JURNAL ILMIAH KOMPUTERISASI AKUNTANSI.
Vol.
No.
2 ,Desember 2024, pp:450-459 p-ISSN: 1979-116X .
e-ISSN : 2621-6248 .
Doi : 10.
51903/kompak.
http://journal.
id/index.
php/kompak n page 1 The Impact of QRIS Payment Usage on Business Income Growth in MSMEs Angelicia1.
Syarbini Ikhsan2.
Umiaty Hamzani3 ,Gita Desyana4.
Djunita Permata
Indah5
1,2,3,4,5
Universitas Tanjungpura Pontianak.
Indonesia Jl.
Prof.
Dr.
Hadari Nawawi.
Pontianak, 78124.
Indonesia Article Info Article history:
Received 17 September 2024
Received in revised form 14 Oktober
Accepted 13 November 2024
Available online 14 Desember 2024
ABSTRACT
This study aims to examine the effect of the implementation of the Quick Response Code Indonesian Standard (QRIS) in increasing business income, especially for Micro.
Small and Medium Enterprises (MSME.
using the Technology Acceptance Model (TAM) approach.
The method used in this study is a descriptive quantitative approach, which aims to provide an overview of the QR Code implementation.
The population in this study involved MSME owners, with a sample taken from 100 respondents through non-probability sampling Data collection was done through questionnaires.
Data analysis includes testing research instruments to assess data quality .
alidity and reliabilit.
, classical assumption test .
, as well as multiple linear regression analysis and hypothesis testing .
test and F tes.
The results show that QRIS implementation and user satisfaction have a significant influence on increasing MSME income, which supports TAM theory regarding the importance of perceived usefulness and perceived ease of use in technology acceptance.
However, other variables, such as QRIS usage literacy, convenience of use, and QRIS service price, did not show a significant influence on MSME Simultaneously, these factors still have an effect on MSME income, although with different variations in influence.
Keywords:
Quick Response Code Indonesian Standard (QRIS).
Micro.
Small and Medium Enterprises (MSME.
Technology Acceptance Model (TAM) and business revenue INTRODUCTION The continuous advancement of technology encourages companies to adapt to the digital environment (Alifia.
Permana, & Harnovinsah, 2.
In today's digital era, transformation in payment methods has become one of the key factors driving economic growth, particularly in the Micro.
Small, and Medium Enterprises (MSME.
One of the innovations gaining popularity is the use of digital payment systems, especially through the Quick Response Code Indonesian Standard (QRIS).
Received September 17, 2024.
Revised Oktober 14, 2024.
Accepted November 13, 2024 n The Impact of QRIS Payment Usage on Business Income Growth in MSMEs QRIS is an update to the Quick Response Code (QR Cod.
payment method, which was officially released by Bank Indonesia on January 1, 2020 (Mayanti, 2.
The utilization of QRIS by MSME actors can offer various benefits, including improved operational efficiency and business growth.
QRIS not only simplifies transactions but also enables MSMEs to reach more consumers through digital platforms.
By implementing QRIS, cash transactions can be simplified into cashless ones, making the buying and selling process easier for both sellers and buyers (Alifia.
Permana, & Harnovinsah, 2.
The growth of a country's digital economy is significantly influenced by advances in technology and information.
The changing transaction systems over time are a form of continuous innovation (Fahrudin & Isnaini, 2.
In today's internet age, an increasing number of Indonesians are using smartphones, which in turn opens greater opportunities for adopting cashless systems in various transactions.
This development reflects the evolution of the payment system, from the barter system .
efore money was introduce.
, physical currency, to the current cashless system.
Cashless transactions, now commonly known as cashless payments, are typically carried out through electronic transfers using services such as mobile banking .
-bankin.
(Fahrudin & Isnaini, 2.
The use of QRIS represents one of the manifestations of Indonesia's vision for a future payment system, aiming to reduce the use of cash while supporting the growth of Micro.
Small, and Medium Enterprises (MSME.
across regions.
This effort is being carried out by promoting digitalization to expand market access and increase competitiveness.
One of the innovations developed is the Quick Response Code Indonesian Standard (QRIS) payment system, which is a collaboration between Bank Indonesia and the Indonesian Payment System Association (ASPI).
QRIS is based on international EMV Co standards (Europay.
MasterCard.
Vis.
, ensuring that transactions can be accepted from various payment applications according to the buyer's country of origin.
The government is also working to educate MSME actors on the use of QRIS through digital payment applications and mobile banking, thereby increasing public understanding of this cashless payment system (Lyani.
Wismayanti, & Yudartha, 2.
Currently, cashless transactions have become easier because QRIS can be used through various platforms, such as mobile banking and e-wallet applications.
This enables cross-bank payments to be more practical.
For business owners.
QRIS offers many advantages, such as:
No need to prepare change with various denominations.
Avoiding the risk of counterfeit money.
Simplifying transaction records, making them more transparent and efficient.
Reducing the potential for misunderstandings in business administration (Fahrudin & Isnaini.
JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459 n p-ISSN : 1979-116X e-ISSN : 2621- 6248 From the consumer side.
QRIS makes payments easier without having to carry large amounts of cash.
This cashless system is more convenient because it can be accessed anytime and anywhere.
Meanwhile, for the government.
QRIS helps increase economic efficiency, reduces costs associated with printing, distributing, and managing cash, and supports state revenue through taxes.
All transactions that are recorded become more transparent and accountable (Nurhaliza.
Putri.
Atika, & Nofirda, 2.
For example, the consumption pattern of the people in Pontianak, which tends to be consumptive, shows great potential for the utilization of QRIS.
Business activities in various areas, such as culinary, basic goods, and clothing, are always bustling with visitors.
utilizing QRIS.
MSME actors in Pontianak can more easily serve customers without worrying about change or administrative errors.
Based on the research conducted by Alifia.
Permana, & Harnovinsah .
and Pratiwi.
Ningsih.
Amaliah, & Intan .
, there is still a significant research gap in understanding the relationship between the use of QRIS and the turnover or income of MSMEs.
The study by Alifia.
Permana, & Harnovinsah .
employed a qualitative approach that emphasizes the broad benefits of QRIS in increasing MSME income, highlighting national-level phenomena but lacking detail in examining the specific variables that drive this improvement.
Meanwhile.
Pratiwi.
Ningsih.
Amaliah, & Intan .
used a quantitative approach with nine independent variables and concluded that none of the variables had any significant effect.
Therefore, this study aims to bridge this gap by conducting a focused analysis that integrates both qualitative and quantitative approaches, exploring measurable factors and contextual nuances to better understand how the use of QRIS directly impacts the income of MSMEs.
Although the use of QRIS has shown potential in improving transaction efficiency and flexibility for MSMEs, many MSMEs still have not fully utilized this technology.
Existing studies mostly focus on the general benefits of QRIS without exploring how specific variables, such as perceived ease of use, perceived usefulness, and attitude toward use, contribute to the increase in MSME income.
Therefore, there is a need to gain a deeper JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459 n The Impact of QRIS Payment Usage on Business Income Growth in MSMEs understanding of how these factors influence the performance of MSMEs in the context of QRIS usage.
This study aims to analyze the impact of QRIS usage on the increase in MSME income, focusing on variables such as Perceived Ease of Use.
Perceived Usefulness, and Attitude Toward Using, which contribute to the adoption of QRIS technology in business METHOD Translation to English:
This study uses a descriptive quantitative approach to analyze the effect of QRIS usage on MSME income.
The independent variables examined include literacy on QRIS usage, application of QRIS usage.
QRIS usage ability.
QRIS usage comfort.
QRIS service cost.
QRIS usage satisfaction.
QRIS usage efficiency, and QRIS usage strategy, while the dependent variable is MSME income.
Data is collected through questionnaires distributed to MSME owners who have used QRIS and analyzed using multiple linear regression to test the influence of each variable on income.
The analysis technique used in this study applies non-probability sampling.
The nonprobability sampling method used is accidental sampling, which is a method of sample selection based on chance, where anyone who happens to meet the researcher can be used as a sample, if it is deemed that the person met is suitable as a data source.
The sample data obtained from the questionnaire consists of 100 respondents and will be analyzed using quantitative documents, including data quality tests (Validity.
Reliabilit.
, classical assumption tests (Normalit.
, determination, multiple linear regression, and hypothesis testing using t-test .
F-test .
with alpha = 5%.
Data processing is done using SPSS version 29 software, which will facilitate the researcher in performing the data Table 1.
Research Variables Variable Indicator Source QRIS Usage Understanding the concept (Alifia.
Permana, & Harnovinsah.
Literacy of QRIS.
Seeking 2.
and (Pratiwi.
Ningsih.
Amaliah, (X1_LP) information about QRIS & Intan, 2.
QRIS Implementing QRIS in (Hidayat.
Aini, & Fetrina, 2.
Application Understanding (Mayanti, 2.
, (Alifia.
Permana, & (X2_PP) QRIS Harnovinsah, 2.
, (Riantika & Ayuningsasi, 2.
, (Pratiwi.
Ningsih.
Amaliah, & Intan, 2.
, (Fahrudin & Isnaini, 2.
, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
QRIS
Usage 1.
Frequency of QRIS use for (Siswoyo Irianto, (X3_PG) transactions in business.
(Adnyasuari & Darma, 2.
, (Arianti.
Darma, & Mahyuni, 2.
, (Alifia.
JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459
n QRIS
Usage
Ability (X4_KP) QRIS
Usage
Comfort
(X5_HLP)
QRIS Service Price
(X6_KPG)
QRIS
Usage
Satisfaction (X7_PEP) QRIS
Usage
Efficiency Improvement
(X8_SEP)
QRIS Payment Strategy (X9_SPP) p-ISSN : 1979-116X e-ISSN : 2621- 6248 Other methods used besides Permana, & Harnovinsah, 2.
QRIS.
(Pratiwi.
Ningsih.
Amaliah, & Intan, 2.
, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
, 2.
Confidence in (Hidayat.
Aini, & Fetrina, 2.
, implementing QRIS.
(Nurhaliza.
Putri.
Atika, & Nofirda.
Desire to improve QRIS 2.
, (Sihaloho.
Ramadani, & usage skills.
Rahmayanti, 2.
, (Arianti.
Darma, & Mahyuni, 2.
, (Alifia.
Permana, & Harnovinsah, 2.
, (Pratiwi.
Ningsih.
Amaliah.
Intan, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
, 2.
Feeling comfortable using (Sihaloho.
Ramadani, & Rahmayanti.
QRIS as a payment method.
(Alifia.
Permana.
Understanding time Harnovinsah, 2.
, (Pratiwi.
Ningsih, efficiency during QRIS Amaliah.
Intan, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
, 2.
Evaluation of the cost (Nurhaliza.
Putri.
Atika, & Nofirda, charged for QRIS usage in 2.
, (Sihaloho.
Ramadani, & Deciding to Rahmayanti, 2.
, and (Hairani, et al.
use QRIS based on the 2.
service price charged.
MSME satisfaction with (Hidayat.
Aini, & Fetrina, 2.
, using QRIS in transactions.
(Sihaloho.
Ramadani, & Rahmayanti.
Recommending QRIS to 2.
, (Alifia.
Permana, other MSMEs that have not Harnovinsah, 2.
, (Pratiwi.
Ningsih, implemented it.
Amaliah.
Intan, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
, 2.
Feeling an increase in (Saputra, 2.
, (Nurhaliza.
Putri, operational efficiency when Atika, & Nofirda, 2.
, (Sihaloho, implementing QRIS in Ramadani, & Rahmayanti, 2.
, (Alifia.
Permana, & Harnovinsah.
Understanding how much 2.
, (Pratiwi.
Ningsih.
Amaliah, & time is needed in a single Intan, 2.
, and (Mukarromah & QRIS transaction.
Amelya, 2.
Considering QRIS as a (Sihaloho.
Ramadani, & Rahmayanti, long-term payment tool in 2.
, (Alifia.
Permana.
Understanding Harnovinsah, 2.
, (Pratiwi.
Ningsih.
JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459 n The Impact of QRIS Payment Usage on Business Income Growth in MSMEs other facilities that QRIS can offer to attract consumers.
MSME Income 1.
Feeling an increase in (Y_PN) income after using QRIS.
How much income has increased after using QRIS.
Comparison of income before and after QRIS usage.
Amaliah, & Intan, 2.
, and (Mukarromah & Amelya, 2.
(Nurhaliza.
Putri.
Atika, & Nofirda, 2.
, (Sihaloho.
Ramadani, & Rahmayanti, 2.
, (Alifia.
Permana, & Harnovinsah, 2.
, (Riantika & Ayuningsasi, 2.
, (Pratiwi.
Ningsih.
Amaliah.
Intan, (Mukarromah & Amelya, 2.
, and (Hairani, et al.
, 2.
DISCUSSION/CONCLUSION .
PT)
Validity and Reliability Test Table 2.
Validity Test Variable Indicator Table R Calculated R Sig Description X1_LP.
000 Valid
X1_LP
X1_LP.
000 Valid X2_PP.
000 Valid
X2_PP
X2_PP.
000 Valid X3_PG.
000 Valid
X3_PG
X3_PG.
000 Valid X4_KP.
000 Valid
X4_KP
X4_KP.
000 Valid 000 Valid X5_HLP X5_HLP.
X5_HLP.
000 Valid X6_KPG.
000 Valid
X6_KPG
X6_KPG.
000 Valid 000 Valid X7_PEP X7_PEP.
X7_PEP.
000 Valid 000 Valid X8_SEP X8_SEP.
X8_SEP.
000 Valid 000 Valid X9_SPP X9_SPP.
X9_SPP.
000 Valid Source: Processed data, 2024 Based on the results in Table 2, the validity test indicates that all the indicators used to measure the variables in this study have correlation coefficient values greater than the table value of rtabel = 0.
195, so all indicators are valid.
In addition to comparing the values of rtabel and rhitung, the results of the validity test show that all the indicators have a Sig.
JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459 n p-ISSN : 1979-116X e-ISSN : 2621- 6248 value below 0.
05, specifically 0.
000, further supporting that all indicators used in this study are valid.
Table 3.
Reliability Test Variable Cronbach Alpha N Description 2 Reliable X1_LP 2 Reliable X2_PP 2 Reliable X3_PG 2 Reliable X4_KP 2 Reliable X5_HLP 0.
2 Reliable X6_KPG 0.
2 Reliable X7_PEP 2 Reliable X8_SEP 0.
2 Reliable X9_SPP 0.
3 Reliable Y_PN Source: Processed data, 2024 Table 3 above shows the reliability test results for each variable used in the study, where the Cronbach Alpha values are greater than 0.
6, indicating that all variables in this study are Classical Assumption Test Table 4.
Normality Test One-Sample Kolmogorov-Smirnov Test Unstandardized Residual N: 100 Normal Parameters a.
b: Mean = 0.
Std.
Deviation = 1.
Most Extreme Differences:
Absolute = 0.
Positive = 0.
Negative = -0.
Test Statistic = 0.
Asymp.
Sig.
-taile.
= 0.
Source: Processed data, 2024 Based on Table 4, the normality test results show a significance value of 0.
200, which is greater than 0.
This indicates that the residuals are normally distributed.
Since the data is normally distributed, the analysis can proceed to the regression analysis stage.
Table 5.
Multicollinearity Test Variable Tolerance VIF Description 575 No Multicollinearity X1_LP 615 No Multicollinearity X2_PP 149 No Multicollinearity X3_PG 147 No Multicollinearity X4_KP 379 No Multicollinearity X5_HLP 0.
JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
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Desember 2024: 450 Ae 459 n The Impact of QRIS Payment Usage on Business Income Growth in MSMEs 250 No Multicollinearity X6_KPG 0.
138 No Multicollinearity X7_PEP 0.
593 No Multicollinearity X8_SEP 0.
432 No Multicollinearity X9_SPP 0.
Source: Processed data, 2024 The multicollinearity test results show that there is no significant multicollinearity problem between the independent variables in the regression model.
Based on the Variance Inflation Factor (VIF) values, all variables show values smaller than the established threshold .
, and the tolerance values are below 0.
10, so it can be concluded that the independent variables do not have high correlation with each other.
This indicates that the relationships between these variables do not cause instability in the regression coefficient Therefore, the regression analysis can proceed under the assumption that multicollinearity is not a concern in this model.
Table 6.
Heteroskedasticity Test Variable Sig.
Description 795 No Heteroskedasticity X1_LP 452 No Heteroskedasticity X2_PP 581 No Heteroskedasticity X3_PG 386 No Heteroskedasticity X4_KP X5_HLP 0.
100 No Heteroskedasticity X6_KPG 0.
380 No Heteroskedasticity X7_PEP 0.
370 No Heteroskedasticity X8_SEP 0.
962 No Heteroskedasticity X9_SPP 0.
685 No Heteroskedasticity Source: Processed data, 2024 The heteroskedasticity test results using the Glejser test show no indication of heteroskedasticity in this regression model.
The significance values are all greater than 0.
which means the residual variance is not dependent on the independent variable values, indicating that the regression model does not experience heteroskedasticity.
Therefore, the assumption of homoskedasticity is met, and the regression analysis can proceed without interference from heteroskedasticity.
Hypothesis Testing Table 7.
Coefficient of Determination Test Model Summaryb Model | R | R Square | Adjusted R Square | Std.
Error of the Estimate 1 | 0.
713 | 0.
508 | 0.
459 | 1.
Source: Processed data, 2024 With an Adjusted R Square value of 0.
459, the regression model in this study can explain 9% of the variability in the data, indicating that the model has a moderate ability to explain the relationship between the independent and dependent variables.
However, about JURNAL ILMIAH KOMPUTERISASI AKUNTANSI Vol.
No.
Desember 2024: 450 Ae 459 n p-ISSN : 1979-116X e-ISSN : 2621- 6248 1% of the variability remains unexplained by this model, which could be due to other variables not included or factors that cannot be measured.
Therefore, while the model is reasonably effective, further analysis is needed to REFERENCES