurement goals [18].
The test criteria of the Validity Test are as follows [18]:
1. If r calculate > r table, with a significant level a = 0.05, then the research instrument is said to be valid 2. If r counts < r table, with a significant level a = 0.05, then the research instrument is said to be invalid c. Reliability Test
The concept of reliability is the extent to which the results of a measurement used remain reliable and free from measurement errors. At the same time, testing the instrument's reliability to determine whether the data produced is reliable or Tough [18]. The reliability test was obtained using Cronbach's Alpha test. Reliability tests are carried out with the following criteria:[18]:
1. The question is declared reliable if Cronbach's alpha score > a significant level.
2. The question is declared unreliable if Cronbach's alpha score < a significant level.
d. Residual Normality Test
The residual normality test in this regression model determines whether the residual values produced usually are distributed [21]. Here are some normality test methods used by the author in this study:
1. Chart Method
The normality test using the graph method is carried out by looking at the spread of data on diagonal sources on the graph Normal p-p Plot of Regression Standardized residual [21]
2. Kolmogorow-Smirnov One Sample Test Method
One Sample Kolmogorow-Smirnov Test determines whether the data distribution follows a regular, Poisson, uniform, or exponential distribution. Residuals are normally distributed if the significance value is more than the specified significance level value (e.g. 0.05)[22]
e. Multicollinearity Test
Multicollinearity is a high correlation between independent variables or with other independent variables—the multicollinearity test tests whether the regression model found a correlation between independent variables [23]. A good regression model should not correlate with independent variables. Compared to manual calculations, the multicollinearity test using VIF (Variant Inflation Factor) assisted by SPSS aims to make the calculation results accurate. In determining the correlation taken in the multicollinearity test, including;
1. H0: H0 is accepted if r square = VIF > a value of 10.0, then it can be concluded that multicollinearity occurs.
2. H1: H1 is accepted if r square = VIF < a value of 10.0, then it can be concluded that multicollinearity does not occur.
f. Heteroscedasticity Test
The heteroscedasticity test aims to test whether the regression model occurs or there is a variance from the residual one observation to another [21]. In this study, the author used two methods used to test heteroscedasticity, namely:
1. Scatter Plot Method
Kriteria dalam penilaian adalah sebagai berikut:
a) If there is a specific pattern, such as dots forming a particular regular pattern (wavy, widened, then narrowed), identification of heteroscedasticity,
b) If there is no clear pattern, and the points spread above and below 0 on the Y-axis, heteroscedasticity does not occur [23].
2. Glejser Test Method
The criteria for the assessment are as follows:
a) If the t-test for the independent variable has a sig value of < 0.05, there is undoubtedly heteroscedasticity b) If the t-test for the independent variable has a sig value of >= 0.05, ensure that there is no heteroscedasticity [23]
3. RESULT AND DISCUSSION
Often to test multiple linear regression analysis, the data are first tested with validity and reliability tests, followed by classical assumption tests, which include residual normality tests, multicollinearity tests, and heteroscedasticity tests.
3.1 Testing Process
There are several tests to get maximum results. The following are the testing process below.
3.1.1 Validity Test
The validity test in this study was carried out by comparing the r-count value with the r-table value according to the validity testing criteria with a significant level = 0.05. To get the r-value of the table, then look at the r-value of the table according to the table formula r obtained the result df = (73-2) or df = (71), with a significant level = 0.05, and obtained
the value of r-table = 0.230. The validity test results for each question item, the variables of ease of use, effectiveness, and user attitude can be seen in the following table 5::
Table 5. Validity Testing
No. r Hitung r Tabel Decision
Convenience (X1)
1. 0,585 0,230 Valid
2. 0,562 0,230 Valid
3. 0,672 0,230 Valid
4. 0,738 0,230 Valid
5. 0,655 0,230 Valid
6. 0,589 0,230 Valid
Effectiveness (X2)
1. 0,556 0,230 Valid
2. 0,602 0,230 Valid
3. 0,622 0,230 Valid
4. 0,666 0,230 Valid
5. 0,650 0,230 Valid
Attitude (Y)
1. 0,637 0,230 Valid
2. 0,711 0,230 Valid
3. 0,728 0,230 Valid
4. 0,697 0,230 Valid
Table 5 explains that in this validity test, the decision-making value is greater than the r-table, so the questionnaire is declared valid. However, if the value of r-Calculate is smaller than rTable, the questionnaire/questionnaire is declared invalid. Test this validity using r-Table 0.230. The results of testing the research instrument on the validity test table show that the r-count is greater than the r-table, which means that all questionnaires were declared valid and used as a data collection tool in this study.
3.1.2 ReliabilityTest
Reliability tests check whether the instrument's accuracy level is accurate. Based on the survey data, the reliability achieved using Cronbach's alpha compared to a significant degree. The significance level used in this study was 0.60.
Table 6 below shows the reliability results of this study.
Table 6. Reliability Testing
Cronbach's Alpha Significant Level Decision
0,789 0,60 Reliable
Table 6 explains that the reliability test results of 0.789 > 0.60 concluded that the questionnaire was reliable and used for research.
3.1.3 Classical Assumption Test a. Residual Normality Test
The data normality test determines whether what is obtained is usually distributed. Below are some normality test methods:
1. Chart Method
Figure 2. Normal P-P Plot Chart
Figure 2 shows that the points spread around the line and follow the diagonal line, and then the residual value is usually distributed.
2. Kolmogrov-Smirnov One Sample Test Method
This study uses the Kolmogorov Smirnov test with SPSS 27 software calculations, whose results show in Table 7 below.
Table 7. Kolmogrov-Smirnov One Sample Test
Unstandardized Residual
N 73
Normal Parametersa,b Mean .0000000
Std. Deviation 1.56069945
Most Extreme Differences Absolute .083
Positive .083
Negative -.083
Test Statistic .083
Asymp. Sig. (2-tailed)c .200d
a. Test distribution is Normal.
b. Calculate from data.
c. Lilliefors Significance Correction
d. It is a lower bound of the true significance
Table 7 above explains that the output above shows that the significance value (Asymp. Sig. 2-tailed) is 0.200.
Since the significance value is more significant than 0.05, the residual value is usually distributed.
b. Multicollinearity Test
This Test determines whether there is multicollinearity because a good regression model should not have multicollinearity.
Table 8. Multicollinearity Test Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients Collinearity Statistics
B Std. Error Beta t Sig Telerance VIF
1 (Constant) 9.665 2.302 4.199 <.001
Kemudahan .040 .101 .055 .397 .692 .641 1.560
Efektivitas .302 .127 .331 2.385 .020 .641 1.560
a.Dependent Variable: ATTITUDE
Table 8 above shows that the Tolerance value of both variables is 0.641, which means greater than 0.10, and the VIF value of both variables is 1.560, which means less than 10. Hypothesis H1 is accepted and concludes that there is no multicollinearity between independent variables.
c. Heteroscedasticity Test
This Test is to see whether or not there is heteroscedasticity because a good regression model should not have heteroscedasticity. In this study, heteroskedasticity tests were used, among others, the Scatter Plot/graph method (looking at the pattern of points on the regression graph) and the glejse method.
1. Scatter Plot/Graph Method
Figure 3. Output Scatterplot
Figure 3 shows that the points do not form a clear pattern, and the dots spread out above and below the number 0 on the Y-axis. So it can be concluded that there is no heteroscedasticity in the regression model.
2. Glejser Test Method
Table 9. Glejser Test Coeffficiensa
Model Unstandardized Coefficients Standardized Coefficients
B Std. Error Beta t Sig
1 (Constant) 1.334 1.434 .930 .355
Kemudahan -.027 .063 -.065 -.434 .666
Efektivitas .026 .079 .050 .334 .739
a.Dependent Variable: ABS_RES
Table 9 above explains that the significance value of convenience is 0.666, and the significance of effectiveness is 0.739. Thus the value of the two independent variables is more significant than 0.05, and it can be concluded that there is no heteroscedasticity problem in the regression model.
3.1.4 Multiple Linear Regression Analysis
Based on the results of the classical assumption test conducted and the results show that the residuals are normally distributed, there is no multicollinearity and no heteroscedasticity. Then the next step that must be done is multiple linear regression analysis.
Formulation Hypothesis:
H1 = There is an influence of Ease (X1) and Effectiveness (X2) on Attitude (Y) H2 = There is an effect of Ease (X1) on Attitude (Y)
H3 = There is an effect of Effectiveness (X2) on Attitude (Y) The level of confidence/significance is 95%, a = 0.05 a. Coefficient of Determination
Table 50. Coefficient of Determination Test Model Summaryb
Model R R Square Adjusted R Square Std. The error in the Estimate
1 .367a .135 .110 1.58284
a. Predictors: (Constant), EFFECTIVENESS, CONVENIENCE b. Dependent Variable: SIKAP
Table 10 above shows that the value of the R Square determination authority proves a value of 0.135. It means that ease (X1) and effectiveness (X2) affect attitude (Y) by 13.5%, while other variables outside of this study influence the remaining 88.5%.
b. Simultaneous Test (F-Test)
Use the F test to determine whether the variables of ease (X1) and effectiveness (X2) are called independent simultaneously (simultaneously) and have a significant effect on the attitude variable (Y) or dependent.
Table 6. Simultaneous Test (Test F) ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 27.281 2 13.641 5.445 .006b
Residual 175.376 70 2.505
Total 202.658 72
a.Dependent Variable: ATTITUDE
b.Predictors: (Constant), EFFECTIVENESS, CONVENIENCE 1. First Hypothesis Testing (H1)
Table 11 above explains that the calculated F value is 5.445 with a significance value of F test 0.006. Since the significance value is less than 0.05, it assumed that H1 accepted is the variable Ease (X1) and Effectiveness (X2) or independent simultaneously (together) affects the variable Attitude (Y) or dependent.
c. Partial Test (t)
The t-test use to determine whether the variables Ease (X1) and Effectiveness (X2) or called independent, partially have a significant effect or not on Attitude (Y) or dependent.
Table 1. Partial Test (Test t) Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients
B Std. Error Beta t Sig
1 (Constant) 9.665 2.302 4.199 <.001
Kemudahan .040 .101 .055 .397 .692
Efektivitas .302 .127 .331 2.385 .020
a.Dependent Variable: ATTITUDE 1. Second Hypothesis Testing (H2)
In Table 12 above, the significance value of the convenience variable (X1) is greater than 5% (0.692 > 0.05), it concluded that the H2 hypothesis is rejected, which means that the independent variable Ease (X1) does not affect the dependent variable Attitude (Y).
2. Third Hypothesis Testing (H3)
It is known that the significance value of the effectiveness variable (X2) is smaller than 5% (0.02 < 0.05), so it can be concluded that the H3 hypothesis is accepted, which means the independent variable Effectiveness (X2) affects the dependent variable Attitude (Y).
3.2 Discussion
The multiple linear regression analysis results show that the magnitude of the constant value produced is 9.665, the regression coefficient for the Ease variable (X1) is 0.302 positive, and Effectiveness (X2) is 0.040 positive values. Thus found, the multiple regression equation is as follows:
Y = 9,665 + 0,302 X1 + 0,040 X2
The multiple linear regression equation Y above interprets that if the Ease perception variable (X1) increases by one unit, then the attitude variable (Y) has no significant effect because the significance value is more excellent than 5%
(0.692 > 0.05). It means that the better the respondent's perception of the ease of electronic document control systems, there is the level of respondents' attitudes toward using electronic document control systems in work activities. If the Effectiveness perception variable (X2) increases by one unit, then the attitude variable (Y) will increase by 0.040 and have a significant effect because the significance value is less than 5% (0.020 < 0.05). It means that the better the respondent's perception of the effectiveness of using an electronic document control system, the more the respondent's attitude toward using it will increase in work activities.
Based on the results of this study of the three hypotheses tested, only H2 was not accepted. Namely, the ease of use of electronic document control systems does not affect the attitude of users of electronic document control systems.
It is because the significance value is more excellent than 5% (0.692 > 0.05), then H2 is rejected. As for H1 and H3 are accepted.
4. CONCLUSION
Based on the results of research calculations and discussions, it can be concluded that the sampling of 73 respondents at PT. Voksel Electric Tbk to permanent employees who use electronic document control systems, it can be seen that 13.5%
of samples accept the existence of electronic document control technology based on the ease and effectiveness of electronic document control systems. The calculation of the three hypotheses tested explains that the H1 hypothesis is accepted: the ease and effectiveness of using electronic document control systems simultaneously (simultaneously) influence the attitude of users of electronic document control systems. The H3 hypothesis is accepted: the effectiveness of using electronic document control systems affects users' attitudes toward electronic document control systems. As for the H2 hypothesis being rejected, the ease of use of electronic document control systems does not affect the attitude of users of electronic document control systems. It is because the significance value of convenience (X1) is greater than 5%
(0.692 >0.05). It was found that the relevant influence between the effectiveness of use and user attitudes in implementing an electronic document control system. The more effective the use of an electronic document control system, the more willing users are to embrace the use of an electronic document control system. For the following study, it is expected to be able to add other variables that can affect the acceptance of the Technology Acceptance Model (TAM).
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