MOVE: Journal of Community Service and Engagement Vol.
No.
January 2026 Page : 110 - 127 DOI : 10.
54408/move.
E-ISSN: 2808-2990
P-ISSN: 2828-4941
The Influence of Internal Control and Information Technology on Fraud Prevention (Empirical study of individuals working in accounting, finance, taxation, auditing, and other financial management fields in Jakarta and surrounding area.
Feber Sormin 1.
Fahri Solahudin2.
Lamhot Hutabarat2.
Widury Siburian2.
Iwan Armawan2 Faculty of Economics and Business.
Universitas Mercu Buana.
Jakarta Faculty of Law.
Mpu Tantular University.
Jakarta febersormin@gmail.
id (Corresponding autho.
Abstrak Tujuan dari penelitian ini adalah untuk mengkaji dan menganalisis pengaruh pengendalian internal (IC) dan Teknologi Informasi (TI) terhadap pencegahan penipuan (FP) di antara individu yang bekerja di bidang Akuntansi.
Keuangan.
Perpajakan.
Audit, dan pengelolaan keuangan lainnya di Jakarta dan sekitarnya.
Metode Penelitian Ae Jenis penelitian ini bersifat kuantitatif, menggunakan analisis regresi linier ganda dengan data primer dan pengukuran data skala ordinal yang dikumpulkan dengan mendistribusikan kuesioner kepada responden individu yang bekerja di bidang Akuntansi.
Keuangan.
Perpajakan.
Audit, dan pengelolaan keuangan lainnya di Jakarta dan sekitarnya di beberapa lokasi bisnis/perusahaan.
Jumlah sampel yang digunakan adalah 62 responden individu yang bekerja di bidang Akuntansi.
Keuangan.
Perpajakan.
Audit, dan pengelolaan keuangan lainnya di Jakarta dan sekitarnya.
Pengolahan data dilakukan dengan menggunakan aplikasi SPSS.
Hasil penelitian: Variabel pengendalian internal dan teknologi informasi terbukti mempengaruhi pencegahan penipuan.
Kata kunci: Pencegahan Penipuan.
Pengendalian Internal.
Teknologi Informasi Abstract The purpose of this research is to examine and analyze the influence of internal control (IC) and Information Technology (IT) on fraud prevention (FP) among individuals working in the fields of Accounting.
Finance.
Taxation.
Auditing, and other financial management in Jakarta and its surrounding areas.
Research Method Ae This type of research is quantitative, using multiple linear regression analysis with primary data and ordinal scale data measurement collected by distributing questionnaires to individual respondents working in the fields of Accounting.
Finance.
Taxation.
Auditing, and other financial management in Jakarta and its surrounding areas at several business/company locations.
The number of samples used was 62 individual respondents working in the fields of Accounting.
Finance.
Taxation.
Auditing, and other financial management in Jakarta and its surrounding areas.
Data processing was carried out using the SPSS application.
Research results: Internal control and information technology variables are proven to influence fraud prevention.
Keywords: Fraud Prevention.
Internal Control.
Information Technology MOVE: Journal of Community Service and Engagement is licensed under an Attribution-ShareAlike 4.
0 International (CC BY-SA 4.
Sormin et al.
Introduction Indonesia's global economic fundamentals from 2021 indicate post-pandemic recovery, with gross domestic product (GDP) growth of 3.
69%, and growth in 2022 to 31%, driven by the transportation sector and exports of goods and services.
Growth is projected at 5.
05% in 2023 and lower at 5.
03% in 2024.
The global COVID-19 pandemic, which was initially predicted to see an economic upturn since 2019, has had a fluctuating impact until 2024.
(Badan pusat statistic.
Stakeholders, especially the government, are certainly required to pay greater attention to and strive to improve the economic well-being of the Indonesian people through national development activities.
Government activities are closely related to the budgeting process, which involves various interests and roles of bureaucratic officials (Pane, 2.
The budgeting process in government allows for misappropriation, leading to inefficiencies, from planning, preparation, implementation, and budget reporting.
The government, as the primary entity responsible, must ensure that there are no leaks or fraud in the budget that has been set through preventive measures such as issuing regulations for effective, efficient, transparent, and accountable state financial management, as well as avoiding fraud.
However, government efforts to date have not yielded optimal results in combating fraud committed by certain state officials.
According Transparency International's https://w.
org, which published Indonesia's Corruption Perception Index (CPI) score for the past four years .
Indonesia's ranking and CPI score remain very low.
In 2022.
Indonesia's CPI was ranked 110/180 with a score of 34, a decrease from the previous year.
In 2023.
Indonesia ranked 115 with a score of 34, and in 2024.
Indonesia rose to 99 with a score of 37, a 3-point increase.
However, significant challenges in eradicating corruption, as indicated by the global score, tend to stagnate, and its ranking in Southeast Asia remains.
The higher a country's CPI score, the lower its corruption rate, and the more effective and qualified its government (Taufik, 2.
The lower the CPI score, the higher the corruption rate and the lower the country's fundamental economic Publication of the CPI data illustrates the facts on the ground in several corruption cases at the State-Owned Enterprise (BUMN) Jiwasraya .
ource: BPK Annual Report .
the Asabri case in 2019 (Source: BPK annual reports 2020, p.
in 2023, corruption involving self-enrichment of officials at the Minister of Agriculture was revealed .
co/huku.
and in 2023, the criminal act of corruption in the Tin Trade Administration in the mining business permit (IUP) area of PT.
Timah Tbk for the period 2015-2022 was revealed in 2024.
The government continues to strive to cover the weaknesses of the control system so as not to create a bigger fraud situation and condition by issuing regulations, such as Government Regulation Number 54 of 2010 concerning Regional Financial Management which regulates the procedures for transparent and accountable regional financial management, with the aim of preventing corrupt practices in the use of public funds.
The government also issued Government Regulation of the Republic of Indonesia number 12 of 2017 concerning Guidance and Supervision of Government Implementation in establishing the Government Internal Supervisory Apparatus (APIP), namely the Inspectorate General of the Ministry, the supervisory unit of nonministerial government institutions, provincial inspectorates and district/city The government issued Presidential Regulation number 82 of 2018 https://equatorscience.
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concerning Health Insurance in which article 92 explains the prevention and handling of fraud in the implementation of the health insurance program which is followed up by one of the regulations of the Ministry of Health (PERMENKES) number 16 of 2019 which provides more detailed regulatory instructions in the context of fraud prevention.
The situations and conditions described are highly contradictory to achieving the national economic development goal of improving the people's welfare.
The implementation of ethics and disciplined internal controls as stipulated in regulations must be carried out collaboratively by all officials and not under the pressure of limited freedom, which could impact fraud prevention.
(Hamid & Nasih, 2.
stated that if honest habits are developed, they will be crucial in preventing fraud cases.
Research (Rifai & Mardijuwono, 2.
explains that various efforts are continuously being made to eradicate and reduce the level of corruption nationally by involving the public at the government level, such as Governors.
Regents.
Mayors, and Ministers.
In reality, to date, fraud prevention efforts have not significantly changed in terms of fraud, and in fact, fraud is becoming more rampant and sophisticated in its practices based on continuously changing and advancing technology.
According to (N'Guilla Sow et al.
Fraud Prevention (FP) refers to the policies and procedures implemented by organizations to avoid becoming victims of fraud.
One of the studies that analyzes fraud prevention is the impact of internal control in a mechanism of duties and functions of officials in various institutions and Internal control is a mechanism in an institution that aims to ensure all activities and operational activities are in accordance with applicable procedures and provisions (COSO.
Utami et al.
, 2.
The internal control system is a process influenced by the board of directors, management, and other entity personnel, which is designed to provide reasonable assurance for the achievement of the effectiveness and efficiency of achieving state administration objectives, the reliability of financial reporting, the security of state assets, and compliance with laws and regulations (Puryati & Febriani, 2.
The internal control system by previous researchers (W.
Utami et al.
, 2.
was measured using five dimensions: first, the control environment consisting of 2 .
second, risk assessment consisting of 3 .
third, control activities consisting of 2 .
fourth, information and communication systems consisting of 2 .
and the fifth dimension is monitoring with two indicators.
The author uses all dimensions and indicators used by W.
Utami et al.
, 2020, for a total of 11 indicators.
Previous research results indicate that internal control has a positive effect on fraud prevention, namely research (W.
Utami et al.
, 2020.
N'Guilla Sow et al.
, 2018.
Puryati & Febriani, 2020.
Rustandy et al.
Taufik, 2019.
Wibowo et al.
, 2.
However, this differs from the results of research by Yulfani et al.
, which states that internal control has no effect on fraud prevention.
Increasing support for improving Indonesia's economic fundamentals certainly requires infrastructure and facilities, one of which is information technology support for the implementation of development activities.
The application of information technology helps companies produce accurate information and has an impact on fraud prevention (Suryanto, 2.
Measurement of information technology variables for fraud prevention in previous research (Ferina et al.
, 2.
used the following dimensions: hardware, software, databases, networks, and other electronic devices, each indicator of which has one question.
(Juhandi et al.
, 2.
explained that information technology can be a managerial decision to prevent fraud in companies.
This is proven by the fact that in developed countries, not only relying on supervision from leaders, but also information technology is able to detect fraud, which is useful https://equatorscience.
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as a preventative measure.
Previous research results indicate that information technology has a positive effect on fraud prevention, namely research (Ferina et al.
Meiryani et al.
, 2019.
Halbouni et al.
, 2.
However, this is different from the results of research (W.
Utami et al.
, 2.
which states that information technology governance has an effect, but not significantly, on early warning fraud.
This is suspected due to the still low attention to good governance of information technology Meanwhile, the results of research (Asrin et al.
, 2.
state that the use of information technology does not have a positive effect on fraud prevention.
To measure the effectiveness of the role of individuals working in the financial sector in carrying out fraud prevention efforts, the author proposes a measurement using the fraud prevention dimensions based on Presidential Regulation No.
82 of 2018.
Article 92, with the implementing regulations through PERMENKES No.
16 of 2019 concerning the prevention and handling of fraud, which is divided into three dimensions in the fraud prevention system.
The fourth dimension (N'Guilla Sow et al.
evaluating anti-fraud processes and controls includes three indicators.
So the total fraud prevention dimensions in this study are four dimensions with indicators in the fraud prevention testing in the study being 11 indicators.
The functions and duties of civil servants or state officials who have weaknesses in fraud prevention are a motivation for the author to conduct research to find out and provide an overview of the research object of internal control and information technology as independent variables on fraud prevention, which is expected to have a positive impact on public welfare and can be a support for the government in eradicating corruption in Indonesia.
Another motivation is based on research gaps, and limited capabilities in the rapid advancement of information technology, it is necessary to adjust indicators/measurements that are in accordance with the development of the latest technological models in measuring fraud prevention.
Based on the description of the background, the scope of the research, the author determines the title of the dissertation "The Influence of Internal Control and Information Technology on Fraud Prevention".
Agency Theory Agency Theory is defined as the relationship between an agent .
usiness managemen.
and a principal .
usiness owne.
(Jensen & Meckling, 1.
In an agency relationship, there is a contract in which one or more people .
instruct another person .
to perform a service on behalf of the principal and authorize the agent to make the best decisions for the principal.
This theory is adopted as a theory in fraud prevention research for individuals working in the scope of accounting, finance, taxation, auditing, and other financial management, where each individual employee or professional in the financial field acts as an agent working in a company or other organization that receives a mandate of trust from the company owner as the highest sovereign owner .
Accounting, finance, taxation, auditing, and other financial management employees .
certainly have interests, both personal and group, when carrying out company operations.
Of course, these agents will have more information, where information about their entity can be intentionally hidden.
To achieve these goals, government agencies and officials strive to create a positive work environment through good governance, as outlined in regulations, to foster a positive organizational culture.
This is necessary so that individual employees or officials who carry out the operations of companies or government organizations can implement internal control measures, supported by information technology, in accordance with the mandate of the law.
However, these https://equatorscience.
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various preventive measures still need to be evaluated and updated according to current demands to minimize or eliminate opportunities for fraud.
Tax Fraud Prevention (Y) Fraud prevention is an activity that needs to be carried out to reduce losses due to fraud, including adequate controls and maintaining personal values and appropriate transactions (Ferina et al.
, 2.
To measure the effectiveness of the role of individuals working in the financial sector in carrying out fraud prevention efforts, the authors propose a measurement using the fraud prevention dimensions based on Presidential Regulation No.
82 of 2018.
Article 92, with the implementing regulations through PERMENKES No.
16 of 2019 concerning the prevention and handling of The researchers established in the fraud prevention system through 3 .
dimensions: first, developing a fraud prevention culture consisting of 2 .
second, developing quality control-oriented services and cost control covering 3 .
third, establishing a fraud prevention team covering 3 .
The fourth dimension (N'Guilla Sow et al.
, 2.
evaluating anti-fraud processes and controls covering 3 .
So, the total dimensions are 4 .
with indicators in the fraud prevention testing in the study using 11 indicators.
Internal Control (X.
Internal control is a mechanism within an institution that aims to ensure that all activities and operational activities are in accordance with applicable procedures and (COSO.
Utami et al.
, 2.
The internal control system is a process influenced by the board of directors, management, and employee personnel or officials of other entities, which is designed to provide reasonable assurance for the achievement of effective and efficient control of the achievement of operational objectives, reliability of financial reporting, safeguarding of state assets, and compliance with laws and regulations (Puryati & Febriani, 2.
The internal control system by previous researchers (W.
Utami et al.
, 2.
was measured using five dimensions: first, the control environment consists of 2 .
indicators, namely:
management philosophy and operating style, and integrity and ethical values.
risk assessment consists of 3 .
indicators, namely: existence and accuracy, completeness, assessment and allocation.
third, control activities consist of 2 .
indicators, namely job description, asset security and records.
The fourth dimension is the information and communication system, consisting of two indicators: classification and timeliness.
and the fifth dimension is monitoring, with two indicators: frequency of activity assessment and reconciliation of financial reports.
The author uses all dimensions and indicators used by W.
Utami et al.
, 2020, for a total of 11 indicators.
Information technology (X.
Information technology is technology in the form of .
ardware, software, human.
used to obtain, transmit, process, interpret, store, organize, and use data meaningfully to obtain quality information (Meiryani et al.
, 2.
The information technology variable in this study was measured using 5 .
dimensions: hardware, software, database, networks, other electronic devices, (Ferina et al.
, 2.
, where the first dimension is Hardware with one indicator, namely hardware knowledge.
The second dimension is Software with one indicator, namely Software Understanding.
The third dimension is Database with one indicator, namely Database Security.
The fourth dimension is Networks with one indicator, namely network support.
The fifth https://equatorscience.
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dimension is other electronic devices with one indicator, namely the Accounting Information System.
Based on the explanation above, the framework of thought in this research is as Internal Control (X.
Fraud prevention (Y) Information technology (X.
Figure 1.
Framework of Thought Hypothesis:
H1: Internal control has a positive effect on tax fraud prevention.
H2: Information technology has a positive effect on tax fraud prevention.
Method The research design uses quantitative research with primary data and is causal comparative in nature to determine the causal relationship between two or more variables, including identifying the facts that occur as influenced variables and influencing variables.
All measurements of independent variables and dependent variables are measured using ordinal: Number-1 = Strongly Disagree.
Number-2 = Disagree.
Number-3 = Agree.
Number-4 = Strongly Agree.
Number-5 = Strongly Agree.
Population and Research Sample The population in the study is individuals with a minimum education of Bachelor (S.
who work in the fields of Accounting.
Finance.
Taxation.
Audit, and Financial Management who work in various types of businesses or professional activities with consideration of standards and regulations who have sufficient knowledge and experience and competence to understand all questions or statements used in the questionnaire instrument, so that the author determines the criteria for selecting respondents as follows:
Individuals working in the fields of Accounting.
Finance.
Taxation.
Auditing, and Financial Management, working in various types of businesses or as financial .
Minimum positions of staff, supervisor, head/manager and above, working in areas related to Accounting.
Finance.
Taxation.
Auditing, and Financial Management, working in various types of businesses and as financial experts.
Individual employees or officials with a minimum of a Bachelor's degree (S.
The research sample was determined based on research (Hair et al.
, 2.
which explains that one of the minimum sample size guidelines is 10 .
en time.
the most indicators in one dimension of each variable used.
The number of variables in this study consists of three .
variables, where one .
dimension with the most indicators was taken from each to calculate the required sample size.
Based on this, the researcher performed the following calculations:
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Table 1 Calculation of the number of respondent sample sizes Variable Dimension that has the Indicator x = Total most indicators Fraud prevention Team.
Control Environment.
Hardware TOTAL Source data: Data Peneliti .
Based on table 1 of the calculation of the number of respondent samples above, the minimum number of samples (Hair et al.
, 2.
is 10 x 6 indicators = a minimum of 60 research respondents to be used and collected proportionally.
Method of collecting data Primary data collection techniques through literature reviews .
xpert books, journals, etc.
) and field research using a survey method with a questionnaire using a Google form sent to individual employees or professional experts in the fields of accounting, finance, taxation, auditing and other financial management.
Analysis Method Data analysis using SPSS software with: Descriptive Statistical Analysis.
Validity and Reliability Test.
Classical Assumption Test with Normality Test: measured by the Kolmogorov-Smirnov Method where the significant value is 0.
Multicollinearity Test: measured by the variance inflation factor (VIF) between VIF <10 and tolerance> 0.
Heteroscedasticity Test: measured by the Glejser test where the sig criterion = 0.
Data Suitability Test using: Simultaneous Significance Test (FStatistic Tes.
, analyzing the accuracy of the independent variable model together, simultaneously influencing the dependent variable.
The sig level is 0.
05 ( = 5%) with the F-statistic test.
Determination Coefficient Test (R2 Tes.
, measuring the R2 Value / The coefficient of determination value is between 0 and 1, the closer the coefficient of determination value is to 1, the stronger the independent variable explains the dependent variable.
Hypothesis Testing with Individual Parameter Significance Test .
-Statistic Tes.
where the t-test compares the significance value <0.
05 or t-count with t-statistic > t-table.
If the sig value <0.
05 then Ho .
ull hypothesi.
is rejected and Ha .
lternative hypothesi.
is accepted, or partially the independent variable has a significant effect on the dependent variable, if otherwise then it is not significant, or Ho is accepted Ha is rejected.
Multiple Linear Regression Analysis to connect one dependent variable with several independent variables in a single predictive model, which aims to determine how much influence the independent variables have on the dependent variable moderated by the organizational culture variable.
The first and second multiple linear regression analysis models are as follows:
Y = 1X1 2X2 e Description: FP = fraud prevention.
= Constant.
= Regression Coefficient.
X1 = internal control (IC).
X2 = Information technology (IT).
e = Error rate https://equatorscience.
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Results and Discussion The frequency profile of the respondents in this study is divided into 4 .
characteristic categories, namely gender, education, position, and length of service .
ork experienc.
, and the number of samples processed is 62 respondents, when all data samples were processed they were normal so they could be used in testing.
Frequency of Respondent Characteristics by Gender Frequency of Respondent Characteristics Based on Gender Nominal data is divided into 2 .
types, namely male and female.
The results of SPSS output data processing based on gender frequency show a sample size of 62 respondents, dominated by 37 male respondents or 59.
7%, and 40 female respondents or 40.
Frequency of Respondent Characteristics based on Education.
Frequency of Respondent Characteristics based on Education is divided into 3 ordinal categories, namely S1.
S2.
S3, with the results of self-processed data from the SPSS output results based on the Frequency above dominated by S1 Education based on the number of samples of 62 respondents consisting of S1 Education Level as many as 29 respondents or 46.
S2 Education amounted to 24 respondents or 38.
7% and S3 amounted to 9 respondents or 14.
meaning that the questions submitted via the questionnaire can be sufficiently understood and comprehended by the respondents who filled it out.
Frequency of Respondent Characteristics by Position Frequency of Respondent Characteristics based on Position Nominal data is divided into 4 .
, namely Staff.
Supervisor.
Head of Department/Financial Expert.
Based on the SPSS output data, the Frequency shows the number of samples of 62 respondents, dominated by Staff/Employees 19 respondents or 6%, and Supervisors 11 respondents or 17.
7%, and the position of head of department/financial expert there are 32 respondents with 51.
Thus, it can be concluded that the expected sample responses who carry out daily activities in the field are fulfilled or are in accordance with the research plan.
Frequency of Respondent Characteristics Based on Length of Work Experience.
Frequency of Respondent Characteristics based on Work Experience is divided into 4 ordinal categories, namely 0-3 years.
3-6 years.
6-12 years.
>12 years, with the results of self-processed data from the SPSS output results based on the frequency above, dominated by respondents with experience of >12 years is 36 respondents or 58.
1%, the second respondent is 3-6 years of experience with 11 respondents or 17.
work experience between 6-12 years is 11 respondents or 17.
7%, and the last is 0-3 years of work experience is 4 respondents or 6.
5%, meaning that based on the work experience of respondents who filled out the questionnaire, it can be said that they understand the contents of the questionnaire questions that are delivered.
Results Descriptive Statistics Analysis Descriptive statistics aims to determine the amount of data, minimum value, maximum value, .
average value, and standard deviation of all research data collection in the end of December 2025 to January 2026.
Based on the number of samples from the population that can be used in this study is 62 respondents and the results of the questionnaire answers are added up per indicator and then divided according to the number of questions in one variable to get the score value per variable and then tested with the SPSS application.
When tested all the data score values per https://equatorscience.
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variable all data are normal, and from 62 respondents normal data samples that can be tested in the descriptive statistics test of the study, the data results are as follows:
Fraud Prevention Internal Control Information technology Valid N .
Table 2.
Descriptive Statistics Minimum Maximum Mean Std.
Deviation Source Data: Results of processing data using SPSS Based on table 2, the results of descriptive statistics can be explained as follows:
The results of the fraud prevention analysis in Table 2 obtained a minimum value of 1.
00, which means that of all respondents who gave the lowest answer rating for fraud prevention, it was 1.
The maximum value was 00, which means that of all respondents who gave the highest answer rating for the implementation of fraud prevention, it was 5.
The mean value of the fraud prevention (FP) variable was 4.
4548, which means the average for the research questionnaire group on fraud prevention was Meanwhile, the standard deviation of 0.
80288 means that the measure of data distribution from the performance variable was 0.
from 62 respondent data.
From the analysis results, the value of 4.
4548 was greater than the standard deviation of 0.
80288, which means the data was normally distributed.
The Internal Control (IC) variable has a minimum value of 1.
00 and a maximum value of 5.
00, indicating that there is variation in internal control in the sample studied.
The mean internal control (IC) value is 4.
meaning that the average questionnaire group is 42.
99% of the internal control value.
The mean result of 4.
2987 is greater than the standard deviation of 0.
72479, indicating that the data is normally distributed.
The Information Technology (IT) variable has a minimum value of 1.
00 and a maximum value of 5.
00, indicating that there is variation in information technology in the sample studied.
The mean value for information technology is 4.
4290, which means the average for the questionnaire group The mean of 4.
4290 is greater than the standard deviation of 76381, indicating that the data is normally distributed.
Classical Assumption Test Normality test results The normality test is performed by examining the Normal Probability Plot, which compares the cumulative distribution with the normal distribution (Ghozali 2018:.
The normal distribution will form a straight diagonal line, depicting the actual data following the diagonal line.
The results of the normality test using the Normal Probability Plot are as follows:
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Figure 2.
Results of Graph Analysis with Normal Probability Plot (Normal P-Plo.
Based on the results of the classical assumption test for normality, the probability plot graph is still spread around the diagonal line which follows the diagonal line, which means that the test carried out is normally distributed.
Multicollinearity Test To determine whether or not there are symptoms of multicollinearity, analysis is carried out based on the Variance Inflation Factor (VIF) and Tolerance values.
If the VIF value is less than 10 and the tolerance is more than 1, it is stated that there is no multicollinearity.
Ghozali .
Table 3.
Multicollinearity Test Results Coefficientsa Collzinearity Statistics Model Tolerance VIF 1 Internal control Information technology Dependent Variable: Tax Fraud Prevention Based on Table 3, the results of the multicollinearity test on the independent variables of this study, the tolerance value of the three independent variables (X1.
is greater than 0.
The Variance Inflation Factor (VIF) value of the two independent variables is less than 10.
Based on the determination criteria that have been stated previously, it can be concluded that there is no multicollinearity problem among the independent variables, so the multicollinearity test is fulfilled.
Heteroscedasticity test Heteroscedasticity is a residual variable that is not the same across all observations in a regression model.
A good regression model should not have The criteria for determining whether heteroscedasticity has occurred are: if there is no clear pattern, and the points are spread above and below the Y-axis, then heteroscedasticity is not present.
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Figure 3.
heteroscedasticity test In figure 3, the results of the heteroscedasticity test in this study, the points in the figure do not show a clear pattern in the scatterplot graph, indicating a good regression model in accordance with the rules of the heteroscedasticity test.
Autocorrelation Test Results An autocorrelation test can be performed if the research data used is time series data .
ata recorded sequentially over tim.
This research data is a cross-section, or data obtained simultaneously, like primary data from a Therefore, an autocorrelation test is unnecessary because the sample data used comes from primary data from the questionnaire.
Hypotesis Test Coefficient of Determination Test (R2 Tes.
The Coefficient of Determination test measures the R2 value/Coefficient of Determination value between 0 and 1.
The closer the coefficient of determination value is to 1, the stronger the independent variable's ability to explain the dependent variable.
The value for the coefficient of determination can be seen in the Adjusted R-Square column.
The first test is carried out only by linear regression between the dependent and independent variables, as follows:
Table 4 Coefficient of Determination Test (R2 Tes.
Model Summaryb Adjusted R Std.
Error of the DurbinModel R Square Square Estimate Watson Predictors: (Constan.
Information technology.
Internal Control Dependent Variable: Fraud Prevention From table 4, it can be seen that the R coefficient is 0.
699 or 69.
9% with an Adjusted R Square value of 0.
688 or 68.
8% influenced by the variables used, while the remaining 31.
2% is influenced by other variables.
Simultaneous Significance Test (F-Statistic tes.
The Simultaneous Significance Test (F-Statistic Tes.
analyzes the accuracy of the model of independent variables simultaneously influencing the dependent The significance level is 0.
05 (=5%) with the F-statistic test.
The results of the simultaneous test (F) between Internal Control.
Tax Professionals, https://equatorscience.
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and Professional Commitment to Taxpayer Compliance are as follows:
Table 5 Simultaneous Significance Test (F-Statistic tes.
ANOVAa Sum of Model Mean Square Squares Regression Residual Total Dependent Variable: Fraud Prevention Predictors: (Constan.
Information technology.
Internal Control Sig.
Based on the results of table 5, it can be seen that the simultaneous test value (F tes.
is 68,528 with a sign value of 0.
000 or <0.
05, so that the F test can conclude that the hypothesis is accepted or, in the sense that all independent variables used in the model influence together and are suitable for predicting the dependent variable and proof of the hypothesis can be carried out.
Hypotesis test Individual parameter significance test .
-statistic tes.
The t-test compares the significance value of t <0.
05 or the calculated t with the tstatistic > t-table, whether Ho is rejected and Ha is accepted, or partially the independent variable has a significant effect on the dependent variable, if otherwise it is not significant, or Ho is accepted and Ha is rejected.
The following is a table of partial test results .
Table 6.
Results of Individual Parameter Significance Test .
-Tes.
Coefficientsa Unstandardized Standardized Model Coefficients Coefficients Std.
Error Beta 1 (Constan.
Internal Control Information technology 1.
Dependent Variable: Fraud Prevention Sig.
Multiple Linear Regression Analysis To relate one dependent variable to several independent variables in a single predictive model, this is to determine how much influence the independent variables have on the dependent variable.
Based on the results of the multiple linear regression analysis test in Table 6, the following can be seen:
Y = 0.
340 IC 1.
189 TI.
The constant value of 0.
335 indicates that if the Internal Control and Information Technology variables are held constant, the fraud prevention value will remain constant at 0.
The constant value in this study is positive, indicating that the independent variable has a positive influence on the dependent variable.
The result of the Internal Control regression coefficient is 0.
340 with a positive value with a sign of 0.
005 or H1 is accepted, meaning that there is a positive https://equatorscience.
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relationship between Internal Control and Fraud Prevention, or every 1% increase in Internal Control will result in an increase in the Fraud Prevention value of 34.
0% assuming that other independent variables remain constant.
The regression coefficient of the Information Technology variable has a positive value with a value of 1.
189 and a sign of 0.
000, or H2 is accepted, so there is a positive relationship between Information Technology and the value of Fraud Prevention, in the sense that every 1% increase in Information Technology will result in an increase in the level of Fraud Prevention by 118.
9% with the assumption that other independent variables remain constant.
Discussion The influence of internal control on fraud prevention Based on the hypothesis test H1 on the significance of the t-test is 2.
933 and the result of the regression coefficient test is 0.
340 with a positive value with a sign of 005, meaning that Ha1 is accepted in the sense that there is a positive relationship between Internal control and Fraud Prevention, or every 1% increase in Internal control will result in an increase in the value of Fraud Prevention by 34.
0% assuming that other independent variables remain constant.
The results of this internal control research on fraud prevention prove that, based on the results of the respondent data processing, internal control with the indicators used has an overall positive effect on fraud prevention.
With the implementation of good and strong internal control, it will be able to create a strong communication environment and processes that are open to each other and avoid opportunities for fraud, as well as increase the transparency and accountability of the Company's and organization's operations in recording every financial transaction properly and correctly.
Likewise, by maintaining the value of integrity, especially in risk assessment through the existence of quasi-funds, as well as completeness, assessment and allocation of good, the risk of fraud can be prevented through strong internal control.
Routine and systematic control activities with job descriptions, asset security and records properly will prevent fraud, especially the existence of an information and communication system built with classification and timeliness.
addition, supervision .
with standard frequency of activity assessment, and reconciliation of financial reports that are routinely and well done have been able to cover weaknesses to prevent fraud.
This research is in line with the research results (W.
Utami et al.
, 2020.
N'Guilla Sow et al.
, 2018.
Puryati & Febriani, 2020.
Rustandy et al.
, 2020.
Taufik, 2019.
Wibowo et al.
, 2.
which explain that internal control has an effect on fraud prevention.
The Influence of Information Technology on Fraud Prevention Based on the H2 hypothesis test from the table in the t test is 4.
147 and the results of the regression coefficient of information technology testing are a value of 1.
189 and a sign of 0.
000, then there is a positive influence relationship between Information Technology on the value of Fraud Prevention or the H2 hypothesis is accepted, in the sense that every 1% increase in Information Technology will result in an increase in the level of Fraud Prevention by 118.
9% with the assumption that other independent variables remain constant.
The research results prove that information technology has a positive effect on fraud prevention.
This means that information technology, manifested through five indicator dimensions, namely hardware, software, databases, networks, and other electronic devices, has an impact on fraud prevention.
Information technology has a https://equatorscience.
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positive and significant effect on fraud prevention, the hardware information technology indicator dimension implemented by each individual in the fields of accounting, finance, taxation, audit, and financial management has good and adequate knowledge and understanding of hardware, as well as operational software .
used by individuals working in the fields of accounting, finance, taxation, audit, and financial management is easy to understand so that in its application it is useful to lighten the workload which has an impact on increasing fraud prevention.
Employee operational databases that are stored and maintained safely, their data confidentiality and are always updated if there are new technological changes also have an impact on increasing fraud prevention.
Technology can change programs, change files, steal data and even prevent sabotage (Basri, 2.
, in anticipating the rapid development of technology from time to time, continuous adjustments/updates to technology have an impact on information technology increasing fraud prevention.
The implementation of network support will certainly be able to expedite the operational work of officials, especially in the utilization of other electronic devices implemented through the Accounting Information System with the support of continuous training to help improve employee competency in fraud prevention.
Based on the demographics of respondents, the majority of respondents have work experience of more than 12 years, namely 58.
1% .
, this explains that the age of the respondents' experience is approaching retirement which will certainly affect the ability to follow updates on information technology developments, but those with more than 12 years of experience realize how useful information technology is in supporting the daily work processes of employees which is useful in improving fraud prevention.
The results of this study support agency theory regarding the use of information technology by individuals in fraud prevention.
It is possible that information asymmetry can occur between the agent and the principal.
When employees working in accounting, finance, taxation, auditing, and financial management .
have high levels of information technology implementation skills, the information asymmetry provided to the public .
can be reduced.
The use of information technology by individual employees/officials will certainly help accelerate early warning information about an incident indicating fraud.
This is in line with the statement (D.
Utami et al.
, 2.
regarding information technology governance regarding early warning fraud, which is expected to help prevent fraud.
The results of this study align with statements (Ferina et al.
, 2021.
Meiryani et al.
, 2019.
Halbouni et al.
, 2.
that state that information technology has a positive effect on fraud prevention.
Conclusion This research proves that internal control and technology are appropriate variables and directly influence fraud prevention.
The results of this study provide evidence and can be used to answer the previously stated research questions.
The conclusions drawn from this research are as follows:
Internal control variables influence fraud prevention.
Internal control can be used as a strategic option for companies, government agencies, or other organizations seeking to change their fraud prevention strategies.
Information technology has a positive effect on fraud prevention.
The better the information technology, the better the fraud prevention.
Information technology can be used as a strategic option if significant changes are desired in fraud https://equatorscience.
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This study has limitations encountered during the research process.
These limitations are as follows:
The respondents used in this study were individuals working in accounting, finance, taxation, auditing, and other financial management fields.
The application of fraud prevention may have different interpretations of the questionnaire questions, resulting in an imperfect completion process.
This could impact the results and quality of data analysis.
The respondents' situation within a strict organizational structure potentially resulted in respondents having limited freedom to provide objective answers to questions, often merely fulfilling their obligations.
The existence of administrative procedures experienced by individuals within each company could certainly influence respondents' completion of the Practical Implications: This research found that internal control and information technology have an impact on improving fraud prevention.
These results provide policy implications for companies, organizations, and governments, specifically for accounting, finance, taxation, audit, and financial management departments, in the form of internal policies on fraud prevention The implementation of internal control and policies to improve human resource capabilities in monitoring and implementing fraud prevention procedures, particularly in the fraud prevention dimension, is addressed in this .
These results provide practical implications for companies, organizations, and governments to improve the competency of individual employees at various levels in work procedures and the use of quality information technology through information technology training and development.
Based on the results of this study, the authors offer the following suggestions for further research:
Respondent data used for subsequent research should be sourced from a single company or organization to provide a more focused understanding of the implementation of fraud prevention.
Future researchers who will use fraud prevention variables can use or add new measurement indicators in addition to those used in this study.
The adjusted R-square coefficient of determination obtained in this study 9%, indicating that this research model is still open to further research by adding or modifying the dimensions used as independent variables, for example, by placing the public sector governance or integrity dimensions as independent variables for fraud prevention.
References