Corresponding Author: Mega Arthika Dewi

INTRODUCTION

The growth of the public sector in Indonesia is an integral part of economic dynamics and national development. The public sector covers all economic activities undertaken by both central and local governments, including public services, infrastructure investment, and social spending. Various factors, including government policies, global economic conditions, and internal challenges, such as regional inequality and poverty, influence the growth of the public sector in Indonesia. Public sector growth in Indonesia has a close relationship with public sector accounting.

Public sector accounting is an accounting practice applied by government entities, including the central government, local governments, and other public bodies. The growth of public sector accounting in Indonesia has accelerated with the Reformation Era in the early 2000s; this is evidenced by the demand for accountability for public institutions at the central and regional levels. The success or failure of an organization's mission implementation in reaching predefined goals and objectives through a periodically implemented accountability medium-state financial management, for example-is measured by accountability.

State financial management in Indonesia is one of the main functions of government that aims to ensure the availability of resources needed to carry out development and public services. State financial management includes the planning, use, and supervision of state funds. Several national laws regulate state financial management in Indonesia. Law Number 15 of 2004 about Amendments to Law Number 17 of 2003 concerning State Finance, Law Number 24 of 2007 concerning Regional Financial Administration and Management, and Law Number 1 of 2004 concerning Treasury are a few significant laws pertaining to state financial management.ï¿½

State financial management and budgeting have a very close and interrelated relationship. Budgeting is one of the main components of state financial management, and both aim to ensure the efficient, effective and responsible use of state resources.

The demand for the importance of implementing performance-based budgeting has brought consequences that must be prepared as a trigger factor for the successful implementation of the use of performance-based budgeting, namely: 1) Emphasis on continual administrative improvement; 2) Leadership and commitment from all organisational components; and 3) Adequate resources (cash, labour, and people) for such improvement initiatives; 4) Explicit incentives and penalties; 5) A burning ambition for success (BPKP, 2005).

A budget is a financial plan for the future that includes revenues, costs, and other financial transactions within one year. In public sector organizations, the budget includes plans about the costs of the plans that have been prepared by the organization/work unit and how to obtain a budget to fund the activities that have been prepared. Budgeting is a principle of accountability in the budgeting process, which starts with planning, preparation, and implementation (Manik & Sari, 2022).

Budgeting begins with the identification of goals, objectives, and strategies. Consensus among all parties or divisions on the objectives to be achieved is a key factor in planning the budget. The budgeting process is long and involves gruelling stages, often resulting in problems such as inaccuracies and a lack of insight into how to develop an effective budget (Manik & Sari, 2022).

In addition to being in charge of preparing the budget in its work units, Lemdiklat Polri also has a role as the bearer of the Polri HR professionalism program, which is in charge of preparing the entire Polri Education budget in Indonesia, starting from the formation of education, vocational education, development education, to higher education. A phenomenon that occurs in Lemdiklat Polri is that in the current budget year, Lemdiklat Polri often revises its budget. In 2022, Lemdiklat Polri revised its budget six times, including due to 1) Changes in Education Quota, 2) Changes in budget nomenclature, 3) Addition of Priority Program Activities, 4) Additional activities, 5) Changes in the budget for student meals at SPN, Pusdik and Schools; and 6) Budget reductions, as a result of Automatic Adjustment from the Ministry of Finance. Then, in 2023, Lemdiklat Polri revised the budget five times, including due to 1) Changes in Education Quota, 2) Changes in budget nomenclature, 3) Addition of activities, 4) Changes in the budget for student meals at SPN, Pusdik and Schools; and 5) Budget reductions as a result of Automatic Adjustment from the Ministry of Finance.

The time and preparation required to revise the budget at Lemdiklat Polri is longer than that of other work units within the National Police. This is due to the need to revise not only the Budget Implementation List (DIPA) of Lemdiklat Polri but also the DIPAs of the State Police Schools, Education Centers and Schools. The Budget Preparation Section in Lemdiklat Polri and its ranks play a vital role as a public service that emphasizes the budget aspect. Effective budget management will provide strong support for the bureaus/bags within the work units to carry out their functions and tasks properly, as budgetary needs are met and supported by skilled human resources.

According to Suyanto (2012), two factors influence budget preparation: system factors and people factors. The system in question concerns the rules in the organization or work unit, while the people factor concerns human resources.

Research conducted by (Wahyuni et al., 2023) the quality of human resources and leadership style have a positive impact on budget preparation capability, according to the study titled The Effect of Commitment, Quality of Human Resources, and Leadership Style on Budget Preparation Capability at the Government Education and Culture Office in Buleleng Regency. Commitment, however, has little bearing on budgetary capability.ï¿½

Research results (Wahyuni et al., 2023) supported by (Ismid et al., 2020) examine the Factor Analysis Affecting the Regional Budgetary Preparation (Case Study on the Regional Asset, Revenue, and Financial Management Agency of Karo Regency). The results of the multiple regression analysis indicate that Human Resources, Organizational Commitment, and Administrative System Improvement positively influence the preparation of the Regional Expenditure Revenue budget. This finding is consistent with previous research (Syamsuddin, 2022) regarding the Effect of Organizational Commitment, Administrative System Improvement, and Human Resources on Performance-Based Budgeting of the Education Office in Pohuwati Regency. From multiple regression analysis, the results of organizational Commitment, administrative system improvement, and human resources have a positive effect on performance-based budgeting in the education office. From the above results, if the quality of human resources is further improved, it will affect the preparation of a better budget.

Earlier studies investigated the impact of Human Resources Competence, Transparency, and Information Technology Utilization on the preparation of Regional Revenue and Expenditure Budgets in Medan City (Lubis & Shara, 2021). From Multiple Regression analysis, the result is that Human Resources Competence, Transparency and Information Technology Utilization have a positive effect on the preparation of Regional Revenue and Expenditure Budgets in Medan City. The results of this study are supported by research (Ismid et al., 2020) concerning the Analysis of Factors Influencing the Preparation of Performance-Based Regional Revenue and Expenditure Budgets in the Aceh Singkil District Government. From the results of multiple regressions, organizational Commitment, organizational system improvement, quality of human resources, reward, and punishment have a positive effect on performance-based regional budgeting. From the above results, if the quality of information technology in the budget preparation process is sufficient and supportive, it will affect the preparation of a better budget.

Previous research on the Effect of Human Resource Quality, Internal Control System and Performance-Based Budget System at Ganesha University of Education reveals that the quality of Human Resources, Internal Control System, and Performance-Based Budget System positively influence DIPA Budget Absorption (Anggeadi et al., 2023).

Previous research on the effect of external information on the preparation of the company's budget that has gone public has shown that external information has a positive effect on the preparation of the company's budget (AMIN, 2013). The results of this study are supported by research (Proverra, 2003) The results of this study are supported by research (Proverra, 2003) on the Influence of External Information on Corporate Budgeting in West Sumatra have the results that the Influence of External Information has a positive effect on Corporate Budgeting in West Sumatra. Research (Yendrawati, 2013) on the Influence of the Internal Control System and Human Resource Capacity on the Quality of Financial Statement Information, considering External Factors as Moderating Variables, finds that external factors moderate the impact of the internal control system on the quality of financial statement information.

Based on the description above, only research (Anggeadi et al., 2023) uses the Internal Control System as an Independent variable but is associated with Budget Absorption. Meanwhile, no one uses it as an independent variable in Budget Preparation Research. The Internal Control System in the Budget Preparation Process is essential. Internal control serves to direct, supervise, and measure an organization's resources. It is crucial for preventing and detecting fraud. When the internal control system is weak, it can lead to numerous instances of regional asset embezzlement, ultimately causing significant harm to the country. A stronger Internal Control System in an Institution/agency will increase the accountability and transparency of an agency's budget management. On the contrary, if the Internal Control System in an institution/agency is weak, it will allow abuse of power so that budget irregularities occur.

In previous research, no research has been found that uses external factors, namely inflation, Information Technology, Policy and Force Majeure, as moderating variables in budget preparation research (Dwiyanthi, 2022). Inflation can affect the budgeting process because the state of the country's economy, which is going up or down, certainly affects the supply of products or services created by the company. These economic conditions can be seen from the monthly or annual inflation rate in general or specifically seen from the classification of products and services. The role of technology in budget preparation Such application services can help employees in the budget preparation process and minimize errors. However, the development of technology is getting higher, and it must be harmonized with the ability of human resources to manage applications. So that technological developments do not become a boomerang for institutions/agencies. Policy in the budgeting process is critical if there is a change in policy by the leadership in the current fiscal year. Then, there will be adjustments to the budget of a related institution/agency. In the preparation of the budget, Force Majeure has an important role, for example, when COVID-19 occurred in Indonesia. The National Police must readjust its budget in order to meet the needs for masks, hand sanitizers, vitamins, and swabs that were not previously allocated. The existence of external factors as moderating variables in research can strengthen or otherwise weaken the influence of the Internal Control System on Budget Preparation.

Based on the background above, this study aims to determine the effect of Human Resources, Information Technology, and Internal Control Systems on budget preparation by considering external factors as moderating variables. This research provides significant benefits both theoretically and practically. Theoretically, it contributes to the academic field by expanding the existing literature on the interaction between organizational resources and external factors in budget preparation processes. Practically, the findings of this study can help organizations enhance their budgeting accuracy and efficiency by highlighting the critical roles of human resources, information technology, and internal control systems. Additionally, policymakers and management professionals can utilize these insights to develop better strategies and frameworks for effective budget management, ensuring that external influences are adequately accounted for.

METHOD

This study uses a quantitative method with a survey approach. The population in this study were 50 work units under the auspices of the National Police Training Headquarters. The sample was taken using the purposive sampling technique, which is the selection of samples based on specific criteria. The respondents selected were planning staff who were directly involved in the preparation of budgets in these work units. The data collection technique used was a questionnaire distributed to selected respondents. Data analysis was carried out using the SmartPLS 4.0 program to test the effect of independent variables (Human Resources, Information Technology, Internal Control System) on the dependent variable (Budget Preparation) with moderating variables (External Factors). The conceptual framework in this study is:

Figure 1. Conceptual Framework

Thus, the hypothesis in this study:

H1	:	Human Resources has a positive effect on the budget preparation of Lemdiklat Polri and its ranks.
H2	:	Information technology has a positive effect on the budget preparation of Lemdiklat Polri and its ranks.
H3	:	Internal Control System has a positive effect on the budget preparation of Lemdiklat Polri and its ranks.
H4	:	External factors moderate the influence of the Internal Control System on budget preparation.

RESULTS AND DISCUSSION

The research results are a process of data collection that has been carried out by researchers in which data processing and research analysis are carried out systematically and objectively to obtain the results of hypothesis testing. To get the results of this study, researchers used the Partial Least Suqare-Structural Equation Model (PLS-SEM) and the following stages of data processing in SmartPLS 4.0, which consists of Outer Model Analysis, Inner Model Analysis and Hypothesis Testing.

Evaluation of Measurement Model (Outer Model)

Evaluation measurement, or what is called the outer model, is interpreted as a measurement model that can see the relationship between indicators and other variables. This outer model is a test of validity and reliability. The outer model test begins with estimating parameters, namely by calculating the PLS algorithm with the following results.

Figure 1. PLS Algorithm Calculation Output Display

Source: PLS Output

From the analysis output, the measurement model (outer model) can be evaluated by testing convergent validity, discriminant validity and reliability.

Convergent Validity Test Results

Convergent validity seeks to verify the validity of each relationship between indicators and their corresponding constructs or latent variables. In the measurement model with reflective indicators, convergent validity is evaluated by examining the correlation between item scores or component scores and the scores of latent variables or constructs as estimated by the PLS program. Convergent validity is examined by the outer loadings value, where an item is said to be valid if it has an outer loadings value> 0.7.

Based on Table 1, it can be seen that the most dominant indicators contributing to their respective latent constructs are as follows:

1. The best indicator in forming the Human Resources variable (X1) is X1.4, which has an outer loadings value of 0.945 and is owned by item X1.4, namely "The Human Resources Involved Have Understood the Policies and Procedures Related to Budget Preparation."ï¿½

2. The best indicator in forming the Information Technology variable (X2) is X2.3, which has an outer loadings value of 0.900 and is owned by item X2.3, namely, "I am satisfied with the performance and functionality of the information technology used in budget preparation."

3. The best indicator in forming the Internal Control System variable (X3) is X3.3, which has an outer loadings value of 0.956 and is owned by item X3.3, namely "Increasing control activities can improve performance."ï¿½

4. The best indicator in forming the External Factors (Z) variable is Z.2, which has an outer loadings value of 0.960 and is owned by item Z.2, namely "Changes in government regulations and policies require adjustments in budget preparation."ï¿½

5. The best indicator in forming the Budget Preparation variable (Y) is Y.6, which has an outer loadings value of 0.944 and is owned by item Y.6, namely, "Budget preparation uses not too many resources but maximizes."

Table 1. Loading Factor Value Before Reduction

Variables	Item	Cut Off	Outer Loadings	Conclusion
Human Resources	X1.1	0.7	0.485	Invalid
	X1.2	0.7	0.576	Invalid
	X1.3	0.7	0.835	Valid
	X1.4	0.7	0.936	Valid
	X1.5	0.7	0.925	Valid
	X1.6	0.7	0.891	Valid
	X1.7	0.7	0.884	Valid
Information Technology	X2.1	0.7	0.585	Invalid
	X2.2	0.7	0.862	Valid
	X2.3	0.7	0.878	Valid
	X2.4	0.7	0.858	Valid
	X2.5	0.7	0.823	Valid
	X2.6	0.7	0.695	Invalid
Internal Control System	X3.1	0.7	0.915	Valid
	X3.2	0.7	0.916	Valid
	X3.3	0.7	0.956	Valid
	X3.4	0.7	0.932	Valid
	X3.5	0.7	0.928	Valid
External Factors	Z.1	0.7	0.938	Valid
	Z.2	0.7	0.960	Valid
	Z.3	0.7	0.822	Valid
	Z.4	0.7	0.880	Valid
	Z.5	0.7	0.944	Valid
Budget Preparation	Y.1	0.7	0.828	Valid
	Y.2	0.7	0.720	Valid
	Y.3	0.7	0.832	Valid
	Y.4	0.7	0.888	Valid
	Y.5	0.7	0.938	Valid
	Y.6	0.7	0.942	Valid

Source: PLS Output Results

Based on the figure and table above, four items have an outer loading value of less than 0.7, so they must be removed. After the items are removed or excluded, the data is run again, and the results are as follows.

Figure 2. PLS Algorithm Calculation Output Display after Reduction

Source: PLS Output Results

Based on this output, the outer loadings value of each indicator after reduction can be found in Table 2 below:

Table 2. Loading Factor Value after Reduction

Variables	Item	Cut Off	Outer Loadings	Conclusion
Human Resources	X1.3	0.7	0.854	Valid
	X1.4	0.7	0.945	Valid
	X1.5	0.7	0.942	Valid
	X1.6	0.7	0.903	Valid
	X1.7	0.7	0.892	Valid
Information Technology	X2.2	0.7	0.843	Valid
	X2.3	0.7	0.900	Valid
	X2.4	0.7	0.885	Valid
	X2.5	0.7	0.875	Valid
Internal Control System	X3.1	0.7	0.915	Valid
	X3.2	0.7	0.916	Valid
	X3.3	0.7	0.956	Valid
	X3.4	0.7	0.932	Valid
	X3.5	0.7	0.928	Valid
External Factors	Z.1	0.7	0.938	Valid
	Z.2	0.7	0.960	Valid
	Z.3	0.7	0.821	Valid
	Z.4	0.7	0.880	Valid
	Z.5	0.7	0.944	Valid
Budget Preparation	Y.1	0.7	0.829	Valid
	Y.2	0.7	0.715	Valid
	Y.3	0.7	0.831	Valid
	Y.4	0.7	0.888	Valid
	Y.5	0.7	0.939	Valid
	Y.6	0.7	0.944	Valid

Source: PLS Output Results

Discriminant Validity Test Results

Discriminant validity can be assessed by examining the AVE value for each construct or latent variable. A model demonstrates stronger discriminant validity when the square root of the AVE for each construct is greater than the correlation between any two constructs within the model. The rule of thumb is said to be valid if the AVE value is more than 0.5. The variable AVE values in this study are:

Table 3. Loading Factor Value after Reduction

Variables	AVE	Conclusion
Human Resources	0.825	Valid
Information Technology	0.768	Valid
Internal Control System	0.864	Valid
External Factors	0.828	Valid
Budget Preparation	0.742	Valid

Source: PLS Output Results

Based on the table, it can be seen that the AVE value for all variables is more significant than 0.5. Thus, the constructs in this research model have good discriminant validity.

Reliability Test

Besides assessing validity, the outer model also evaluates the reliability of the construct or latent variable. This is done by examining the composite reliability value and Cronbach's alpha of the indicator block measuring the construct. A construct is considered reliable if the composite reliability value exceeds 0.7 and the Cronbach's alpha value is above 0.6. The reliability test results are as follows.

Table 4. Composite Reliability Value

Variables	Composite Reliability	Cronbach Alpha	Conclusion
Human Resources	0.953	0.947	Reliable
Information Technology	0.903	0.899	Reliable
Internal Control System	0.961	0.961	Reliable
External Factors	0.993	0.950	Reliable
Budget Preparation	0.937	0.928	Reliable

Source: PLS Output Results

Test Coefficient of Determination (R-Square)

The R-Square (Rï¿½) value indicates the extent to which exogenous variables explain the variation in endogenous variables. The greater the R2 value, the better the level of determination.

Table 5. R-Square

Variables	R²
Budget Preparation	0.836

The results of the calculation of R2 for each endogenous latent variable in the table above show a value of 0.836, which means that the value variable in budget preparation can be explained or influenced by human resource variables, information technology and internal control systems by 83.6%. Meanwhile, the remaining 16.4% is influenced by other factors outside the modelling of this study.

Predictive Relevance Test (Q2)

The Qï¿½ value assesses how effectively the model generates observed values and parameter estimates. A Qï¿½ value greater than 0 suggests that the model performs well, and a higher Qï¿½ indicates that the model's predictions are deemed relevant.

Q2 = 1 - (1-R2)

Q2 = 1 - (1-0.836)

Q2 = 0.836

The results of the Q2 calculation above show that the research model has a Q2 value of 0.836 or 83.6%, where the independent variables in this study can predict the budget preparation variable. At the same time, the rest is the contribution of other variables that are not included in this research model. Based on the calculation with the Q2 equation, this model also has a very high predictive relevance because the value is greater than 0 (zero).

Hypothesis Test Results

Hypothesis testing is conducted by examining the t-statistic value obtained from the bootstrapping process. A hypothesis is considered accepted (supported) if the t-statistic exceeds 1.96 at a 5% significance level (two-tailed). The results of the SmartPLS program bootstrapping process can be seen in Table 6 below:

Table 6. Value of t-statistics

Hypothesis	Influence	*Path* *Coefficient*	T- Statistics	P- Value	Hypothesis Conclusion
H1	HR → Budgeting	0.081	0.507	0.613	Rejected
H2	Information technology → budgeting	0.367	3.647	0.000	Accepted
H3	Internal control system → budgeting	0.399	2.827	0.005	Accepted

Source: PLS Output Results

Based on the test results in Table 6, the effect of each variable is described as follows:

1. H1: Human Resources has a positive effect on the preparation of the budget of the Police Training Center and its ranks (DENIED). This is because the T statistic value is smaller than the T table (1.96), and the P value is more significant than 0.05 (0.05 < 0.613) with a positive coefficient value. Human resources have a positive but insignificant effect on the preparation of the budget of the Police Training Center and its ranks.

2. H2: Information Technology has a positive effect on the preparation of Lemdiklat Polri's budget and its ranks (ACCEPTED). This is because the T statistic value is greater than the T table (1.96), and the P value is less than 0.05 (0.05> 0.000) with a positive coefficient value. So, information technology has a positive and significant effect on the preparation of the budget of the Police Training Center and its ranks.

3. H3: The Internal Control System has a positive effect on the budget preparation of the Polri Training and Training Center and its ranks (ACCEPTED). This is because the T statistic value is greater than the T table (1.96), and the P value is less than 0.05 (0.05> 0.005) with a positive coefficient value. So, the internal control system has a positive and significant effect on the budget preparation of the National Police Training Center and its ranks.

Moderated Regression Analysis (MRA) Test Results

To test External Factors as a moderating variable for the relationship between the internal control system and budget preparation. The criteria used as a basis for comparison are as follows:

The hypothesis is rejected if the t-statistic < 1.96 or the p-value> 0.05. The hypothesis is accepted if the t-statistic > 1.96 or the p-value < 0.05.

Table 6. MRA Results

Hypothesis

Influence

T - Statistics

P - Value

Hypothesis Conclusion

External factors X internal control system → budget preparation

0.107

0.915

Rejected

Based on the test results in Table 6, the results of hypothesis H4: External Factors moderate the influence of the Internal Control System on Budgeting (DENIED). This is because the t-statistic value is 0.107 < 1.96, and the p-value is 0.915> 0.05. Thus, external factors cannot moderate the effect of the internal control system on the preparation of the Polri Lemdiklat budget and its ranks.

The Effect of Human Resources on Budget Preparation

Human Resources is a crucial internal factor that significantly impacts an organization's success or failure in reaching its goals, making it essential to manage HR effectively and efficiently (Sholihah et al., 2015). The existence of good-quality human resources will undoubtedly encourage the achievement of predetermined targets. The results and testing of the first hypothesis (H1) show that the human resource variable has a positive but insignificant effect on budget preparation. Human resources have dominant indicators in budget preparation, such as the expertise of each employee. However, with an excellent level of respondent achievement, more is needed to prove that human resources have a significant effect on budget preparation. This is likely because budget preparation only depends partially on human resources; there are other resources such as budget resources, information in the form of data, equipment and technology, and other supporting facilities (Rumenser, 2014). The results of this study are not in line with the research (Wahyuni et al., 2023), (Ismid et al., 2020), (Lubis & Shara, 2021). However, the results that have no effect are in line with several previous studies, including those conducted (Kartini, 2019), (Rumenser, 2014).

The Effect of Information Technology on Budgeting

The definition of information technology can vary even though each definition has the same core (Sabaruddinsah, 2011) information technology is described as a blend of computer and telecommunications technologies, incorporating hardware, software, databases, network technology, and other telecommunications equipment. It is employed to process, acquire, organize, store, and manage data in various forms to generate relevant, accurate, and timely information for personal, business, and government purposes. It is strategic information that determines decision-making (Indrayani, 2012).

The results and testing of the second hypothesis (H2) show that information technology variables have a positive and significant effect on Budget Preparation. The effective use of Information Technology can improve the efficiency of the budgeting process by providing sophisticated tools for data collection, analysis and reporting. Sophisticated budget software can provide additional support to estimate and monitor budgets more effectively. The results of this study are in line with those conducted by (Lubis & Shara, 2021), who stated that Information Technology affects the Preparation of Regional Revenue and Expenditure Budgets in Medan City.

Effect of Internal Control System on Budget Preparation

According to (Single, 2013), every activity in implementing the budget has two levels. The first is the operating system, which is designed to meet predetermined objectives. The second is a control system designed to ensure that the objectives of the operating system will be achieved. The existing components of the government's internal control system are a form of internal control system components adopted from COSO. According to COSO, five components of the internal control system are described according to Government Regulation No. 60 of 2008 concerning internal control systems, namely the control environment, risk assessment, control activities, information and communication, and monitoring.

The results and testing of the third hypothesis (H3) show that the internal control system variable has a positive and significant effect on Budget Preparation. A robust Internal Control System plays a vital role in ensuring that the budget preparation process runs in accordance with applicable policies and procedures. This helps reduce the risk of error and abuse and improves compliance with established standards. Thus, budgeting can be improved overall, allowing organizations to make better and more sustainable decisions. The results of this study are in line with previous research (Suryani & Pujiono, 2020).

External Factors moderate the influence of the Internal Control System on Budget Preparation.

The external environment is an environmental condition that is outside the control of the organization and has a significant effect on strategic plans and operational plans so that it directly or indirectly affects the quality of output; in this case, what is meant is financial statements (Kolit et al., 2023). The internal control system covers many aspects of the internal management of an organization or company. Internal control is a framework consisting of procedures that are interrelated in carrying out a habit within the company to control the running of the company, which includes and secures assets, checks the accuracy and correctness of administration or accounting, promotes efficiency in operations and helps maintain company policies to be obeyed (Supit, 2015).

The results and testing of the fourth hypothesis (H4) show that in this study, the External Factors variable does not moderate the influence of the Internal Control System on Budget Preparation. This is likely because implementing a change usually cannot be done quickly but through bureaucracy first and through several stages, such as waiting for the Ministry / Institution Work and Budget Plan (RKA) revision process in the current fiscal year or having to wait for the preparation of a needs plan in the next fiscal year. Budget preparation documents sometimes change when a leadership instruction is issued.

External factors in this study are Application updates, Regulatory changes, Geopolitical changes, Pandemics and Inflation rates. External factors themselves can be a threat to the internal control system that affects budgeting, such as a lack of risk management against geopolitical changes or rising inflation if you have good risk management in the internal control system. Then, the budget preparation document can be easily adjusted if external factors arise. The results of this study are not in line with previous research (Yendrawati, 2013). However, the results that have no effect are in line with research (Untary & Ardiyanto, 2015).

CONCLUSION

This research was conducted to determine whether human resources, information technology, and internal control systems influence budget preparation with external factors as moderating variables. Data was obtained from planning staff at Lemdiklat Polri and its jurisdictions (Lemdiklat Polri, 34 SPNs, and 15 Pusdik Schools). This study aims to test the effect of Human Resources on Budget Preparation, the effect of Information Technology on Budget Preparation, the effect of the Internal Control System on Budget Preparation, and whether External Factors moderate the effect of the Internal Control System on Budget Preparation. Based on the results of test analysis and research with the SmartPLS 4.0 program that has been carried out in the previous chapter, the following conclusions can be obtained: (1) Human Resources have no effect on Budget Preparation, (2) Information Technology affects Budget Preparation, (3) Internal Control System affects Budget Preparation, and (4) External Factors do not moderate the effect of the Internal Control System on Budget Preparation. The results of this study provide implications for Lemdiklat Polri and its ranks that need to optimize the importance of Information Technology. Effective use of information technology can improve the efficiency of the budget preparation process by providing sophisticated tools for data collection, analysis and reporting. Sophisticated budget software can provide additional support to forecast and monitor budgets more effectively. The results of this study also provide implications for the National Police Training Agency and its ranks that need to optimize the importance of the Internal Control System. A robust internal control system plays a vital role in ensuring that the budget preparation process is in accordance with applicable policies and procedures. This helps to reduce the risk of error and abuse and improve compliance with established standards. As such, budgeting can be improved overall, enabling the organization to make better and more sustainable decisions.

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