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Business and Economics
DOI: 10.21070/acopen.10.2025.11091

Digital Payment, Support, and Ethics Drive Micro and Small Business Income


Universitas Islam Negeri Sumatera Utara
Indonesia
Universitas Islam Negeri Sumatera Utara
Indonesia
Universitas Islam Negeri Sumatera Utara
Indonesia

(*) Corresponding Author

Digital Payment Islamic Business Government Subsidies MSME Income

Abstract

General Background: The rapid evolution of financial technology has introduced digital payment systems as vital tools for business growth. Specific Background: Within the context of Indonesian micro, small, and medium enterprises (MSMEs), especially in Medan City, these advancements intersect with government policy and religious ethics. Knowledge Gap: However, limited empirical evidence exists on how digital payments, Islamic business principles, and state subsidies collectively influence MSME income. Aims: This study aims to quantitatively examine the effect of digital payment technologies, Islamic business practices, and government subsidies on MSME revenue in Medan. Results: Using a correlational approach and Slovin-based purposive sampling of 100 MSME owners from a population of 70,843, multiple linear regression analysis reveals that all three independent variables significantly and positively affect MSME income. Novelty: The study integrates faith-based economic principles with technological and policy variables, providing a unique multidimensional perspective on MSME growth. Implications: The findings suggest that synergistic support—combining ethical entrepreneurship, digital finance, and government intervention—can enhance income generation for MSMEs, thereby offering valuable policy insights for sustainable economic development.

Highlights:

  • Reveals how Islamic principles integrate with modern business tools.

  • Shows digital payments and subsidies boost MSME profits.

  • Offers policy insights for sustainable MSME development.

Keywords: Digital Payments, Islamic Business, Government Subsidies, MSME Income

 

Introduction

The development of employment and economic growth in Medan City is driven by MSMEs. MSMEs contribute 90% of employment and up to 60% of GDP, according to the Ministry of Cooperatives and SMEs. As a result, these businesses significantly influence national economic growth [1]. At the regional level, MSMEs in Medan City play an important role in driving the economy, creating jobs, and encouraging the diversity of products and services that support sustainable economic development [2]. Therefore, the development of MSMEs is a major focus in the national economic strategy.

In the digital era, MSMEs face new challenges, especially in implementing digital payment systems to improve company efficiency and competitiveness. Digital payments are a technology-based non-cash transaction technique that enables electronic transactions using e-wallets, online banking, and credit cards [3]. This method has several advantages, including ease of transactions, payment efficiency, and better financial security. The increasing public interest in digital transactions requires MSMEs to adapt to maintain market competitiveness [4]. In research [5], it shows that digitalization of transactions can increase operational efficiency and productivity in MSMEs, thereby encouraging rapid company development. The use of digital payments allows businesses to reduce dependence on cash transactions, which often have constraints in terms of flexibility and security. Payment procedures will be more efficient and faster by using digital payment options [6].

However, not all MSMEs can easily implement digital payments. Various obstacles, including limited access to technology, high implementation costs, and lack of digital literacy, remain major challenges. There are 66 million MSMEs in Indonesia, 27 million of which use some form of digital technology. This figure represents 40.91 percent of all MSMEs. The digital divide shows that while digital payments can substantially increase MSME revenues, most business operators have yet to effectively use them. As a result, strong regulatory initiatives, ongoing education, and technology incentives for MSMEs are critical to facilitate more uniform and successful adoption of digital payments.

In addition to technology, government support is an important element in encouraging the development of MSMEs. Entrepreneurs can learn and obtain funding to improve their technical skills through programs such as “MSMEs Go Digital" and People's Business Credit. Since implementing KUR, MSMEs in Medan City have shown improvements in both productivity and competitiveness. There are a number of programs implemented by the Medan City Government to assist MSMEs. These programs include training focused on digitalization, financial assistance, creation of supporting infrastructure, and regional regulations [7]. However, even though various regulations have been implemented, there are still obstacles, including limited access to information and inadequate levels of education among MSME participants. Research by Yulianingsih [8] shows that structural obstacles still exist, including budget constraints and inadequate legal understanding of obtaining government support. Therefore, government policies must be aligned with improving socialization techniques and assistance to ensure that MSMEs get optimal benefits from existing programs.

The advantages of a digital payment system lie not only in transaction efficiency, but also in increasing transparency and more accurate financial records. With this system, business actors can monitor cash flow in real time, reduce the risk of losing funds, and build a more trusted financial reputation in the eyes of financial institutions. This opens up opportunities for MSMEs to gain wider access to financing. In the context of Islamic business ethics, the implementation of digital payments is also in line with the principles of honesty (shidq), amanah, and openness (transparency) which are the foundations of muamalah. The use of transparent payment technology can prevent the practices of usury, gharar, and fraud, and encourage the creation of a fair and sustainable business environment in accordance with sharia values ​​[10]. Therefore, the integration of technological advances and Islamic business ethics is key to strengthening competitiveness and creating an inclusive and equitable economic system. The concepts of integrity, equity, reliability, and accountability contribute to fostering consumer trust and encouraging sustainable business practices [9]. Research by [10] shows that the use of Islamic business principles improves the performance and profitability of MSMEs. However, some company stakeholders see obstacles in building a better and more sustainable corporate environment in the long term: failure to understand the concept of Islamic business. Some parties ignore business ethics norms in the face of fierce corporate competition, which can result in unfair business practices [11]. That is why the application of Islamic business ethics is a strategic component in increasing corporate competitiveness and is a moral issue for MSME stakeholders.

The urgency of this research lies in the need to holistically understand the factors that influence the increase in MSME income amidst the increasingly rapid digital transformation. Although digitalization has opened up great opportunities for MSMEs, the gap in the application of technology and the lack of understanding of the principles of Islamic business ethics are still real challenges, especially in Medan City. In addition, government support is often not optimally implemented in the field. Therefore, a comprehensive study is needed that not only highlights the digital technology aspect, but also considers the role of policy intervention and Islamic ethical values ​​in shaping the financial performance of MSMEs.

The purpose of this study is to determine how the financial performance of MSMEs in Medan City is related to digital payments, government assistance, and Islamic business principles. Academics, government agencies, and MSME stakeholders can use the findings of this study to inform the development of policies and strategies that will make MSMEs more competitive in today's digital economy.

Method

The associative method is used in this quantitative study. In conducting research, analyzing data, and drawing conclusions, quantitative methods rely more on numerical data. This study uses associative techniques to calculate the magnitude of these factors and evaluate hypotheses about the relationships between them [12]. Questions given to MSME actors in Medan City are the main data sources for this study. This study involved 70,843 MSME actors as its population. By using the Slovin formula, a purposive sampling technique was used.

n=N/(1 + 〖N (e〗^2))

Where:

n : number of samples

N : population size

e : (error tolerance)

In this study, the researcher used a 10% (0.1) error tolerance threshold. The following is the calculation of the sample size obtained using the Slovin formula. The research population includes MSME actors in Medan City.

n=70.843/(1 + 70.843×〖0,1〗^2 )

n=99,89

Rounded up to 100 souls

In this study, 100 people were selected using the purposive sampling method. The criteria used to select participants were specifically UMKM actors in Medan City.

This study tested this idea using multivariate linear regression. Researchers use multiple regression to find the most significant causal relationships when there are multiple independent variables and one dependent variable [11]. For multiple regression, the following model was used:

Y = a + b1X1 + b2X2 + b3X3 + e

Where:

Y = Predicted value

a = Constant/intercept

b = regression coefficient/slope

X1 = Independent variable (Digital Payment)

X2 = Independent variable (Government Support)

X3 = Independent variable (Islamic Business Ethics)

Ԑ = Residual value

Results and Discussion

A. Results

1. Testing Data Validity and Reliability

a. Validity Test

When the results of a study are in accordance with what the participants say, we say the study is valid. Data are considered valid if there is no clear difference between the conditions reported by the research subjects and the actual conditions experienced by the person. The Product Moment correlation approach is used for the purpose of validity testing. At a significance level of 5%, we compare the item-specific correlation coefficients with the values ​​in the r table. If the calculated r table value is greater than that value, the validity test concludes that the questionnaire is valid. The survey fails if the calculated r-table value is lower than the r-table value.

Research Variables Item r Count r Table Sig Sig Standard Information
Digital Payment (X1) X1.1 0,772 0,1966 0,000 <0,05 Valid
X1.2 0,808 0,1966 0,000 Valid
X1.3 0,802 0,1966 0,000 Valid
X1.4 0,766 0,1966 0,000 Valid
X1.5 0,786 0,1966 0,000 Valid
X1.6 0,774 0,1966 0,000 Valid
X1.7 0,736 0,1966 0,000 Valid
X1.8 0,723 0,1966 0,000 Valid
Government Support (X2) X1.9 0,800 0,1966 0,000 Valid
X1.10 0,812 0,1966 0,000 Valid
X2.1 0,727 0,1966 0,000 <0,05 Valid
X2.2 0,774 0,1966 0,000 Valid
X2.3 0,703 0,1966 0,000 Valid
X2.4 0,846 0,1966 0,000 Valid
X2.5 0,780 0,1966 0,000 Valid
X2.6 0,784 0,1966 0,000 Valid
X2.7 0,713 0,1966 0,000 Valid
X2.8 0,649 0,1966 0,000 Valid
Islamic Business Ethics (X3) X2.9 0,724 0,1966 0,000 Valid
X2.10 0,735 0,1966 0,000 Valid
X3.1 0,780 0,1966 0,000 <0,05 Valid
X3.2 0,794 0,1966 0,000 Valid
X3.3 0,737 0,1966 0,000 Valid
X3.4 0,770 0,1966 0,000 Valid
X3.5 0,787 0,1966 0,000 Valid
X3.6 0,770 0,1966 0,000 Valid
X3.7 0,803 0,1966 0,000 Valid
MSME Income (Y) X3.8 0,740 0,1966 0,000 Valid
X3.9 0,813 0,1966 0,000 Valid
X3.10 0,784 0,1966 0,000 Valid
YP1 0,783 0,1966 0,000 <0,05 Valid
YP2 0,774 0,1966 0,000 Valid
YP3 0,722 0,1966 0,000 Valid
YP4 0,777 0,1966 0,000 Valid
YP5 0,769 0,1966 0,000 Valid
YP6 0,766 0,1966 0,000 Valid
YP7 0,707 0,1966 0,000 Valid
Table 1.Validity Test Results

All statement indicators have significant r values ​​lower than 0.05, as shown in Table 1, and the calculated r value is higher than the table r value. All aspects of these indicators are valid. The variables of this study can be measured appropriately using these indicators.

b. Reliability Test

Reliability is determined by how well the results hold up when we measure the same symptoms multiple times with the same instrument. When the reliability coefficient (r₁₁) is more than 0.6, the research instrument is considered reliable according to Cronbach's Alpha.

Variables Cronbach's Alpha Information
Digital Payment 0,928 Reliable
Government Support 0,910 Reliable
Islamic Business Ethics 0,927 Reliable
MSME Revenue 0,874 Reliable
Table 2.Reliability Test Results

Table 2 shows that all variables have Cronbach Alpha values ​​higher than 0.6. All research variables have been determined to be reliable based on the criteria mentioned previously.

2. Classical Assumption Test

Many statistical tests exist, varying from basic to complex methodologies, depending on the features of the data and the objectives or challenges of the research.

a. Normality Test

Creating a graph showing the distribution of scores is a basic way to check for normality. The simplicity of this approach makes the normality test highly dependent on the observer's accuracy in interpreting the graphical representation of the data. If the volume of data is substantial and its distribution deviates from normality, the possibility of error in conclusions increases. The normality test of residual values ​​and the Kolmogorov-Smirnov were used in this study. To reduce the possibility of error, the normality test was supplemented with the Probability Plot test. A detailed explanation of the evaluation process is provided below.

One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual
N 100
Normal Parametersa,b Mean .0000000
Std. Deviation 1.64239639
Most Extreme Differences Absolute .075
Positive .049
Negative -.075
Test Statistic .075
Asymp. Sig. (2-tailed)c .177
Monte Carlo Sig. (2-tailed)d Sig. .171
99% Confidence Interval Lower Bound .161
Upper Bound .181
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
d. Lilliefors' method based on 10000 Monte Carlo samples with starting seed 2000000.
Table 3.Kolmogorov-Smirnov Normality Test

The following is the result of the One Sample Kolmogorov-Smirnov test. Compared with the 0.05 limit, the two-sided significance level is 0.177. Based on this result, the residual data from this study follows a normal distribution. The results that pass the normality test follow a normal distribution.

The probability plot for the normality test is illustrated in Figure 3 below:

Figure 1.Results of Normality Test

Figure 2.Results of Normality Test

The second illustration shows a histogram of the trend to the right indicating a downward trend. Both sets of figures show a normally distributed distribution for the residual values ​​used in this analysis.

b. Multicollinearity Test

A number of independent variables in multiple regression analysis are represented by the correlation coefficient (r) value. This phenomenon can be understood by conducting a multicollinearity test. Variance Inflation Factor (VIF) and Tolerance Indicator can be used to detect multicollinearity. The model does not show multicollinearity if Tolerance is greater than 0.10. Once Tolerance drops below 0.10, multicollinearity occurs. Multiple correlation is present when the VIF score is greater than 10. It seems that the independent variables are not multicollinear, because their VIF scores are less than 10.

Variables VIF Tolerance Multikolinearitas
Digital Payment 1.018 0,982 Not occur
Government Suppor 1.021 0,980 Not occur
Islamic Business Ethics 1.039 0,963 Not occur
Table 4. Multicollinearity Test Results

Based on table 4, here are the test results:

VIF requirements, VIF < 10, conclusion: Multicollinearity does not occur.

X1: 1.018 is less than 10, there is no multicollinearity.

X2: 1.021 is less than 10, there is no multicollinearity.

X3: 1.039 is less than 10, there is no multicollinearity.

Tolerance requirements, Tolerance > 0.10 the conclusion is that there is no multicollinearity.

X1: 0.982 is greater than 0.10, there is no multicollinearity.

X2: 0.980 is greater than 0.10, there is no multicollinearity.

X3: 0.963 is greater than 0.10, there is no multicollinearity.

c. Heteroscedasticity Test

If there is a change in the absolute residual variation after data processing, then the heteroscedasticity test will determine it. If the assumption of no heteroscedasticity is violated, the interpretation of analytical data is disturbed in both small and large sample sizes, which causes reduced accuracy in estimating the regression coefficients. This study tests heteroscedasticity using scatterplot graphs.

Heteroscedasticity in scatter diagrams can be caused by the following things:

a. Some of the other data are below the zero line and some are above it.

b. Both above and below the zero line, the data points do not appear to be concentrated.

c. The data points do not follow a clear pattern, such as an up or down wave shape.

d. The data points should be randomly distributed, with no clear pattern. Figure 4 is a reference.

Figure 3.Heteroscedasticity Test Results

Above and below the zero line, the data in Figure 4 are scattered. The distribution of the points does not show any waves, and there is no pattern of expansion, contraction, and expansion. As a result, the research model meets the efficiency requirements for understanding the analysis findings.

By using scatter diagrams and the Glejser test, this study tests the possibility of heteroscedasticity. Assuming all independent variables have a Sig. value higher than 0.05, the Glejser test can eliminate heteroscedasticity from the regression model.

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.524 1.124 1.356 .178
Digital Payment -.022 .016 -.138 -1.366 .175
Government Support .002 .017 .010 .094 .925
Islamic Business Ethics .015 .016 .100 .982 .329
a. Dependent Variable: Abs_RES
Table 5.Glejser Test

The t-values ​​for the following variables Digital Payment, Government Support, and Islamic Business Ethics are 0.982, 0.094, and -1.366, respectively, according to the Glejser test. The significance levels of digital payment (0.175), Government Support (0.925), and Islamic Business Ethics (0.329) are all more than 0.05. Since all independent variables in this study have a significance level greater than 0.05, the regression equation model does not show heteroscedasticity.

3. Hypothesis Test

Statistical testing and calculation of test values, evaluation of test results, determination of significance levels, and finally, drawing conclusions are various stages that include the implementation of hypothesis testing in this study. The process begins with the formulation of the null hypothesis (H₀) and the alternative hypothesis (Ha).

1) Partial Test (t)

a) Making a hypothesis in a sentence description

b) Making a hypothesis in a sentence description

H0: Digital Payments, Government Support, and Islamic Business Ethics have an insignificant effect on MSMEs' Income.

Ha: Digital payments, Government Support, and Islamic Business Ethics have a significant effect on MSMEs' income.

Determining the level of significance (α)

c) Testing rules

If, t count < t table, then Ha is rejected while H0 is accepted.

If, t count > t table, then Ha is accepted while H0 is rejected.

d) Comparing t-table and t-count

The calculated t-value is compared with the t-table to ensure the assessment of the proposed hypothesis.

e) Making a decision

The final phase of this testing procedure is to ensure acceptance or rejection of the hypothesis based on the data obtained from the statistical calculations performed.

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 9.171 1.899 4.830 .000
Digital Payment .178 .028 .458 6.460 .000
Government Support .176 .028 .446 6.285 .000
Islamic Business Ethics .131 .026 .353 4.934 .000
a. Dependent Variable: MSME Income
Table 6.Partial Test Results

The regression equation is obtained from Table 6 above as follows:

Partial testing is used to test the independent variables against the dependent variable one by one. The table above shows the results of the t-test calculations for each variable X1, X2, and X3, with a significance value < 0.1, to determine whether they have an effect on the dependent variable Y by comparing the t-table with N = 100 samples and α = 0.05. The t-table value obtained is 1.98498, which results in:

a. Digital Payment Variable

The t-test for the Digital Payment variable (X1) shows a t-calculated value of 6.460 with a significance level of 5%. Since the t-calculated value (6.460) is greater than the t-table value (1.98498) and the significance value is less than 0.05, it can be concluded that, partially, the Digital Payment variable has a significant effect on the MSME Income variable (Y). The decision is that Ha is accepted, meaning that the Digital Payment variable has an effect on increasing MSME income in Medan.

b. Government Support Variable

The t-test for the Government Support variable (X2) shows a t-calculated value of 6.285 with a significance level of 5%. Since the t-calculated value (6.285) is greater than the t-table value (1.98498) and the significance value is less than 0.05, it can be concluded that, partially, the Government Support variable has a significant effect on the MSME Income variable (Y). The decision is that Ha is accepted, meaning that the Government Support variable has an effect on increasing MSME income in Medan.

c. Islamic Business Ethics Variable

The t-test for the Islamic Business Ethics variable (X3) shows a t-calculated value of 4.934 with a significance level of 5%. Since the t-calculated value (4.934) is greater than the t-table value (1.98498) and the significance value is less than 0.05, it can be concluded that, partially, the Islamic Business Ethics variable has a significant effect on the MSME Income variable (Y). The decision is that Ha is accepted, meaning that the Islamic Business Ethics variable has an effect on increasing MSME income in Medan.

2) Simultaneous Test (F)

By taking into account the total influence of all independent variables in the model, this test finds out whether the variable influences Y. Scheme of the testing process:

a. The dependent variable is MSME Income; the independent variables are digital payments, Government Support, and Islamic Business Ethics. At the same time, please describe the alternative hypothesis (H1) and the null hypothesis (H0) related to these variables.

b. Determine the acceptance and rejection zones in the F table by calculating the degrees of freedom (d = k; n - k) and setting α = 5% or 0.05.

c. The F-value from the table is compared with the F-value calculated using k degrees of freedom in the numerator and n minus k degrees of freedom in the denominator, all at a significance level of 5% (α). The following are the components needed to conduct a hypothesis test simultaneously: The null hypothesis (Ho) is rejected, indicating significance, if the F-count exceeds the F-table at α = 5%. The null hypothesis (Ho) is accepted, meaning statistically insignificant, if the F-count is smaller than the F-table at α = 5%. Here are the results.

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 297.311 3 99.104 35.626 .000b
Residual 267.049 96 2.782
Total 564.360 99
a. Dependent Variable: MSME Income
b. Predictors: (Constant), Islamic Business Ethics, Digital Payment, Government Support
Table 7.Simultaneous Test Results

Based on table 7, the F-count is 35.626 > from the F-table 2.70 and the F significance value is 0.00 < 0.05, so the hypothesis can be accepted. This shows that together the independent variables consisting of Digital Payment (X1), Government Support (X2), and Islamic Business Ethics (X3) have a significant effect on the dependent variable in this case, MSME Income (Y).

3) Test of Determination Coefficient

One way to assess how well a regression model captures changes in the dependent variable is to look at the coefficient of determination. A low R2 score indicates that the independent factors do not provide sufficient explanation for the dependent variable. Accuracy improves as the R2 value approaches 1. Thus, table 8 is derived.

Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .726a .527 .512 1.66786
a. Predictors: (Constant), Islamic Business Ethics, Digital Payment, Government Support
b. Dependent Variable: MSME Income
Table 8.Results of Determination Coefficient Test

Medan City MSMEs consider Islamic business principles, digital payments, and Government Support. Based on the results of the determination coefficient test, the corrected R square value is 0.512. These independent factors contribute 51.2% of the variance in MSME income in Medan City. The rest is influenced by other variables.

4. Multiple Linear Regression Test

The purpose of this study is to examine the relationship between X, MSME income, and Y, the relationship between digital payments, government assistance, and Islamic business principles. Linear regression analysis is used in this study. The results are presented in Table 9 below:

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 9.171 1.899 4.830 .000
Digital Payment .178 .028 .458 6.460 .000
Government Support .176 .028 .446 6.285 .000
Islamic Business Ethics .131 .026 .353 4.934 .000
a. Dependent Variable: Pendapatan UMKM
Table 9.Multiple Linear Regression Test

Using tabular data and multiple linear regression, we can obtain the following equation:

Y = a + b 1 X 1 + b 2 X 2 + b 3 X 3 + e

Y = 9.171+ 0.178X1 + 0.176X2 + 0.131X3 + e

Based on the equation, the following can be explained:

1. The constant a of 9.171 indicates that if the variables Digital Payment, Government Support, and Islamic Business Ethics remain constant, then MSME income will be only 9.171%.

2. The regression coefficient for the Digital Payment variable of 0.178 indicates that if the level of Digital Payment increases by 1%, MSME income will increase by 0.178%.

3. The regression coefficient for the Government Support variable of 0.176 indicates that if the level of Government Support for MSMEs increases by 1%, MSME income will increase by 0.176%.

4. The regression coefficient for the Islamic Business Ethics variable of 0.131 indicates that if the level of Islamic Business Ethics increases by 1%, MSME income will increase by 0.131%.

B. Discussion

1. The Influence of Digital Payment on MSME Income in Medan City

The results of the study indicate that digital payment elements affect MSME income. Although using a significance level of 0.00, the t-table value of 1.98498 and the t-count value of 6.460 are both higher than the threshold of 0.05. Ha is accepted because digital payments have a major impact on MSME income. Digital Payments contribute to increasing MSME income in Medan City.

Digital Payment is an automated service that facilitates digital transaction authorization using credit cards, debit cards, bank transfers, or electronic money, making it easier to shop online with safe and instant procedures. According to[13], one way to make monetary transactions is through a digital payment system, which utilizes electronic devices such as smartphones, tablets, and laptops. In this system, electronic money or e-money is recognized as a legitimate payment method and is increasingly used by the public. The main benefit of a digital payment system is its ability to facilitate and accelerate financial transactions without the need for cash or credit cards. One example is the implementation of QRIS which has been proven effective in facilitating transactions and increasing MSME income and digital payment systems such as QRIS can significantly increase consumer satisfaction [14]. Thus, MSMEs can increase their income by increasing operational efficiency and expanding market access made possible by the digital payment system [15].

This research is in accordance with research studies [16] with the title "Analysis of the Influence of Social Media and Digital Payment Usage on MSME Income in Medan City During the Covid-19 Pandemic", and also research [17] with the title "The Influence of E-Commerce, Social Media, Digital Marketing and Digital Payment on the Income of Fashion MSMEs in the Digital Era (Case Study at Little Bangkok Tanah Abang Market)". It is known that if the use of Digital Payment increases, it will also affect the Income of MSMEs in Medan City.

2. The Influence of Government Support on MSME Income in Medan City

Government Support has an effect on MSME income, according to the research results. With a significance level of 0.00 lower than 0.05, the calculated t value of 6.285 exceeds the t table value of 1.98498. Therefore, Ha can be accepted if there is a statistical relationship between Government Support and MSME income. MSME income in Medan City is driven by government subsidies.

Government assistance includes all policies, regulations, incentives, and resources provided by the government to encourage the growth and development of certain sectors, including MSMEs [18]. According to research [6], this assistance can be in the form of cash incentives, subsidies, favorable tax policies, and training programs to improve the competitiveness of small businesses. Effective government assistance can improve the competitiveness of MSMEs through various training initiatives and business mentoring. In addition, the government plays an important role in the current era of contemporary economic digitalization by encouraging the creation of an environment that supports the development of MSMEs.

This study is in accordance with research [19] with the title "Analysis of the Influence of Digital Marketing and Government Support on the Success of MSMEs in Medan City". It is known that if the use of Government Support increases, it will also affect the Income of MSMEs in Medan City.

3. The Influence of Islamic Business Ethics on MSME Income in Medan City

Such findings indicate a strong relationship between Islamic Business Ethics and MSMEs’ ​​profits. If we choose a significance threshold of 0.00 less than 0.05, we find that the estimated t-value of 4.934 is greater than the t-table value of 1.98498. Since MSMEs’ ​​income is influenced by Islamic Business Ethics, ha must be true. Companies in Medan City that adhere to Islamic business principles are more able to obtain financing.

The principles of sharia law, which underlie Islamic Business Ethics, emphasize the need to be honest, impartial, transparent, and socially responsible in all financial transactions [20]. The core of this view is that there must be harmony between the spiritual and social components of the business world and an emphasis on financial gain [21]. In Islamic Business Ethics, business actors are expected to adhere to principles such as integrity, equity, social accountability, and the prohibition of detrimental behavior, including usury and gharar [22]. Business ethics function as principles in carrying out daily activities based on integrity, transparency, and professionalism [23]. When applied to the MSME sector, this ethic has the potential to increase consumer trust and loyalty, which in turn can increase company revenue [24]. Therefore, the application of Islamic business principles to MSMEs in Medan City can be an important aspect in building a sustainable and highly competitive company.

This study is in accordance with research [25] with the title "The Influence of Islamic Business Ethics and Creativity on the Profits of Micro, Small and Medium Enterprises (MSMEs) in Boyolali Regency", and also research [26] with the title "The Influence of Islamic Business Ethics on Profits in Micro and Small Businesses in Watang Sawitto District, Pinrang Regency" It is known that if the implementation of Islamic Business Ethics increases, it will also affect the Income of MSMEs in Medan City.

4. The Influence of Digital Payment, Government Support, and Islamic Business Ethics on MSME Income in Medan City

This study found that in Medan City, MSME income (Y) is significantly influenced by digital payments (X1), government assistance (X2), and sharia business principles (X3). Using a significance threshold of 0.00 and an F value of 35.626, the results of the SPSS simultaneous F test evaluating the hypothesis validated the findings.

If the estimated F value (35.626 > 2.70) is greater than the F table value (0.00 < 0.05) and the significance value is less than 0.05, then the independent factors simultaneously influence the dependent variable.

Digital Payments (X1), Government Support (X2), and Islamic Business Ethics (X3) contributed 51.2% to MSME Income (Y) in Medan City. On the other hand, the remaining 48.8% (100% - 51.2%) was influenced by several variables, including company innovation, market access, marketing strategy, capital investment, competitive landscape, and other external influences.

In addition, there is a favorable correlation between Digital Payments (X1), Government Support (X2), and Islamic Business Ethics (X3) with MSME Income (Y). MSME income in Medan City will increase if one of these independent factors is increased.

Conclusion

This study found that digital payments boost the income of MSMEs in Medan City. To maximize transaction efficiency and expand market access, MSMEs must directly enter the digital payment system. Government assistance has a beneficial and substantial impact on MSME income. The government is expected to increase access to financing, support digitalization training initiatives, and increase the effectiveness of pro-MSME laws. MSMEs can increase their income by adopting Islamic business methods. So, in order to survive in business and gain customer trust, companies must follow the rules of Islamic Business Ethics, which include transparency and accountability. While other factors that contribute to the remaining 51.2% of the variation in MSME income in Medan City, digital payments, Government Support, and Islamic business principles all play a significant role.

Further research is recommended to investigate complementary elements that influence MSME revenue, including the impact of e-commerce platforms, the effectiveness of fiscal policies for MSMEs, and the level of digital technology adoption in various business sectors. Adding additional samples or a mixed-method approach could broaden the research focus and provide better insights.

Acknowledgement

The researcher would like to thank the parties who have helped this research to completion, especially the MSMEs in Medan which were the samples in this study.

References

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