https://dinastipub.
org/DIJEFA Vol.
No.
2, 2025
DOI: https://doi.
org/10.
38035/dijefa.
https://creativecommons.
org/licenses/by/4.
The Impact of Restaurant Tax Contribution on Regional Tax and Strategies to Achieve Restaurant Tax Targets in Bekasi City (Case Study at the Regional Revenue Agency of Bekasi Cit.
Rosma Titis Hapsari1.
Adler Haymans Manurung2.
Wastam Wahyu Hidayat3.
Idel Eprianto4.
Jhonni Sinaga5 Master of Management Student.
Faculty of Economics and Business Bhayangkara Jakarta Raya University.
Jakarta.
Indonesia, titishapsarisoroso@gmail.
Lecturer the Faculty of Economics and Business Bhayangkara Jakarta Raya University.
Jakarta.
Indonesia, adler.
manurung@dsn.
Lecturer the Faculty of Economics and Business Bhayangkara Jakarta Raya University.
Jakarta.
Indonesia, wastam.
wahyu@dsn.
Lecturer the Faculty of Economics and Business Bhayangkara Jakarta Raya University.
Jakarta.
Indonesia, idel.
eprianto@dsn.
Lecturer the Faculty of Economics and Business Bhayangkara Jakarta Raya University.
Jakarta.
Indonesia, jhonni.
sinaga@dsn.
Corresponding Author: titishapsarisoroso@gmail.
Abstract: This study aims to analyze the contribution of restaurant taxes to regional tax revenue and strategies to achieve restaurant tax targets in Bekasi City, referencing Law No.
1 of 2022 on Financial Relations Between the Central and Regional Governments.
The research emphasizes increasing Local Own-Source Revenue (PAD) through regional taxes, specifically restaurant taxes.
Using a quantitative approach with multiple regression analysis, the study evaluates the impact of external and internal variables such as tax extensification, tax collection, and technological innovation on restaurant tax revenue.
The findings indicate that technological innovation and tax collection significantly influence regional tax revenue, with a coefficient of determination (RA) of 92.
While tax extensification does not show a significant individual effect, collectively, these variables explain most of the variation in regional tax revenue.
The study identifies gaps in understanding the factors affecting restaurant tax target achievement and the need for more effective tax management strategies.
Recommendations for local governments include enhancing technology use in tax administration and strengthening the tax collection system to improve taxpayer compliance.
This research contributes to the development of more effective and efficient tax policies to support local economic growth in Bekasi City.
Keyword: Restaurant Tax.
Local Original Revenue.
Tax Extensification.
Tax Collection.
Technology and Innovation.
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INTRODUCTION
Fulfilling funding for development and administration in the regions is an important aspect that can be achieved through self-generated regional revenue or external sources.
In this context.
Regional Governments are expected to reduce dependence on the Central Government by increasing Regional Own-Source Revenue (PAD).
One of the strategic steps taken is the enactment of Law No.
1 of 2022 concerning Financial Relations Between the Central Government and Regional Governments (HKPD), which provides a strong legal basis for Regional Governments to optimize regional tax revenue and improve regional financial management systems more effectively.
Regional taxes, particularly restaurant taxes, become one of the main sources of revenue for the Bekasi City Government in carrying out governmental and developmental functions.
Restaurant taxes in Bekasi City are collected based on a self-assessment system, where taxpayers are responsible for calculating, reporting, and paying taxes in accordance with applicable regulations.
Restaurant taxes have become one of the largest contributors to PAD, in line with the rapid growth of the restaurant business sector.
However, restaurant tax revenue does not always match the set targets.
For example, in 2020, amid the COVID-19 pandemic that affected almost all economic sectors, restaurant tax revenue was recorded as relatively good, although the target was lower compared to the previous year.
This indicates that even though the restaurant sector experienced a decline due to social restriction policies, there were certain factors that caused tax revenue to not be significantly affected.
However, in subsequent years, although the restaurant sector in Bekasi City experienced growth, the realization of restaurant tax revenue often did not reach 100% of the set targets.
This phenomenon indicates a discrepancy between the potential tax that can be collected from the restaurant sector and the revenue recorded in the regional budget.
Previous studies related to regional tax revenue, including restaurant taxes, have highlighted several aspects, but have not covered all the factors that deeply affect the achievement of restaurant tax targets.
For instance.
Chitra Meilina .
examined the effectiveness of hotel and restaurant taxes in Bekasi City, but the focus was more on general tax regulations and policy effectiveness.
Kurniawan .
studied tax extensification strategies, including restaurant taxes, but focused more on expanding the tax base rather than analyzing specific challenges faced by the restaurant This research identifies a significant research gap, namely the lack of in-depth analysis of specific factors causing instability or failure to achieve restaurant tax revenue targets.
Moreover, there has been no exploration of unique obstacles and opportunities within this Another gap is the lack of focus on external and internal factors specifically affecting the achievement of restaurant tax targets in Bekasi City.
Previous studies have mostly highlighted regional taxes as a whole, without identifying elements that pose specific challenges within the restaurant sector, such as taxpayer compliance levels, challenges in tax administration and collection, and issues related to the utilization of technology.
Although the restaurant sector in Bekasi City shows rapid development, the realization of tax revenue from this sector is often unstable.
This indicates the presence of factors that are not fully understood or addressed, such as the impact of modernization on taxpayer compliance, gaps in the tax collection system, and suboptimal use of technology in administration and oversight processes.
The role of technology in influencing the effectiveness of restaurant tax revenue is also rarely discussed in the context of Bekasi City.
Technological innovations, such as the integration of tax information systems and online services for tax reporting and payment, can increase taxpayer compliance and facilitate oversight.
However, so far, there has been no comprehensive study examining how this technology can play a role in achieving restaurant tax revenue targets, particularly in terms of improving administrative efficiency and strengthening tax compliance.
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This study aims to fill this gap by focusing on the utilization of technology in tax administration and how it can become a strategy to achieve stable restaurant tax targets in line with the expectations of the regional government.
Thus, the research gap identified in this study is the lack of a combined analysis of the contribution of restaurant taxes to regional tax revenue, the specific influence of internal and external factors on the discrepancy in restaurant tax revenue targets, and the role of technology in enhancing the effectiveness of restaurant tax This research will provide an in-depth analysis of these factors and offer strategic recommendations for the Bekasi City Government to increase the potential of restaurant tax revenue and achieve more stable targets each year.
The obtained data shows that in 2023, regional tax revenue provided the largest contribution, while in 2020, the contribution of regional tax revenue to PAD was recorded as the lowest in the last five years.
Tax extensification aims to expand the tax base by increasing the number of registered taxpayers.
These extensification activities include identifying and registering new taxpayers, tax outreach, and education, as well as monitoring and taking action against unregistered taxpayers.
It is expected that through extensification, the number of registered taxpayers will increase, thereby contributing to the rise in regional tax revenue.
Furthermore, effective tax collection can encourage restaurant taxpayers to be more compliant, which in turn can increase regional tax revenue.
Active collection efforts, such as issuing warning letters, force letters, and seizure actions, can compel taxpayers to settle their tax arrears The implementation of strict sanctions also has the potential to raise taxpayer awareness and compliance in fulfilling their tax obligations.
Jumlah Wajib Pajak Restoran Figure 1.
Total Restaurant Taxpayers Source: Bekasi City Regional Revenue Realization Report for Fiscal Year 2019 Ae 2023 Data on the number of restaurant taxpayers in Bekasi City from 2019 to 2023 shows a consistent upward trend, although there was a slight decline in 2023.
In 2019, the number of restaurant taxpayers was recorded at 2,224, increasing to 2,507 in 2020, and continuing to rise to 2,974 in 2022.
However, in 2023, this number slightly decreased to 2,958.
Nevertheless, technological developments and innovations such as tax information systems and online tax services can help improve taxpayer efficiency and compliance.
Integrated tax information systems and online tax services facilitate taxpayers in fulfilling their obligations, both in reporting and paying taxes.
The contribution of restaurant taxes to regional tax revenue in Bekasi City is expected to continue to increase through various strategies mentioned, such as tax extensification, effective collection, and the application of technology and innovation in regional tax The comprehensive and coordinated implementation of these strategies is expected to boost restaurant tax revenue, which in turn will increase overall regional tax revenue in Bekasi City.
Data on the realization of restaurant tax revenue from 2019 to 2023 shows fluctuations between targets and realizations, indicating challenges and opportunities in 1056 | P a g e https://dinastipub.
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achieving better targets in the future.
Initial observations indicate issues in setting restaurant tax targets and tax collection, such as the absence of standard calculation methods in planning restaurant tax targets, unexplored restaurant potential, and suboptimal oversight.
This research aims to address several key objectives and provide significant contributions both theoretically and practically.
The primary objectives of this study include analyzing the impact of tax extensification, tax collection, and technological innovation on PBJT Food and Beverage/Restaurant Tax revenue.
It seeks to identify which independent variable exerts the most considerable influence on PBJT Food and Beverage/Restaurant Tax revenue, analyze the contribution of restaurant tax to total regional tax revenue, assess the alignment between the established PBJT Food and Beverage/Restaurant Tax with its potential, and identify the obstacles faced in achieving restaurant tax targets.
Moreover, the study will evaluate the strategies implemented by the Bekasi City Revenue Agency (Bapend.
to meet the predetermined PBJT Food and Beverage/Restaurant Tax targets.
The research findings are anticipated to add new insights and serve as a reference for future studies, contributing to the development of tax science, especially concerning factors affecting regional tax revenue and its contribution to PAD.
For practitioners, particularly local governments, the results can provide valuable input for devising strategies and policies to enhance restaurant tax revenue and optimize its contribution to PAD.
For regulators, the findings may inform the creation of more effective regional tax management regulations at the national level.
By achieving these objectives, this research aims to bridge existing gaps in the literature and offer strategic recommendations for improving regional tax revenue systems, particularly focusing on the role of technology and effective tax collection strategies in ensuring stable and increased tax revenue.
Based on these considerations, the researcher is interested in discussing "The Impact of Restaurant Tax Contribution on Regional Tax and Strategies to Achieve Restaurant Tax Targets in Bekasi City.
METHOD
Research Design In the book AuDesign Research, 4th EditionAy by Creswell .
, it is explained that data and research need to be collected to support the development of design.
The method used to collect data will determine how research and data collection can be classified.
The expected results of the research will influence the data collection strategy used.
This study adopts an explanatory research approach with a quantitative method to obtain in-depth, authentic, reliable, and objective data.
The research design employs pure quantitative analysis, where the obtained quantitative data will be analyzed to provide more comprehensive results regarding restaurant tax revenue and its contribution to regional taxes.
The quantitative method in this research is used to analyze numerical data related to restaurant tax revenue, tax targets, tax potential, and its contribution to regional taxes.
Statistical and trend analysis are used to identify patterns and This study also examines the relationships between identified variables, such as tax extensification, tax collection, and technological innovation at the Regional Revenue Agency of Bekasi City.
Thus, the main focus of the research lies in quantitative data, which is expected to provide a clear and informative picture of the factors influencing restaurant tax revenue and its impact on regional taxes.
The study will also examine the relationships between identified variables, such as tax extensification, tax collection, and technological innovation at the Regional Revenue Agency of Bekasi City.
Research Object 1057 | P a g e https://dinastipub.
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This study, undertaken by researchers at the Regional Revenue Agency of Bekasi City, primarily concentrates on attaining restaurant tax targets and their impact on regional tax revenues in Bekasi City.
The research highlights the roles of tax extensification, tax collection, and the implementation of technology and innovation in legal enforcement.
Its primary goal is to offer a thorough understanding of the variables that influence tax revenue performance.
Population and Sample of the Study The population and sample in this study encompass a generalization area consisting of objects or subjects with specific qualities and characteristics determined by the researcher for analysis and conclusion.
According to Sugiyono .
, the population refers to a generalization area consisting of objects or subjects with certain quantities and attributes selected by the researcher.
In this study, the population includes restaurants operating in Bekasi City that are registered as taxpayers paying restaurant taxes.
These restaurants are registered with relevant agencies and meet certain criteria, such as having turnover taxed according to regional regulations.
The sample is a subset of the population's quantity and characteristics.
When the population is extensive and it is not feasible for the researcher to study the entire population due to limited funds, manpower, and time, the researcher can select a sample from that population and generalize the conclusions to the entire population (Sugiyono, 2.
In this study, sampling was conducted using a purposive method, selecting restaurants with observable restaurant tax contributions representing the entire population of restaurants in Bekasi City.
Sample selection considers factors such as restaurant type, location, and the size of tax contributions in previous years based on available data.
Precisely defining the population is crucial as it forms the basis for selecting a representative sample, providing a clear framework for data collection and analysis, and ensuring the validity and reliability of the research findings.
Sources of Data and Data Collection Methods This study focuses on examining the influence of restaurant tax revenue on regional taxes, utilizing quantitative data obtained from the Regional Revenue Agency of Bekasi City.
Internal data sources comprise annual and monthly reports detailing information about restaurant tax revenue, including transaction numbers and tax amounts paid.
This data undergoes statistical analysis to assess the restaurant tax's contribution to overall regional tax In addition, external data is sourced from other government agencies such as the Central Bureau of Statistics (BPS) and relevant ministries through official publications, annual reports, and online databases.
This external data aids in understanding the effects of factors like economic growth, tourist visits, and restaurant industry trends on restaurant tax.
Data processing methods involve parametric statistical tests, with data being analyzed using e-views software to thoroughly evaluate the research variables.
Mathematical Model of the Study This study's mathematical model involves several analyses to understand the influence of independent variables on the dependent variable.
Firstly.
Multiple Linear Regression Analysis examines the linear relationship between two or more independent variables (X1.
X2,.
and a dependent variable (Y), aiming to determine whether there is a positive or negative relationship between these variables.
The multiple linear regression equation used is:
Y=a 1X1 2X2 3X3 4X4 ZZ e where YY is the regional tax revenue variable, a is the constant.
X1 to X3 are the variables of tax extensification, tax collection, and technology and innovation.
ZZ is the intervening variable, and ee is the error term.
Secondly.
Time Series and Panel Data Analysis combines time series data and crosectional data.
Time series data consists of one or more variables observed over a certain period, while cross-sectional data are observations from several units at a specific point in time.
The panel data regression model used is: Yit = a 1X1it 2X2it 3X3it ZZit Cit where Yit is 1058 | P a g e https://dinastipub.
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the regional tax revenue variable for entity i at period t, a is the constant, 1 to Z are the regression coefficients.
X1 to X3 are the variables of tax extensification, tax collection, and technology and innovation for entity ii at period tt.
ZZ is the intervening variable, and Cit is the error for entity i at period t.
Thirdly.
Model Coefficient Estimation reflects the existence of independent variables, intervening variables, and dependent variables.
The model to be estimated is: Yit = a 1X1it 2X2it 3X3it 4X4it ZZit 5(X1it x Zi.
6(X2it x Zi.
7(X3it x Zi.
8(X4it x Zi.
Ci.
This model is described as aa representing the constant, 1 to 8 representing the coefficients of influence for each variable .
ax extensification, tax collection, technology, and intervening variable.
, and Cit representing the error for entity ii at period tt.
Coefficients 1 to 8 indicate the extent to which changes in each variable influence regional tax revenue.
RESULTS AND DISCUSSION
Descriptive Statistics Table 1.
Descriptive Statistics of Research Variables Month / Year Regional Tax (Y) Restaurant Revenue (Z) Extensification (X.
Tax Collection (X.
Technology and Innovation (X.
Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 1059 | P a g e https://dinastipub.
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Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 Feb-21 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 Apr-22 May-22 Jun-22 Jul-22 Aug-22 Sep-22 Oct-22 Nov-22 1060 | P a g e https://dinastipub.
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Dec-22 Jan-23 Feb-23 Mar-23 Apr-23 May-23 Jun-23 Jul-23 Aug-23 Sep-23 Oct-23 Nov-23 Source: Regional Revenue Report of Bekasi City Ae Processed by the author From the data above.
Regional Tax (Y) as the first dependent variable in this study has a minimum value of IDR 69.
97 billion per month, a maximum value of IDR 293.
43 billion, an average of IDR 153.
37 billion, and a standard deviation of IDR 45.
8 billion.
The average value is close to the maximum, indicating that Regional Tax (Y) is relatively close to the maximum Restaurant Revenue (Z) as the second dependent variable in this study has a minimum value of IDR 8.
114 billion per month, a maximum value of IDR 40.
312 billion, an average of IDR 26.
66 billion, and a standard deviation of IDR 7.
04 billion.
The average value is near the maximum, showing that Restaurant Revenue (Y) is relatively close to the maximum value, with a very small standard deviation.
Tax Extensification (X.
as the first independent variable in this study has a minimum value of 2,040 taxpayers per month, a maximum value of 3,077 taxpayers, an average of 3,074 taxpayers, and a standard deviation of 3.
The average value is close to the maximum, indicating that the number of taxpayers is relatively close to the maximum value, with a very small standard deviation.
Tax Collection (PP) as the third dependent variable has a minimum collection value of IDR 1.
686 billion and a maximum of IDR 11.
893 billion per month.
The average monthly collection is IDR 6.
876 billion, with a standard deviation of IDR 3.
145 billion.
The high average indicates a good level of tax collection effectiveness, with a small standard deviation indicating stability in collection values.
Technology Innovation (X.
as the fourth independent variable in this study has a minimum value of IDR 6.
247 billion per month, a maximum value of IDR 26.
987 billion, an average of IDR 18.
880 billion, and a standard deviation of IDR 4.
873 billion.
The average value being close to the maximum shows that investment in technology and innovation has been consistent and substantial throughout the study period.
Correlation Between Variables Table 2.
Correlation Between Research Variables 1061 | P a g e https://dinastipub.
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PD (Y)
PD (Y)
PR (Z)
EP (X.
PP (X.
TI (X.
Sumber: Diolah Penulis PR (Z) 3895*** EP (X.
PP (X.
TI (X.
3498*** 9245*** Table 2 shows a clear positive correlation between Restaurant Revenue (PR/Z) and Regional Tax (PD/Y), indicating a direct relationship between these variables.
This correlation is significant at the 1% significance level, demonstrating a strong statistical connection.
increase of one unit in PR (Z) will result in an increase of 0.
3895 units in PD (Y).
Technology Innovation (TI/X.
also has a positive and significant correlation with PD (Y).
An increase of one unit in TI (X.
will lead to an increase of 0.
3498 units in PD (Y), with significance at the 1% level.
Additionally.
TI (X.
is positively correlated with PR (Z), where an increase of one unit in TI (X.
will increase PR (Z) by 0.
9245 units, also significant at the 1% level.
However.
Tax Extensification (EP/X.
and Tax Collection (PP/X.
do not show significant correlation or impact on PD (Y) and PR (Z) at the 10% significance level, indicating these variables do not significantly influence the model.
These results also indicate no multicollinearity issues in the regression model, making the analysis valid and reliable.
Discussion of Results Table 3.
Multiple Regression Results for PD (Y) Intercept EP (X.
PP (X.
TI (X.
CoefficientsStandard Error t Stat P-value 23672E-32 Table 3 reveals that two variables significantly influence Regional Tax (PD/Y).
The first variable is Tax Collection (PP/X.
, which has a positive impact on PD/Y and is significant at the 1% significance level.
This means that when PP/X2 increases by one unit.
PD/Y will increase by 0.
06 units.
This finding supports the Tax Theory proposed by Halim et al.
and Mardiasmo .
, which states that effective tax collection can boost regional tax revenue.
The second variable influencing PD/Y is Technology Innovation (TI/X.
Similar to PP/X2.
TI/X3 has a positive and significant impact on PD/Y at the 1% significance level.
When TI/X3 increases by one unit.
PD/Y will increase by 0.
986 units.
This result supports previous research by Prakoso & Tahar .
, which links technological innovation with increased efficiency and effectiveness in regional tax management.
This analysis can be connected to several relevant theories.
The Central Place Theory proposed by Walter Christaller .
and supported by Prakoso & Tahar .
explains that developing economic centers attract more economic activities, including restaurant tax payments and technological investments.
Therefore, increases in TI (X.
and PP (X.
suggest that when technological innovation and tax collection are enhanced, economic centers tend to grow and support higher regional taxes.
Tax Theory, as explained by Halim et al.
and Mardiasmo .
, emphasizes the importance of efficient tax collection to maximize tax revenue.
The finding that PP (X.
has a positive and significant impact on PD (Y) underscores the importance of implementing an effective tax collection system as part of regional tax policy.
Regional Tax Theory from Hastuti .
and Law No.
28 of 2009 states that regional taxes, including restaurant taxes, play a critical role in increasing local revenue.
Restaurant taxes, as a major local revenue source, can be understood through the variable PR (Z), which correlates with regional tax (PD/Y).
Initial data showing that PP (X.
and TI (X.
significantly influence PD (Y) supports this view, as areas with effective tax rules and technology investments tend to have higher tax revenues.
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In practical terms, this research indicates that improvements in technological innovation (TI/X.
and tax collection (PP/X.
can have a significant positive impact on regional tax revenue (PD/Y).
This suggests that local governments should focus on enhancing technological innovation and strengthening their tax collection systems.
Better technology enables higher transparency and more effective oversight, while an efficient collection system ensures that owed taxes are actually collected.
The results of this study, supporting various theories and previous research, provide a strong basis for a better understanding of the factors influencing regional taxes.
This emphasizes the importance of effective tax policies, efficient tax collection practices, and ongoing investments in technology to drive local economic growth and increase regional revenue.
Tax Extensification (EP/X.
does not significantly influence Regional Tax (PD/Y).
However, collectively, the independent variables (EP/X1.
PP/X2.
TI/X.
significantly affect PD/Y with a coefficient of determination (R.
18%, meaning that 92.
18% of the variability in PD/Y can be explained by these three independent variables, while the remaining 82% is explained by other variables not included in the model.
Together, the four variables significantly explain PD/Y at a 5% significance level.
This study also tests the same model with Restaurant Revenue (PR/Z) as the dependent variable to see the influence of variables EP/X1.
PP/X2, and TI/X3 on PR/Z.
This model aims to further explore the relationships between independent variables affecting both dependent variables.
PD/Y and PR/Z, and understand how these factors interact in the local economic context.
As for Model 2 of this study, the variables EP (X.
PP (X.
, and TI (X.
are as follows:
Table 4.
Multiple Regression Results for PR (Z) Intercept EP (X.
PP (X.
TI (X.
CoefficientsStandard Error t Stat P-value 71285E-06 Table 4 clearly shows that the Technology Innovation (TI/X.
variable has a significant positive influence on Restaurant Revenue (PR/Z) at a 1% significance level.
If the TI (X.
variable increases by 1 unit, the PR (Z) variable will increase by 0.
3505 units.
This finding supports previous studies by Dhiya Arief Putri .
Sahrani .
, and Diana Sari .
on the influence of technology and innovation on tax revenue.
They concluded that technology and innovation in tax systems can enhance tax collection efficiency and taxpayer compliance.
Collectively, the independent variables (EP/X1.
PP/X2.
TI/X.
have a coefficient of determination (R.
value of 17.
53%, meaning that 17.
53% of the variation in PR (Z) can be explained by these three independent variables, while the remaining portion is explained by other variables not included in the model.
Variables EP (X.
and PP (X.
do not have a significant impact on Restaurant Revenue (PR/Z) at the 10% significance level.
Other research by Dhiya Arief Putri .
and Solehoddin .
confirms these findings, showing that effective extensification strategies by Bapenda Kota Pekanbaru successfully increased restaurant tax revenue, which in turn boosted Regional Own-Source Revenue (PAD).
Additionally, research related to the effectiveness of tax collection by Azzahra .
Habaib .
, and Giffiany Fibri Setiawan & Christiana Retno Gayatrie .
indicates that proper collection methods can enhance taxpayer compliance, which is crucial for regional tax Overall, these results demonstrate that technology and innovation play a key role in promoting tax compliance and increasing restaurant tax revenue, while effective tax extensification and collection strategies are also important, though they may not always be Model 3 creates a model where PD(Y) is the dependent variable and PR (Z) is the mediating or intervening variable.
The results of the model are as follows:
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Table 5.
Multiple Regression Results for PD (Y) with PR (Z) as a Mediating Variable Intercept
PR (Z)
EP (X.
PP (X.
TI (X.
Coefficients Standard Error t Stat P-value 79705E-06 Table 5 reveals that in the multiple regression model incorporating PR (Z) as a mediating variable, not all variables significantly impact Regional Tax (PD/Y) at the 10% significance level.
This suggests that certain variables may not contribute strongly enough to explain the variability in PD (Y) when PR (Z) is used as a mediator.
Further research is needed to understand the factors affecting this relationship more deeply.
On the other hand, when all independent variables (PR (Z).
EP (X.
PP (X.
, and TI (X.
) are combined, they can explain 17.
54% of the variation in PD (Y), as indicated by the coefficient of determination (R.
value of 17.
This means that, although some variables may not be individually significant, collectively they have enough influence to provide a meaningful explanation of the variation in PD (Y).
These variables together have a significant impact on PD (Y) at the 5% significance level.
This indicates that, while the individual impact of some variables may not be significant, the collective contribution of all independent variables provides a strong explanation for the variability in PD (Y).
This observation is important as it shows that a holistic approach, considering all independent variables together, can provide better insights into the factors influencing Regional Tax (PD/Y).
These results underscore the importance of considering variables collectively rather than focusing only on individual effects.
The findings also imply that there are other variables beyond EP (X.
PP (X.
TI (X.
, and PR (Z) that play a role in influencing Regional Tax (PD/Y).
Therefore, further research is needed to identify and evaluate additional variables that might contribute to a more comprehensive explanation of the factors affecting Regional Tax.
These findings also support previous research showing that regional taxes are a complex system with many interacting variables.
For example.
Prakoso & Tahar .
demonstrated that technological innovation significantly enhances tax efficiency, aligning with the findings on TI (X.
Additionally, research by Dhiya Arief Putri .
and Solehoddin .
indicated that effective tax extensification strategies can increase restaurant tax revenue, supporting findings related to EP (X.
and PR (Z).
The multiple regression analysis from Table 5 shows that although not all variables significantly impact Regional Tax (PD/Y) at the 10% significance level, collectively, these variables can explain 17.
54% of the variation in PD (Y).
These findings highlight the importance of considering all independent variables together and indicate the need for further research to identify other variables that may contribute to Regional Tax.
This relationship is also consistent with previous research explaining the complexity of regional tax systems and the interaction of various factors influencing tax revenue.
Research Implications This study offers several crucial implications for the development of policies and practices in the area of regional taxes and restaurant revenue.
The findings highlight that Technology Innovation (TI/X.
and Tax Collection (PP/X.
significantly influence Regional Tax (PD/Y).
With a coefficient of determination (R.
18%, independent variables such as TI.
PP, and EP collectively explain a majority of the variation in PD.
This underscores the importance of investing in technology and innovation to enhance tax collection efficiency and strengthen the existing collection system.
Local governments should consider adopting advanced technology in tax administration to ensure timely and accurate tax collection.
These findings are consistent with previous research by Dhiya Arief Putri .
Sahrani .
, and Diana Sari .
, which stated that technology and innovation can 1064 | P a g e https://dinastipub.
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enhance tax efficiency.
Technologies like digital payment applications and online reporting systems can accelerate data collection processes, facilitate taxpayer obligations, and reduce potential manual errors.
Therefore, local governments must continue investing in technology and innovation to optimize regional tax revenue and support economic growth.
Furthermore, the study shows that Restaurant Revenue (PR/Z) positively correlates with Regional Tax (PD/Y) and Technology Innovation (TI/X.
This supports research by Halim et .
and Mardiasmo .
, emphasizing the importance of revenue from the restaurant sector in increasing Regional Own-Source Revenue (PAD).
Local governments should focus on strategies to increase restaurant revenue through extensification efforts and improved taxpayer compliance.
Research by Azzahra .
Habaib .
, and Giffiany Fibri Setiawan & Christiana Retno Gayatrie .
shows that effective tax collection can enhance taxpayer An efficient and transparent collection system, along with strict sanctions for violations, is necessary to raise taxpayer awareness and responsibility.
The study also reveals that Tax Extensification (EP/X.
does not significantly influence Regional Tax (PD/Y), although collectively, the independent variables can explain most of the variation in PD/Y.
This suggests that tax extensification strategies should be supported by other factors like technology and effective collection systems.
Research by Dhiya Arief Putri .
and Solehoddin .
supports this finding, showing that extensification strategies implemented by Bapenda Kota Pekanbaru successfully increased restaurant tax revenue, in turn boosting PAD.
The findings also have implications for future tax policies.
The results indicate that technology innovation and tax collection significantly and positively impact regional tax Thus, future tax policies should include investment in technology and innovation and improvements in the tax collection system to ensure more effective tax collection.
Additionally, tax extensification strategies should be optimized, considering other factors influencing tax The discussion highlights the need for further research to identify other variables that might contribute to regional tax revenue.
The coefficient of determination (R.
value of 17.
for the independent variables in explaining Regional Tax (PD/Y) suggests other variables beyond EP (X.
PP (X.
, and TI (X.
need to be identified and analyzed.
Further research can provide a more comprehensive understanding of the factors influencing regional tax revenue.
Additionally, the practical implications of these findings are that local governments must improve the quality of tax administration services.
Good service, transparency, and accountability in tax administration can increase taxpayer trust and encourage compliance.
Continuous taxpayer education on the importance of timely tax payments and the benefits derived from paid taxes is also necessary.
In conclusion, this study provides strong empirical evidence on the importance of technology and effective collection systems in increasing regional tax revenue.
These findings support tax theories proposed by Halim et al.
Mardiasmo .
, and Prakoso & Tahar .
, and enrich the literature on extensification and tax collection strategies.
The results also offer practical guidance for local governments in developing more effective and efficient tax policies, enabling them to optimize tax revenue as a primary income source to support local development and economic growth.
CONCLUSION
The study concludes that Tax Collection (PP/X.
and Technology Innovation (TI/X.
significantly impact Regional Tax (PD/Y) at a 1% significance level, indicating the importance of effective tax collection and technology investment for enhancing tax revenue.
Technology Innovation (TI/X.
also positively influences Restaurant Revenue (PR/Z), contributing to local Collectively.
Tax Extensification (EP/X.
PP/X2, and TI/X3 significantly influence both PD/Y and PR/Z, highlighting the need for a holistic approach in tax policy, incorporating technology, extensification strategies, and effective tax collection.
However.
EP/X1 alone does 1065 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
2, 2025
not significantly impact PD/Y or PR/Z, indicating the need for additional factors to support tax revenue growth.
The study suggests that the Bekasi local government should take proactive measures to encourage the development of the restaurant industry, such as providing fiscal and non-fiscal incentives to attract investors, increasing tax awareness and compliance, modernizing the tax system with advanced technologies, and developing supportive licensing and regulatory Collaboration with the private sector can further support skill training, culinary innovation, and technical development.
By implementing these strategies, the Bekasi local government can create a more conducive environment for the restaurant industry's growth, ultimately increasing restaurant tax revenue and Regional Tax to support local economic development and growth.
REFERENCES