International Journal of Economics.
Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
stie-aas.
id/index.
php/IJEBAR ANALYSIS OF THE EFFECT OF BUDGETING SYSTEM AND OPERATIONAL RISK ON THE FINANCIAL PERFORMANCE OF HOUSING DEVELOPER COMPANIES Oma NuryantoA.
RukminiA.
Sri Laksmi PardanawatiA
1,2,3
AAS Indonesia Institute of Business and Technology.
Surakarta E-mail: 1omanuryanto7@gmail.
com, 2rukmini.
aas@gmail.
com, 3laksmi.
aas@gmail.
Abstract:
This study aims to examine the effect of the budgeting system and operational risk on the financial performance of housing developer companies in the Solo Raya region.
The research population consists of 34 companies that are members of the Real Estate Indonesia (REI) Solo Raya Chapter.
Data were collected using a structured questionnaire and analyzed using multiple linear regression with SPSS.
The results show that the budgeting system has a positive and significant effect on financial performance, with a significance value of 0.
028 (< 0.
Meanwhile, operational risk does not have a significant partial effect, although it contributes jointly with the budgeting system in influencing financial performance, as indicated by a significance value of 0.
002 in the F-test.
The coefficient of determination (Adjusted RA) is 299, indicating that 29.
9% of the variation in financial performance can be explained by the two independent variables.
These findings highlight the importance of strengthening the budgeting process and maintaining effective risk management practices in order to enhance financial performance.
Keywords:
budgeting system, operational risk, financial performance, housing developer Submitted: 2025-05-31.
Revised: 2025-06-24.
Accepted: 2025-06-26 Introduction The housing industry in Indonesia continues to grow alongside the increasing population and rapid urbanization.
Housing developer companies play a crucial role in providing dwellings that meet market demands.
However, these companies often face various challenges, both operational and financial, that can affect their financial performance.
In this context, effective management of budgeting systems and operational risk management are two important factors influencing the financial performance of housing developer companies (Kasmir.
A well-designed budgeting system enables companies to plan and allocate resources efficiently, as well as monitor and control cash flows to align with predetermined goals (Mulyadi, 2.
Inaccurate budgeting can lead to resource wastage, difficulties in fulfilling financial obligations, and decreased profitability.
This is particularly critical considering that large-scale housing projects typically involve significant investments and extended construction periods, requiring companies to have well-thought-out financial planning to avoid fatal mistakes in fund management (Sutrisno, 2.
International Journal of Economics.
Business and Accounting Research (IJEBAR) Page 452 International Journal of Economics.
Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
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php/IJEBAR In addition to budgeting, operational risk is also a factor that influences financial Operational risks in the context of housing developers include issues such as construction delays, surges in raw material prices, changes in government regulations, and fluctuations in market demand that can disrupt project progress (Kurniawan, 2.
Companies that fail to manage these risks effectively are at risk of incurring substantial losses, which in turn will reduce their financial performance.
Therefore, it is important for companies to implement effective risk control systems to minimize the negative impacts on their operations and finances.
Proper management of both factorsAiefficient budgeting systems and optimal operational risk managementAiis expected to improve the financial performance of housing developer companies.
Based on this background, this study aims to analyze the influence of budgeting systems and operational risks on the financial performance of housing developer companies, thereby providing deeper insights into the importance of these factors in achieving sustainable financial goals.
Research Method Population and Sample The population of this study consists of 34 housing developer companies operating in Surakarta, registered under the Real Estate Indonesia (REI) Komisariat Solo Raya.
Due to the relatively small population size, this study employs a census sampling technique, where the entire population is used as the sample (Sugiyono, 2.
Data and Data Collection Techniques This study utilizes a quantitative approach with an associative method.
The data consist of primary data collected through questionnaires distributed to managers responsible for budgeting and operational risk management, and secondary data obtained from company financial reports and documentation.
The questionnaire employs a five-point Likert scale ranging from 1 (Strongly Disagre.
to 5 (Strongly Agre.
to measure the implementation of budgeting systems and operational risk management (Sugiyono, 2.
Variables and Operational Definitions The independent variables in this study are budgeting system and operational risk, while the dependent variable is financial performance.
The operationalization of variables is based on established indicators, including documentation, cross-divisional participation, budget evaluation, risk documentation, and financial performance indicators such as profitability and liquidity ratios.
Validity and Reliability Tests Instrument validity was tested using PearsonAos Product-Moment correlation, with items considered valid if the correlation coefficient exceeds the critical value at a 5% significance level.
Reliability was assessed with CronbachAos Alpha, where values above 60 indicate acceptable reliability (Ghozali, 2.
The reliability test yielded a CronbachAos Alpha of 0.
933, confirming that the instrument is valid and reliable.
Classical Assumption Tests Classical assumption tests were conducted to ensure the regression modelAos adequacy, including normality (Shapiro-Wilk or Kolmogorov-Smirnov tes.
, multicollinearity (Variance Inflation Facto.
, homoscedasticity (Breusch-Pagan and White test.
, and autocorrelation (Durbin-Watson tes.
These tests ensure the validity and reliability of the regression analysis results (Wooldridge, 2.
International Journal of Economics.
Business and Accounting Research (IJEBAR) Page 453 International Journal of Economics.
Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
stie-aas.
id/index.
php/IJEBAR Data Analysis Techniques Multiple linear regression analysis was employed to examine the influence of budgeting systems and operational risk on financial performance.
Hypothesis testing included the F-test to assess the overall model significance, t-tests to evaluate the significance of individual independent variables, and the coefficient of determination (RA) to determine the modelAos explanatory power regarding data variability (Widarjono, 2.
Results and Discussion Results Respondent Data This study involved respondents from 34 housing developer companies registered under the Real Estate Indonesia (REI) Komisariat Solo Raya.
Each respondent holds a role that involves direct knowledge of the companyAos financial and operational conditions, such as financial managers, project managers, or business owners.
The demographic profile of the respondents was collected through a questionnaire, and is summarized in the table below:
Table 1.
Respondent Demographics Gender
Frequency Persentage Male
73,5%
Female 26,5% Total The majority of respondents were male, indicating a dominance of men in decision-making roles within the property development sector.
Classical Assumption Tests Classical assumption tests were conducted to assess the reliability and validity of the regression model.
These include normality, multicollinearity, homoscedasticity, and autocorrelation tests.
Normality Test Normality was tested using the One-Sample Kolmogorov-Smirnov (K-S) method.
The results are as follows:
Table 2.
Kolmogorov-Smirnov Test Results Test Statistic Value Sample Size (N) K-S Statistic (Absolut.
Asympotic Significance .
-taile.
Monte Carlo Significance .
-taile.
Since the Monte Carlo significance value is 0.
596 (> 0.
, the residuals are normally distributed, fulfilling the normality assumption.
Multicollinearity Test This test examines whether high correlations exist between independent variables.
Indicators used are Tolerance (> 0.
and Variance Inflation Factor (VIF < .
Table 3.
Multicollinearity Test Results Variable Tolerance VIF Budgeting System 0.
Operational Risk 0.
International Journal of Economics.
Business and Accounting Research (IJEBAR) Page 454 International Journal of Economics.
Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
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php/IJEBAR All tolerance values exceed 0.
10 and VIF values are below 10, indicating the absence of .
Homoscedasticity Test The Glejser test was used to examine whether residuals have constant variance.
The significance values for both variables were above 0.
05 (Budgeting System: 0.
Operational Risk: 0.
, suggesting that the model meets the homoscedasticity .
Autocorrelation Test The Durbin-Watson test was used to detect autocorrelation in the residuals.
Since dU < DW < 4 Ae dU .
580 < 1.
746 < 2.
, no autocorrelation is detected, indicating that residuals are independent.
Hypothesis Testing .
Multiple Linear Regression Analysis The regression equation obtained is:
Y = 4.
379XCA 0.
295XCC
Where:
Y = Financial Performance .
XCA = Budgeting System .
XCC = Operational Risk Interpretation:
The constant .
suggests the base level of financial performance when both independent variables are zero.
A one-unit increase in the budgeting system (XCA) is associated with an increase in financial performance by 0.
379 units, holding other factors constant.
A one-unit increase in operational risk (XCC) corresponds to a 0.
295 increase in financial performance, though this may not be statistically significant.
F-Test (Model Fit Tes.
The F-test assesses whether the independent variables jointly influence the dependent F-statistic: 8.
021 and Significance: 0.
Since the p-value is < 0.
05, the model is statistically significant, indicating that the budgeting system and operational risk jointly affect financial performance.
t-Test (Partial Significance Tes.
This test evaluates the individual effect of each independent variable.
Table 4.
t-Test Results Variable Coefficient (B) t-value Sig.
Interpretation Budgeting System 028 Significant .
< 0.
Operational Risk 095 Not Significant .
> 0.
The budgeting system has a significant partial effect on financial performance.
Operational risk does not have a statistically significant partial effect.
Coefficient of Determination (RA) This test measures how much variance in the dependent variable is explained by the independent variables.
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Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
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R-Squared Results Statistic Value R Square Adjusted R Square Standard Error Estimate 1.
The Adjusted R Square of 0.
299 indicates that 29.
9% of the variation in financial performance is explained by the budgeting system and operational risk.
The remaining 1% is influenced by other factors not included in this model.
Discussion The Influence of Budgeting System on Financial Performance The results of the t-test indicate that the budgeting system has a significant influence on financial performance, with a significance value of 0.
028 (< 0.
This finding suggests that the more effective and structured the budgeting system implemented by the company, the better its financial performance will be.
This result is in line with Mulyadi .
, who stated that a well-designed budgeting system serves as an essential tool for planning and control.
It ensures efficient and measurable use of resources, enabling organizations to monitor expenditures, evaluate outcomes, and make informed financial decisions.
Moreover, the findings support the research by Dendy Syaiful Akbar and Ruhiyat .
, which showed that performance-based budgeting positively impacts the financial performance of local governments.
Although their study was conducted in the public sector, the principles of performance-based budgeting are equally applicable in the private sector, including among property developers.
A structured and participatory budgeting process allows management to evaluate financial target achievements and identify areas requiring improvement, thereby enhancing overall financial health and accountability.
The Influence of Operational Risk on Financial Performance Based on the t-test results, operational risk does not have a significant partial influence on financial performance, as indicated by the significance value of 0.
095 (> 0.
This implies that operational risk, when assessed individually, does not exert a strong influence on changes in the financial performance of the company.
However, the F-test shows that operational risk, in combination with the budgeting system, contributes significantly to the model (F significance = 0.
This indicates that while operational risk may not independently impact financial performance, it still plays a role when considered alongside other managerial factors.
This finding is consistent with the study by Dayana and Untu .
published in Jurnal EMBA, which concluded that operational risk did not have a statistically significant partial effect on the financial performance of regional development banks, though it contributed jointly with other types of risks.
The implication is that the impact of operational risk can be mitigated or absorbed if the company has effective internal control systems and risk management strategies in place.
These mechanisms can buffer the adverse effects of operational uncertainties, preserving the stability of financial outcomes.
International Journal of Economics.
Business and Accounting Research (IJEBAR) Page 456 International Journal of Economics.
Business and Accounting Research (IJEBAR) Peer Reviewed Ae International Journal Vol-9.
Issue-2, 2025 (IJEBAR) E-ISSN: 2614-1280 P-ISSN 2622-4771 https://jurnal.
stie-aas.
id/index.
php/IJEBAR In summary, the study highlights the critical role of a robust budgeting system in driving financial performance and suggests that operational risks, while important, may have a more nuanced or indirect effect, especially in companies with adequate governance frameworks.
Conclusion Based on the findings regarding the influence of the budgeting system and operational risk on the financial performance of housing developer companies, the following conclusions can be The Budgeting System has a significant effect on Financial Performance.
The t-test results indicate a positive and statistically significant relationship between the budgeting system and financial performance, with a significance value of 0.
028 (< 0.
This suggests that improvements in the quality and effectiveness of the budgeting system positively contribute to enhancing the financial performance of the company.
Operational Risk does not have a significant partial effect on Financial Performance.
The t-test results show that operational risk has a significance value of 0.
095 (> 0.
indicating no significant individual effect on financial performance.
However, the simultaneous test (F-tes.
confirms that operational risk still contributes collectively with the budgeting system in influencing financial performance.
References