The Influence of Original Revenue and Transfer Revenue on Capital Expenditure in South Tangerang City

ABSTRACT

The purpose of this study is to determine and analyze the effect of own-source revenue and transfer revenue on capital expenditure in South Tangerang City. The data used is time series data regarding local own-source revenue and transfer revenue on capital expenditure in South Tangerang City 2012-2021. Data analysis methods include Multiple Regression Analysis, t test, and coefficient of determination analysis. From the Multiple Regression Analysis, the regression equation Y=1.03819 + 0.521X2-0.612X3 is obtained. The constant of 1.03819 means that the increase in capital expenditure allocation is 1.03819 percent if there is no increase in local revenue and transfer revenue. The regression coefficient of the local own-source revenue variable shows a positive influence on capital expenditure of 0.521. From the t-test results, it can be explained that local ownsource revenue has a significant effect on capital expenditure, where the t-count> t-table value is obtained (2.701> 2.306). The regression coefficient of the local ownsource revenue variable shows a negative effect on capital expenditure of 0.612. From the t-test results, it can be explained that transfer revenues have a significant effect on capital expenditures in South Tangerang City, where the t-count value is obtained < t-table (1.259 < 2.306). From the coefficient of determination analysis, it is known that local revenue and transfer revenue affect capital expenditure by 47.4%, while the remaining 52.6% is influenced by other variables outside this research model. Increased capital expenditure has an important role because it has a long-term benefit period to provide services to the public because infrastructure development and the provision of various facilities are carried out to increase investment attractiveness. Industrial infrastructure development has a real impact on the increase in local revenue. So that if the Regional Government wants to improve public services and people's welfare by increasing capital expenditure, then the Regional Government must strive to explore as much local revenue as possible.

A. INTRODUCTION
The implementation of regional autonomy along with fiscal decentralization along with the enactment of Law Number 23 of 2014 concerning Regional Government and Law Number 1 of 2022 concerning Financial Relations between the Central Government and Local Governments, presents a new government administration policy space. The presence of this policy gives authority to the regions to regulate and manage their territory, including regional financial management. Both laws are the result of revisions following the needs in an effort to respond to various problems in the implementation of local government.
With the policy of regional autonomy and fiscal decentralization, the quality of public services must certainly increase. It is expected that there will be an increase in services in various sectors, especially the public sector. This will also be an attractive factor for investors to invest in the region. This hope can be realized if the government provides various facilities for investment (Kusmayadi & Qomari, 2019). As a logical consequence, there is a greater allocation of expenditure by local governments. In this case, capital expenditure is one of the expenditures carried out by local governments (Antari & Sedana, 2018). The distribution of Transfer to Regions and Village Funds is part of the fiscal decentralization policy. Fiscal decentralization includes the means and mechanisms of fiscal cooperation in the distribution of state revenues between the central and local governments, including the allocation of expenditures, and the implementation of finances in local governments (Cheema & Rondinelli, 2007).
Budgeting is one of the pillars of public financial management. At the local government level, policies taken by the central government within the framework of central and local financial relations have the logical consequence that the choice of fiscal decentralization policy presents local governments with the authority to manage revenues and expenditures for the benefit of carrying out activities within the scope of local government authority. Local government organizers have the authority and responsibility to organize the interests of the community based on the principles of openness, public participation, and accountability to the community (Farvacque-Vitkovic et al., 2014).
Disrupted economic activity has implications for changes in the state budget posture both from the amount of State Revenue, the amount of State Expenditure, and the amount of Financing. In the level of implementation of public finance, the government budget is determined annually in the form of budget policy (Musgrave & Musgrave, 1989). Local budget policies are not always in normal conditions. Under certain conditions, regional budget policies are faced with crisis conditions both due to natural and non-natural disasters such as the pandemic. Preparing solutions to the financial crisis due to the pandemic requires full attention from the government, especially related to liquidity management to support government activities or operations (Habyarimana et al., 2020).
This alternative source of funding has the potential to effectively complement traditional sources of providing and maintaining high social impact public facilities by bringing in new resources and encouraging timely project completion (Chen & Bartle, 2017). Departs from local government financial administration conveyed by (Farvacque-Vitkovic et al., 2014) that local financial management strategies are key in order to oversee the continuity of services to the community.
Local governments in disaster conditions, both natural and non-natural disasters, result in a decrease in local revenue, including the component of local tax revenue. High uncertainty in local revenue components based on local tax sources in developing countries is a key factor that causes local financial deficits. High uncertainty in tax-based revenue sources in developing countries is often considered a key factor behind of local fiscal deficits. Local officials can use their administrative discretion in the management of public assets to generate off-budget revenues to help alleviate fiscal pressures. This research studies how budget constraints and market opportunities affect financing using public assets (Dong & Wang, 2018).
In more complicated situations (and with available resources), such assistance is absent. Taking into account the very limited central response to local fiscal needs, it can be argued that the fiscal development of local budgets in Czechia and Slovakia is no longer proportional. With significant increases in expenditures and even more significant decreases in revenues, Czech and Slovak municipalities may not have sufficient resources to fully fulfill their responsibilities, with visible impacts especially on social services, sports, culture, and the environment (Nemec & Špaček, 2020).
South Tangerang City in 2012 shows that local own-source revenue was only IDR576 billion, which increased so rapidly that in 2017 it amounted to IDR1,448 billion and in 2019 IDR1,818 billion with a percentage reaching 88.2%. However, it shows the acquisition of local revenue, especially at the beginning of the pandemic, namely the 2019 fiscal year which managed to reach the highest point of IDR 1,818 billion. However, along with the conditions of the pandemic with all the policy implementations that followed, the local revenue fell to IDR 1,539 billion and the percentage fell to 87.42%. However, the percentage of local tax contribution to local revenue in South Tangerang City in 2020 was still above the national average of 65%-75%. To overcome the decline in PAD (Pendapatan Asli Daerah) due to the pandemic, strategic steps need to be taken to boost PAD. Efforts that can be made are to provide tax relief and tax incentives (Ra'is & Rohman, 2020). This step will foster regional competitiveness so that it has economic resilience. Regions that have high competitiveness have the opportunity to get more and sufficient sources of PAD.
Modernization of local tax administration through strengthening the local tax collection mechanism starting from data collection, registration, payment, supervision, billing to inspection. In addition, tax collection is carried out through an information technology approach in local tax management and cooperation with related agencies, including the National Land Agency and Land Deed Officials for the synergy of managing Rural and Urban Land and Building Tax and Fees for Acquisition of Rights on Land and Buildings, the State Attorney's Office for assistance in local tax collection, the Investment Office for licensing synergies and information system integration (Sofi, 2021).
Furthermore, related to the realization of transfer revenue in 2012, the realization of transfer revenue was IDR1,126 billion, experiencing a consistent increase so that in 2019 the realization was IDR1,536 billion. However, the acquisition of transfer revenues, especially at the beginning of the Covid-19 pandemic, namely the 2019 fiscal year, which managed to reach the highest point of IDR1,536 billion. However, along with the conditions of the pandemic with all the policy implementations that followed, the transfer revenue fell to IDR1,307 billion. In relation to the composition of capital expenditure during the 2012-2021 period in South Tangerang City, the three largest were capital expenditure on equipment and machinery, capital expenditure on buildings and structures, and capital expenditure on roads, networks and irrigation. The largest capital expenditure for equipment and machinery in 2012 amounted to IDR203.1 billion, the largest capital expenditure for buildings and structures in 2019 amounted to IDR504.04 billion, and the largest capital expenditure for roads, networks, and irrigation in 2018 amounted to IDR445.89 billion.
Local governments in Indonesia play an important role in providing services that support the quality of Indonesia's human resources, as well as public infrastructure that supports economic growth (World Bank, 2020). In accordance with the economic allocation in the Regional Budget there is capital expenditure which shows a positive effect on the provision of infrastructure (Hiktaop & Hayon, 2019).
This study wants to find out how much Regional Original Revenue partially affects Capital Expenditure in South Tangerang City and how much Transfer Revenue partially affects Capital Expenditure in South Tangerang City. In addition, this study also wants to know how the variables of Local Revenue and Transfer Revenue together (simultaneously) affect Capital Expenditure in South Tangerang City. This study aims to identify the importance of local revenue in delivering public services and impacting people's welfare by increasing capital expenditure with the support of local revenue. In Figure 2 below is the research flow which is the steps in the implementation of this research. These steps are described in the form of Flowchart Diagrams, as shown in Figure 1.

B. METHODS
Research design is used to analyze and identify the subject of this study. In order to make the research going in the right way, a research design is needed. The design of this research is descriptive quantitative method because the data is presented in numerical and descriptive form. The type of data collected is in accordance with the needs of research analysis in order to answer research questions (Creswell, 2014). Research design is used to analyze and identify the subject of this study. In order to make the research going in the right way, a research design is needed. The design of this research is descriptive quantitative method because the data is presented in numerical and descriptive form. Judging from the source of data collection, there are two types, namely primary data sources and secondary data sources (Kumar, 2011). The data used in this quantitative research stage is secondary data. Secondary data in this study were obtained in hardcopy and softcopy from the relevant agencies.
Secondary data is a variety of information that has been previously and deliberately collected by researchers used to complement research data needs. Specifically, secondary data are local government financial reports. These local government financial reports are very Start Literature Study

Quantitative Data Collection
Classical Assumption Test

Conclusions and
Suggestions Finish adequate as data for this study. This is because the general purpose of preparing financial statements is to present relevant information about the financial position, budget realization, budget surplus balance, cash flow, operating results, and changes in equity of a reporting entity that is useful for users in making and evaluating decisions about resource allocation. Specifically, the purpose of local government financial reporting is to present information that is useful for decision making and to demonstrate/assess the accountability and financial performance of a reporting entity for the resources managed and make decisions, both economic, social and political decisions. The secondary data obtained and the types of documents and provider agencies are presented in Table 1. Document Type Data Provider Agency 1 Regional Medium-Term Development Plan Regional Development Planning, Research and Development Agency 2 Regional Regulation on the Regional Budget Regional Finance and Asset Agency 3 Regional Government Financial Report Secondary data for the preparation of quantitative research data sets in addition to going through document provider agencies, researchers also search through the official websites of government agencies. Regional financial data through the website https://keuda.kemendagri.go.id and https://djpk.kemenkeu.go.id/?p=5412. Audit report data on the website https://e-ppid.bpk.go.id and https://banten.bpk.go.id. While South Tangerang City Government data through the website https://jdih.tangerangselatankota.go.id and https://tangselkota.bps.go.id.
The data set for the first segment of the quantitative stage research was prepared by considering that the data units of local own-source revenues, transfer revenues, and capital expenditures are in nominal rupiah with large values, so the model before becoming the analysis data set will be transformed first to the natural logarithm (ln). If the value of local revenue, transfer revenue, and capital expenditure is just used, the value of the variable will be very large. By using the natural logarithm (ln), the billion or trillion values become simpler, without changing the proportion of the original values. Sometimes it is possible to change the variables (e.g. by conversion to logarithms) to create a better line (Gorard, 2004).
The equation above is explained in Table 2. Classical assumption testing is carried out to fulfill the multiple linear regression assumptions used to test the hypothesis in this study. The classic assumption tests used are Normality Test, Multicollinearity Test, Heteroscedasticity Test, and Autocorrelation Test. To analyze whether or not there is an influence between local government revenues (logrev) and transfer revenues or intergovernmental relation (intgov) with capital expenditure (capex) the researcher will use multiple regression analysis. Analysis with more than two variables will use multiple regression analysis with the econometric equation model (Gujarati & Porter, 2009) as mentioned above.
Multiple linear regression analysis was used to achieve the objective of this study, which is to determine the effect of local own-source revenue and transfer revenue on capital expenditure in South Tangerang City. Multiple regression regression analysis is a statistical technique used for studies that predict that several variables may influence the dependent variable (Gujarati & Porter, 2009). There are advantages to using multivariate regression analysis as it allows a number of complex relationships between variables to be examined simultaneously and in terms of their joint contribution to explaining variations in local government financial conditions (Jones & Walker, 2007).
Multiple regression is a statistical technique in which one can analyze the relationship between a dependent or criterion variable and a set of independent or predictor variables. As a statistical tool, multiple regression is often used to achieve the goal of finding the best prediction equation for a set of variables, namely variables X2 and X3 (predictors), and variable Y (criterion variable) (Ho, 2006). There are three main results to be analyzed: model summary or Adjusted R-Square (R2) analysis, F-test, and significance testing (t-test).
The Adjusted R-Square (R 2 ) value summarizes the model's ability to explain the sample by assessing the combined effect of a set of variables (De-Vaus, 2002). The higher the Adjusted R-Square (R 2 ), the stronger the model. The F-test is used to test the significance of the regression model as a whole. In other words, a significant F value tells us whether the R-square is greater than zero due to sampling error. To test whether the independent variables simultaneously affect the dependent variable, the F-test is used by looking at the probability value of the Fstatistic. The t-test is used to test the significance of individual coefficients. The null hypothesis of the t-test is that the regression coefficient of the independent variable is zero when other predictors are present in the model. Researchers can use the t-test to test hypotheses about individual partial regression coefficients (Gujarati, 2004).

C. RESULT AND DISCUSSION 1. Descriptive Analysis of Capital Expenditure Pace and Ratio
The pace of capital expenditure and the ratio of capital expenditure to total expenditure over the period 2012-2021 are presented in Figure 2. In 2012, the percentage ratio of capital expenditure to total expenditure was 39.73%, which decreased in 2013 to 33.17%. Furthermore, it increased several times until 2015 it reached 37.51%. In 2019 to 2020, when the Covid-19 pandemic policy was implemented, it decreased from 33.21% to 26.91%. However, the capital expenditure ratio of South Tangerang City is still above the national capital expenditure ratio, which is around 21.1% (DJPK Kemenkeu, 2019).
The improving quality of regional expenditure can be seen from the decreasing portion of personnel expenditure in the APBD. The smaller the portion of APBD expenditure used for apparatus expenditure, the APBD can be optimized to support other types of expenditure that are more related to public services such as capital expenditure for the construction of community facilities or to support expenditures that are effective in driving the regional economy such as increasing connectivity by building new roads and bridges (DJPK Kemenkeu, 2019).
In terms of the composition of capital expenditure during the 2012-2021 period in South Tangerang City, the three largest were capital expenditure on equipment and machinery, capital expenditure on buildings and structures, and capital expenditure on roads, networks, and irrigation. The largest capital expenditure for equipment and machinery in 2012 amounted to IDR203.1 billion, the largest capital expenditure for buildings and structures in 2019 amounted to IDR504.04 billion, and the largest capital expenditure for roads, networks, and irrigation in 2018 amounted to IDR445.89 billion.

Classical Assumption Test
The multiple regression model can be categorized as a good model if the model meets the assumptions of data normality and is free from classical assumptions both related to multicollinearity, autocorrelation, and heteroscedasticity (Sujarweni, 2021). The step of using classical assumption testing is carried out along with the multiple regression test process so that the steps taken in the classical assumption test use the same analysis application as the regression test.
Based on the Shapiro-Wilk normality test, the p-value for Ln_capex is 0.576 higher than 0.05, Ln_logrev is 0.548 higher than 0.05, and Ln_intgov is 0.331 higher than 0.05. Therefore, this study cannot accept the alternative hypothesis at 95% significance. It can be concluded that the normality significance test shows that the values are correct, because they are based on normally distributed assumptions.
Multicollinearity occurs when two or more independent variables have a high level of correlation (Cooper & Schindler, 2014). Looking at the results of the amount of correlation between independent variables, it appears that the Ln_intgov variable has a correlation with the Ln_logrev variable with a correlation level of 0.825 or around 85%. Because this correlation is still below 95%, it can be concluded that there is no multicollinearity.
The heteroscedasticity test can be seen with the park test, namely by regressing the natural logarithm value of the squared residual (Lne2) with the independent variables (X2 and X3). The test criteria are if the Significance value> 0.05 means that there are no symptoms of heteroscedasticity, while if the Significance value <0.05 means that there are symptoms of heteroscedasticity. Based on the test results the Sig value. X2 (logrev) is 0.506 (>0.05) and the Sig value. X3 (intgov) of 0.968 (>0.05). Therefore, it is concluded based on the park test that there are no symptoms of heteroscedasticity, because the significance value obtained is greater than 0.05 (with a statistical confidence level of 95% or α = 0.05).
The autocorrelation test aims to test whether in the linear regression model there is a correlation between confounding errors in period t-1 (previous). If there is a correlation, it is called an autocorrelation problem (Ghozali, 2018). In this study using the Durbin-Watson Test (DW Test). The Durbin-Watson test requires a constant (intercept) in the regression model and there are no lag variables between the independent variables (Brooks, 2008).
Analysis and interpretation of the Durbin-Watson Test output results show that there is no autocorrelation if it meets dU < d < 4 -dU with the test result value (d) = 1.816. In accordance with the Durbin-Watson Table with k = 10 and v = 2 shows the value of dL = 0.697 and dU = 1.641, so 4 -dU = 2.359. Based on the statistical test results, the d value is between the required critical values. Therefore, the null hypothesis of no autocorrelation is accepted and it is concluded that the residuals of the model have no autocorrelation.

Multiple Regression Analysis
Multiple regression is a statistical technique in which one can analyze the relationship between a dependent or criterion variable and a set of independent or predictor variables. As a statistical tool, multiple regression is often used to achieve the goal of finding the best prediction equation for a set of variables, namely variables X1 and X2 (predictors), and variable Y (criterion variable) (Ho, 2006). The output results of SPSS multiple regression analysis of quantitative data sets related to capital expenditure (CE=Y), local government reveue (LR=X2) and intergovernmental relations (IR=X3) are presented in Table 3. Based on the coefficients in Table 3 above, the regression equation constructed is as follows: = 1,03819 + 0,521 2 − 0,612 3 The estimate associated with the local own-source revenue variable (logrev/LR) is indicated by its significant p-value of 0.031 as it is less than 0.05. This significant value means that there is only a 3.1% chance that the logrev/LR coefficient is due to sampling error. Thus, the p-value indicates that local own-source revenue is statistically significant in explaining local government capital expenditure in the presence of other variables. The positive sign means that an increase in the level of own-source revenue will cause capital expenditure to increase. Further explanation is as follows: when the coefficient of own-source revenue is estimated to be 0.521, an increase in own-source revenue by one unit will cause an increase in capital expenditure of 0.521, assuming other variables are held constant. This finding is consistent with the hypothesis.
Meanwhile, the estimate of the transfer income variable (intgov/IR) is shown by its insignificant p-value of 0.248 because it is more than 0.05. It can be concluded that statistically transfer income is not significant in explaining the level of capital expenditure in the presence of other variables. In other words, statistically, transfer revenues have no predictive ability. Based on the results of the analysis above, this finding is not in line with the hypothesis. As research in the social field, this study set the probability or significance level at 0.05 (Ho, 2006). If the t-statistic value is greater than α = 0.05 then H0 is accepted and Ha is rejected, but if the t-statistic is smaller than α = 0.05 then H0 is rejected and Ha is accepted. The hypothesis is as follows: a. H01: There is no significant influence between local revenue (PAD) partially on capital expenditure in South Tangerang City for the period 2012-2021. b. Ha1: There is a significant influence between partially local revenue (PAD) on capital expenditure in South Tangerang City for the period 2012 -2021 c. H02: There is no significant influence between transfer revenue partially on capital expenditure in South Tangerang City for the period 2012 -2021 d. Ha2: There is a significant influence between transfer revenue partially on capital expenditure in South Tangerang City for the period 2012-2021.
Based on the regression results obtained in Figure 2 above, the proof of the hypothesis has been presented as that the probability value of the t-Statistic of the local government revenue (LR) variable of 0.031 is smaller than 0.05, which means that H01 is rejected and Ha1 is accepted. The conclusion is that there is a significant influence between local revenue partially on capital expenditure in South Tangerang City for the period 2012-2021. Furthermore, the result of the t-Statistic probability value of the transfer income variable intergovental relation of 0.248 is greater than 0.05, which means that H02 is accepted and Ha2 is rejected. The conclusion is that there is no significant influence between transfer revenue partially on capital expenditure in South Tangerang City for the period 2012-2021.
The Adjusted R-Square (R2) value summarizes the model's ability to explain the sample by assessing the combined effect of a set of variables (De-Vaus, 2002). The higher the Adjusted R-Square (R2), the stronger the model. The results of SPSS Multiple regression analysis output on the quantitative data set related to Adjusted R-Square R2 (Model Summary) are presented in Table 4. Predictors: (constant), intgov, logrev From From the model summary presented in Table4 above, the adjusted R-square value is 0.474, which means that the two explanatory variables (intgov and logrev) together in the model explain 47.4% of the variation in capital expenditure (capex). In other words, based on the results of multiple linear regression analysis of the effect of local revenue (logrev) and transfer revenue (intgov) on capital expenditure (capex) in South Tangerang City, the coefficient of determination is 0.474. This means that 47.4% of capital expenditure in South Tangerang City in the period 2012-2021 can be explained by the variables of local own-source revenue (logrev) and transfer revenue (intgov). Meanwhile, 52.6% is explained by other variables not examined in this study.

D. CONCLUSION AND SUGGESTIONS
The results of the analysis and interpretation related to the classical assumption test on the quantitative data set as quantitative research data for multiple regression analysis which includes normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test all meet the characteristics of the best linear unbiased estimator (BLUE). Thus, the quantitative data set can be subjected to further tests, namely multiple regression tests.
From hypothesis testing, this study found that the local own-source revenue variable statistically significantly influenced capital expenditure. The direction of the local own-source revenue variable is positive. This finding is consistent with the hypothesis. This result is in line with the research findings (Rizal & Erpita, 2019) but in the opposite direction to the research results (Satria et al., 2021) and contrary to the insignificant findings by (Ruhiyat & Handayani, 2021). Meanwhile, the transfer income variable in the hypothesis test results statistically shows that it does not significantly affect the dependent variable on capital expenditure. The direction of the transfer income variable shows a negative direction. This finding is inconsistent with the hypothesis. This result also contradicts the significant findings and positive direction by (Lewis, 2013).
Increased capital expenditure has an important role because it has a long-term benefit period to provide services to the public because infrastructure development and the provision of various facilities are carried out to increase investment attractiveness. Industrial infrastructure development has a real impact on the increase in local revenue. So that if the Regional Government wants to improve public services and people's welfare by increasing capital expenditure, then the Regional Government must strive to explore as much local revenue as possible.
Efforts to explore local revenue suggested include: (a) Provide tax relief and tax incentive compensation in the form of discounts for timely payment of Land and Building Tax to encourage the achievement of local tax realization and provide a tax payment grace period policy for taxpayers experiencing liquidity difficulties; (b) Conduct intensification and extensification based on local laws and regulations by reviewing the potential of local taxes and levies; (c) Make breakthroughs and coordination with related ministries and with surrounding local governments; (d) Modernize local tax administration and simplify business processes through strengthening local tax collection mechanisms starting from data collection, registration, payment, supervision, billing to inspection; (e) Collaborate with relevant stakeholders, among others with the National Land Agency and the Tax Service Office (KPP) in updating and validating local tax data; (f) Place human resources, especially functional officials according to their expertise and capacity, especially in the field of local revenue while increasing capacity and capability through counseling, training and even diploma education in Land and Building Tax; (g) Increase awareness of local taxpayers through counseling and placing public money trust in trustworthy local government management; (h) Educate local taxpayers through local tax technical training so that they can improve the quality of selfassessment; (i) Provide excellent service to taxpayers, among others, the tax authorities pick up the ball to local taxpayers; and (j) Provide measurable sanctions to local taxpayers who violate, among others, installing banners or stickers at the local taxpayer's place of business.

ACKNOWLEDGEMENT
The author would like to thank the Politeknik STIA LAN Jakarta for providing support in the form of assistance in this research so that it can be carried out properly.