Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 485 https://internationalpubls.com Gaps in Access to People's Business Credit Financing for MSEs in Depok, West Java Experimental Design Approach 1 Irma Setyawati,2 Raden Parianom,3 Andini Nurwulandari,4 Dipa Teruna Awaludin,5 Risna Triandhari 1Management Department Faculty Economic and Business Universitas Nasional Jakarta, Indonesia,2 Economic sciences Department Faculty Economic and Busines UPN Veteran Jakarta, Indonesia,3 Management Department Faculty Economic and Business Universitas Nasional Jakarta, Indonesia,4 Accounting Department Faculty Economic and Business Universitas Nasional, Indonesia,5 Economics Department Faculty Economic and Business Universitas Nasional, Indonesia Email: irmasetyawati@civitas.unas.ac.id, radenparianom@upnvj.ac.id, andini.nurwulandari@civitas.unas.ac.id, dipateruna@civitas.unas.ac.id, risnatriandhari@ui.ac.id Correspondence: irmasetyawati@civitas.unas.ac.id Article History: Received: 26-10-2024 Revised:10-11-2024 Accepted:18-12-2024 Abstract: This research investigates the challenges encountered by micro and small enterprises (MSEs) in Depok, Indonesia, in accessing the Kredit Usaha Rakyat (KUR) program and explores how these obstacles impact poverty reduction and income distribution. Employing an experimental design, the study focuses on key factors affecting financial access, including MSEs' comprehension of KUR, business age, financial reporting practices, and the adoption of technology in marketing. A total of 147 MSEs were divided into treatment and control groups, where the treatment group received targeted interventions through Focus Group Discussions (FGDs). Data was collected both before and after the intervention to assess its impact on KUR access. The findings reveal a marked improvement in KUR access for the treatment group, particularly in terms of enhanced understanding of KUR procedures and significantly improved financial reporting capabilities. Additionally, the increased adoption of technology in marketing was found to positively influence financial access. Regression analysis demonstrates that factors such as KUR understanding and financial reporting practices have a statistically significant effect on financial accessibility, while business age exerts minimal influence. Conversely, the control group did not exhibit any substantial changes in KUR access, highlighting the efficacy of the intervention. In conclusion, this study emphasizes that structured interventions, such as FGDs, are effective in strengthening MSEs' ability to secure financing through KUR, which is pivotal for poverty alleviation and economic inclusion. The results underscore the necessity for ongoing training and support programs to sustain MSEs' growth and financial stability. Keywords: Experimental design; KUR; poverty gap; access to finance; MSEs mailto:@civitas.unas.ac.id mailto:risnatriandhari@ui.ac.id mailto:irmasetyawati@civitas.unas.ac.id Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 486 https://internationalpubls.com INTRODUCTION The Ministry of PPN/Bappenas developed the National Long-Term Development Plan 2025-2045 in support of the Golden Indonesia Vision 2045, realizing Indonesia as a "Sovereign, Advanced, Sustainable Archipelago". The goals of the RPJPN Golden Indonesia Vision 2025-2045 include five things: Indonesia's per capita income is on par with developed countries; poverty is heading towards 0% and inequality is reduced, Indonesia is targeting a gini ratio in the range of 0.290-0.320; the contribution of Eastern Indonesia's GRDP in 2045 is targeted at 28.5; increased leadership and influence in the international world, Indonesia is targeting to enter the top 15 Global Power Index; the competitiveness of human resources is increasing. Indonesia targets a Human Capital Index value of 0.73. Greenhouse gas emission intensity towards net zero emission, Indonesia targets to reduce greenhouse gas emission intensity by 93.5% (Bappenas, 2022). The goal of the Golden Indonesia vision, in resolving poverty, is a situation where a person is unable to maintain himself in accordance with the standard of living of his group, unable to utilize his energy, mentality, and mind. The key to eradicating poverty is access to education, health, and infrastructure. The American Episcopal Conference (Garneau, 2001) formulated three meanings of poverty, namely (1) real poverty, born of injustice, manipulation, and violence, (2) poverty because a person is not considered human, loses the right to life, and freedom of choice, (3) spiritual poverty, loss of spiritual awareness, a sense of solidarity with others, especially with the poor and in need of liberation. Meanwhile, the Sustainable Development Goals (SDGs) is a global and national commitment to the welfare of society that includes 17 global goals and targets for 2030 declared by developed and developing countries at the UN General Assembly in September 2015. It expresses a global call to take urgent action to save the planet. In this regard, the private sector is one of the key stakeholders that can shoulder the fundamental responsibility of accelerating the process of SDGs implementation (Rashed & Shah, 2021). Regarding the first item in the 17 global goals and targets of the 2030 SDGs, namely zero poverty, in September 2019, Indonesia's poor population reached 24.78 million (9.221%), the lowest percentage since 2014. In March 2021, the poverty rate in Indonesia increased by 10.14% or 27.54 million people, due to COVID-19 that hit all over the world. Figure 1 shows the development of the number of poor people, September 2019-March 2023. Source: (3)BPS, 2023 Figure 1: Development of the Number of Poor People, September 2019-March 2023 Figure 1 shows that the number of poor people in March 2023 was 25.90 million, a decrease of 0.46 million people against September 2022 and a decrease of 0.26 million people against March 2022. The percentage of poor people in March 2023 was 9.36%, down 0.21% from September 2022 and down 0.18% from March 2022. In the provinces of Banten, DKI Jakarta and West Java, there was a decrease in the depth and severity of poverty from 2018-2021, and in 2022, some provinces the index rose. This means that among the poor, although they have not been able to get out of the poverty line, there has been an increase in income even though the amount is small. DKI Jakarta as the capital city and buffer zone still has gaps Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 487 https://internationalpubls.com in its income distribution.Table 1 shows the index of poverty depth and severity in the provinces of Banten, DKI Jakarta and West Java in 2018-2022. Poverty Depth and Severity Index in Banten, DKI Jakarta and West Java Provinces, 2018-2022 No. Province Poverty Depth Index (P1) Poverty Severity Index (P2) 2018 2019 2020 2021 2022 2018 2019 2020 2021 2022 1 BANTEN 0,685 0,625 0,91 1,06 0,835 0,16 0,17 0,245 0,29 0,185 2 DKI JAKARTA 0,55 0,45 0,63 0,695 0,725 0,11 0,09 0,13 0,16 0,175 3 WEST JAVA 1,095 1,005 1,1 1,295 1,175 0,275 0,235 0,23 0,32 0,28 Source: BPS (2022) Based on Table 1, there is a gap in income distribution between Jakarta and West Java provinces. Meanwhile, Banten province does not differ much from Jakarta province, because the two provinces are located together and the population mobilization from Banten to Jakarta is quite high. The government has been consistent in its efforts to reduce poverty, since 1983 the government has been deregulating structural adjustments and restructuring the economy. The government has attempted to alleviate poverty through Law No. 20/2008 on Micro, Small and Medium Enterprises. However, deregulation in the areas of trade and investment has not benefited MSEs, rather large companies and conglomerates have benefited. Empirical studies prove that value-added is not enjoyed by small, medium and large-scale companies, it is conglomerate-scale companies, with a workforce of more than 1000 people, that enjoy an increase in value-added in absolute terms and per average company (Gandhi et al., 2021; Trie et al., 2022). There are still several obstacles for MSEs to develop faster, including difficulties for MSEs to penetrate the market, weaknesses in business development and strengthening, and difficulties in obtaining sources of financing from formal financial institutions. MSEs, which are mostly engaged in the informal sector, have weak access to bank credit. One of the reasons is the administrative requirements of banks, especially collateral issues that cannot be met, especially for micro and small business actors. Credit allocation to MSEs during 2018 was still 19.9% (Setyawati, 2009; Lestari, 2021; Ismiyanti & Mahadwartha, 2020; Bafadal et al., 2022; Soleiman et al., 2023). Economic accessibility theory explains how economic and non-economic factors affect the ability of individuals or groups to access financial resources and economic opportunities. In this context, accessibility often refers to the ability to use financial services, such as credit, and how barriers in this process can impair the ability of individuals or businesses to proceed (Ghosh, F., & Shrestha, 2020). In the context of MSEs and Kredit Usaha Rakyat (KUR), economic accessibility theory can help in identifying and understanding the various constraints that prevent MSEs from making the most of this program (Huston, 2010; Irjayanti & Azis, 2012). The theory of economic opportunity and entrepreneurship is particularly relevant in the context of Micro and Small Enterprises (MSEs) and People's Business Credit (KUR) because it is an approach that examines the extent to which individuals and groups pursue and utilize economic opportunities to create businesses and innovations. This theory links the concept of entrepreneurship to access to economic time and money, and how these factors influence business success (Alvares & Barney, 2020). In addition, in the context of MSEs and KUR, risk management theory has several important applications as this approach is related to the identification, evaluation, and mitigation of risks to reduce negative impacts that could harm individuals, businesses, or organizations. In the context of Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 488 https://internationalpubls.com business and credit access, it is important to understand how risks can influence business decisions and potential mitigation strategies (Van den Boom, 2020; Mashiri, 2022). Thus, theories of economic accessibility, economic opportunity and risk management, as well as risk management theory, are highly relevant in analysing barriers to entry for MSEs in the KUR program, including poverty reduction and income equality. By understanding and analyzing the components of economic accessibility theory, economic opportunity theory and business strategy, as well as risk management theory, MSEs will be better able to identify and mitigate the risks they face when interacting to access the KUR program. MSEs will also be better able to analyse how to use programs similar to KUR to teach business skills and how to maximise the benefits of existing resources. Government policy to assist MSEs began in November 2007, by issuing the KUR program for MSE actors, as per Presidential Instruction Number 6 of 2007 concerning Policies to Accelerate Real Sector Development and Empower MSEs, especially in the field of Financial Sector Reform, then continued by government policy on the Procedures for Implementing Interest Subsidies for KUR through PMK Number 20/PMK.05/2016. The attention to developing MSEs is based on the reason that MSEs absorb a lot of labor, especially the use of local natural resources, so that the growth of MSEs will have a positive impact on increasing the number of workers, reducing the number of poverty, equity in income distribution, and economic development in rural areas (Nazroi et al., 2022). Through the KUR program, the government hopes to accelerate the development of economic activities, especially in the real sector, especially for poverty reduction and expansion of employment opportunities (Courtney Kurlanska, 2010; Farida et al., 2015; Djufri et al., 2021). The purpose of this research is to analyze the barriers to MSEs' access to the People's Business Credit (KUR) program, in an effort to accelerate poverty reduction and income equality. The target of the study is to improve the KUR program for MSEs in an effort to accelerate poverty reduction. This study aims to identify and formulate policy alternatives that are useful for loosening the various factors that hinder MSEs' access to the KUR program so as to increase the role of MSEs in accelerating poverty reduction. It is hoped that the development of MSEs will become government policy in accelerating development and alleviating poverty and become the focus of research around the world. Sustainable Development Goals are global and national commitments in an effort to improve the welfare of society (Ali Soytas, 2015; Sachs, 2015; Fonseca et al., 2020; Biermann et al., 2022). METHODOLOGY This research uses data collection methods by conducting field research and experimental design. Field research is conducted by distributing questionnaires to respondents and interviews (Setyawati & Suroso, 2017), while experimental design, is research that allows researchers to control all external variables that affect the experiment, to achieve high internal validity (Haaland, 2020). Data sources consist of primary data obtained from field surveys in the Depok area, West Java, from business actors (MSEs), financial institutions and government officials and secondary data by conducting literature studies. The distribution of samples and respondents in Depok, West Java was determined by purposive sampling. To ensure that the data collected is easy to tabulate, process and analyze, a data collection instrument is needed, consisting of a questionnaire for local government officials to measure program implementation performance, local government competence, commitment and focus of attention, MSE empowerment policies, and the root causes of MSE empowerment implementation in Depok, West Java, addressed to the Head of the Agency in charge of Cooperative and MSE development, representatives of the Regional Head, and representatives of local apparatus staff within the agency in charge of cooperative and MSE development. http://kur.ekon.go.id/upload/peraturan/PMK20th.2016.pdf http://kur.ekon.go.id/upload/peraturan/PMK20th.2016.pdf http://kur.ekon.go.id/upload/peraturan/PMK20th.2016.pdf Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 489 https://internationalpubls.com This research methodology uses an experimental design by providing assistance through Focus Group Discussions (FGDs) to Micro and Small Enterprises (MSEs) in Depok. This approach aims to examine the influence of MSEs' level of understanding of People's Business Credit (KUR), age of the MSE, ownership of financial statements, and use of technology in marketing on ease of access to financing. Through FGDs, MSEs are provided with relevant information and training to improve their understanding and skills in these aspects. The experiment involved dividing MSEs into control and treatment groups. The treatment group received intensive mentoring through FGDs, while the control group did not receive any similar intervention. Data was collected before and after the intervention to measure changes in ease of access to finance. Table 2 shows the distribution of respondents in Depok, West Java. Table 2: Distribution of MSE Respondents in Depok, West Java. Data Source (people) Total Treatment Group Control group Implementing Bank Guarantor Institution Related services MFI/KSP 27 120 9 9 7 9 136 Source: Primary data The division of treatment and control groups, based on field observations that have been made, so that the following justifications are taken 1. Limited Resources: ● Intensity of Intervention: Assistance through FGDs is resource-intensive in terms of time, experts, and operational costs. Therefore, only a small number of MSEs can be effectively engaged in the treatment group. ● Efficiency of Implementation: Organizing FGDs with too many participants can reduce the effectiveness of discussions and mentoring. Smaller groups allow for more in-depth and focused interactions. 2. Participant Availability and Suitability: ● Selection Criteria: There were only 26 MSEs that met specific criteria to receive the intervention, such as level of readiness, special needs, or willingness to participate intensively. ● Participant Commitment: Participants in the treatment group may have to commit to a more intense set of activities, limiting their numbers to those who are truly prepared. 3. Experimental Research Design: ● Exploratory or Pilot Studies: these are the initial stages of testing the effectiveness of an intervention, a smaller treatment group size is acceptable as a first step before scaling up. ● Focus on Data Quality: smaller treatment groups allow researchers to focus more on collecting in- depth, high-quality data. Questionnaires for MSEs as objects of empowerment program implementation to measure the performance of program implementation, and the root causes of MSE empowerment implementation in the regions. The questionnaire is addressed to cooperative administrators and entrepreneurs involved in local government empowerment programs. Respondents were MSE actors, cooperatives, agencies, MFIs and experts. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 490 https://internationalpubls.com To identify factors that influence the ease of access to financing, such as KUR, quantitative and qualitative analysis methods are used. Qualitative research can use two approaches, a direct approach and an indirect approach. In this research, the direct method is used with in-depth interviews and focus group discussions with relevant stakeholders. Meanwhile, the empirical model is used to strengthen the research results, to see the factors that influence MSEs to have access to financing, especially KUR. The method used will use Ordinary Least Square (Gujarati & Porter, 2010; Setyawati, 2016, 2017). In this study, we will look at the impact before MSEs receive a mentoring workshop on easy access to financing and after the implementation of the mentoring workhsop. The first model was used to look at the factors that influence MSEs to accept KUR: ...............................................(1a) Where: Y : Ease of access to KUR financing X1 : MSEs' level of understanding of KUR X2 : UMK Age X3 : Have financial statements X4 : Marketing that already uses technology Equation 1 shows the factors that influence the ease of access to KUR financing. Model 1 will be estimated before FGD assistance and after FGD assistance in the treatment and control groups. In addition to using data from the questionnaire, this study also uses macro data for the city of Depok to see the impact of MSE growth and the amount of MSE credit on income inequality and the poverty gap level, so a model like Table 3 will be used (Gujarati & Porter, 2010). Table 3. Model of Income Inequality and Poverty Gap Levels Variables Explanation Poverty gap (Y )1 Measures the average level of income below the poverty line, as a percentage of the poverty line. Gini coefficient growth (Y )2 The Gini coefficient is the ratio of the area between the Lorenz curves. High values represent high levels of inequality Source: (Kanayo et al., 2013) Where: X1 : Total MSEs X 2: Credit Value of MSEs in Depok City X3 : Depok city inflation X4 : BI Rate RESULT AND DISCUSSION From the entire population of MSEs in Depok City, there were 147 people who were used as research samples in a Focus Group Discussion forum with the aim of exploring opinions, views, and perceptions about a barrier to MSE access to the People's Business Credit (KUR) program, in an effort to accelerate poverty reduction and income distribution in depth. Group discussions allow ideas to emerge that may not be fully realized with alternative methods. In addition, a questionnaire was distributed to MSEs to determine the characteristics of respondents regarding the businesses they operate. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 491 https://internationalpubls.com MSEs in Depok city, West Java the ownership status is wife (female), which is 79 people (54%), this phenomenon could be due to women starting a business to supplement family income due to economic difficulties, and as a result, they have more time to manage their work schedule. In addition, the Government and NGOs have implemented many programs to support women in their businesses and increase their participation in the family economy and social and economic factors have an important role in advancing women's businesses in Indonesia (Egan & Tosanguan, 2009; Kanayo et al., 2013; Utami CW., 2017; Granata et al., 2018). The age of MSE owners in Depok city, West Java is between 41 - 50 years old with a total of 65 people (44%). This phenomenon may be due to the fact that individuals in the 41-50 age range have significant work experience and have access to larger credit limits to start a business. Individuals in this age range may seek opportunities to increase group cohesion through entrepreneurial ventures. Increased social capital and market knowledge can help facilitate business activities. For Indonesian entrepreneurs, family values and the desire to increase profits are the most important motivators (Lévesque & Minniti, 2006; Purwana & Suhud, 2017; Purnawan et al., 2023). Most of the latest education (80 people or 54%) of MSE owners in Depok city, West Java is Diploma/Bachelor degree. This phenomenon could be due to basic knowledge in management, accounting, marketing and other skills essential for running a business in Higher Education. Higher education institutions usually have wider access to information, technology and professional networks. This can help them acquire the necessary resources to start and grow their business as well as the relationships they build at work, which may have caused some hesitation about creating their own work schedule through franchising. They become more aware of the need to start their own business after receiving rigorous education (Tambunan, 2019; Parangkulan, 2023). After providing assistance through FGDs to MSEs in Depok, the results showed a significant increase in the ease of access to KUR financing for MSEs involved in the treatment group. MSEs that received the FGD intervention showed an increased understanding of KUR, from the application procedures to the benefits offered. In addition, they were also more skilled in preparing financial reports and more active in utilizing technology in marketing their products. The data estimation results indicate that the variables of MSEs' level of understanding of KUR, ownership of financial statements, and the use of technology in marketing have a positive and significant influence on the ease of access to financing. Meanwhile, the age variable of MSEs does not show a significant influence in this context. This confirms that mentoring through FGDs is effective in improving the key factors that make it easier for MSEs to access sources of financing, especially from formal financial institutions. The control group in this study consisted of MSEs that did not receive assistance through FGDs. The results of the analysis show that the control group did not experience any significant changes in their ease of access to financing after the research period. Their level of understanding of KUR, ability to prepare financial statements, and use of technology in marketing remained relatively stagnant compared to before the study began. A comparison between the control and treatment groups confirmed the effectiveness of the intervention through FGDs. While the treatment group showed significant improvements in key variables, the control group showed no significant changes. This indicates that without the mentoring and training provided, MSEs are less likely to experience improvements in ease of access to finance. This finding reinforces the importance of mentoring programs to help MSEs improve their capacity and competence in accessing formal sources of financing. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 492 https://internationalpubls.com Treatment Group Before FGD Assistance: Estimation result Ease of Access to Financing = 0.75 + 0.18 (Level of Understanding of KUR) + 0.004 (Age of MSEs) + 0.22 (Having Financial Statements) + 0.15 (Marketing Using Technology) + ε1 Table 4. Estimation Results Before FGD Assistance Variables Coefficient Standard Error Value of t p-value Intercept (α) 0,75*** 0,12 6,25 0,001 KUR Understanding Level (β₁) 0,18*** 0,06 3,00 0,003 Age of MSEs (β₂) 0,004** 0,002 2,00 0,048 Having Financial Statements (β₃) 0,22*** 0,08 2,75 0,007 Marketing with Technology (β₄) 0,15** 0,07 2,14 0,035 R² 0,65 Source: researcher estimation results ***significant at 1% **significant at 5% After FGD Facilitation: Estimation Results Ease of Access to Financing = 1.50 + 0.40 (Level of Understanding of KUR) + 0.002 (Age of MSEs) + 0.45 (Having Financial Statements) + 0.35 (Marketing Using Technology) + ε2 Table 5. Estimation Results After FGD Assistance Variables Coefficient Standard Error Value of t p-value Intercept (α) 1,50*** 0,10 15,00 0,001 KUR Understanding Level (β₁) 0,40*** 0,05 8,00 0,001 Age of MSEs (β₂) 0,002** 0,001 2,00 0,048 Having Financial Statements (β₃) 0,45*** 0,06 7,50 0,001 Marketing with Technology (β₄) 0,35*** 0,05 7,00 0,001 R² 0,87 Source: researcher estimation results ***significant at 1% **significant at 5% After the implementation of mentoring through Focus Group Discussions (FGDs), there was a significant improvement in the variables affecting ease of access to financing for MSEs. The intercept (α) increased from 0.75 to 1.50, indicating a basic improvement in the overall ease of access to financing. The coefficient β₁ (Level of Understanding of KUR) increased from 0.18 to 0.40, with a decrease in the p-value, indicating a higher significance and important role of understanding KUR after the mentoring intervention. Furthermore, the coefficient of β₃ (Owning Financial Statements) increased from 0.22 to 0.45, indicating that ownership of financial statements has a greater influence on the ease of access to financing after mentoring. The coefficient of β₄ (Marketing with Technology) also increased from 0.15 to 0.35, indicating that the role of technology in marketing is increasingly significant in facilitating access to financing. The increase in the R² value from 0.65 to 0.87 indicates that the regression model after FGD mentoring has a stronger ability to explain the variability of data related to ease of access to financing. This finding confirms the effectiveness of FGD mentoring in strengthening the influence of Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 493 https://internationalpubls.com the independent variables on the dependent variable, so that MSEs are better able to access formal sources of financing. Control Group Before FGD Assistance: Estimation Results Ease of Access to Financing = 0.80 + 0.17 (Level of Understanding of KUR) + 0.004 (Age of MSEs) + 0.23 (Having Financial Statements) + 0.16 (Marketing Using Technology) + ε3 Table 6. Estimation Results Before FGD Assistance Variables Coefficient Standard Error Value of t p-value Intercept (α) 0,80*** 0,13 6,15 0,001 KUR Understanding Level (β₁) 0,17*** 0,06 2,83 0,006 Age of MSEs (β₂) 0,004** 0,002 2,00 0,048 Having Financial Statements (β₃) 0,23*** 0,08 2,88 0,005 Marketing with Technology (β₄) 0,16** 0,07 2,29 0,023 R² 0,67 Source: researcher estimation results ***significant at 1% **significant at 5% After the Research Period (Without FGD Assistance): Estimation Results Ease of Access to Financing = 0.82 + 0.18 (Level of Understanding of KUR) + 0.004 (Age of MSEs) + 0.24 (Having Financial Statements) + 0.17 (Marketing Using Technology) + ε4 Table 6. Estimation Results After the Research Period Variables Coefficient Standard Error Value of t p-value Intercept (α) 0,82 0,13 6,31 <0,001 KUR Understanding Level (β₁) 0,18 0,06 3,00 0,003 Age of MSEs (β₂) 0,004 0,002 2,00 0,048 Having Financial Statements (β₃) 0,24 0,08 3,00 0,003 Marketing with Technology (β₄) 0,17 0,07 2,43 0,017 R² 0,69 Source: researcher estimation results ***significant at 1% **significant at 5% After the study period, the control group showed a very minimal change in the coefficient compared to the pre-study condition. The intercept (α) only increased from 0.80 to 0.82, a statistically insignificant change. The coefficients of the independent variables also experienced a statistically insignificant increase, indicating that without the mentoring intervention, the variables did not have a significant effect on ease of access to financing. In addition, the R² value of the control group regression model increased slightly from 0.52 to 0.59. This increase is very small and indicates that the regression model's ability to explain data variability remains consistent without any significant improvement in predictive ability. This indicates that without the mentoring intervention through FGDs, the regression model did not improve significantly in predicting the ease of access to financing for MSEs. This finding confirms the importance of mentoring interventions to bring about meaningful changes in access to finance. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 494 https://internationalpubls.com After the implementation of mentoring through Focus Group Discussion (FGD), an in-depth analysis was conducted on the impact of each independent variable on the ease of access to financing for Micro and Small Enterprises (MSEs) in Depok. This analysis compared the results between the treatment group that received FGD mentoring and the control group that did not receive the same intervention. 1. MSEs' level of understanding of KUR Treatment Group: After the FGD assistance, the regression coefficient for the variable MSEs' level of understanding of the People's Business Credit (KUR) increased significantly from 0.18 to 0.40 with a p value of 0.001. This shows that an increase in MSEs' understanding of KUR substantially increases the ease of access to financing. The FGD assistance succeeded in increasing MSEs' knowledge of the application procedures, requirements, and benefits of KUR, so that they are more prepared and confident in applying for financing. The significant increase in the treatment group confirms the effectiveness of FGDs in improving MSEs' understanding of KUR. A better understanding enables MSEs to meet credit requirements more effectively, in line with previous research findings that emphasize the importance of financial literacy in access to financing. (Tambunan, (2019) Control Group: In the control group, the change in the coefficient was only from 0.17 to 0.18 with a p value of 0.05, indicating no significant increase in KUR understanding without the mentoring intervention. In the control group, the increase in the regression coefficient for the variable KUR Understanding Level only occurred from 0.17 to 0.18 with a p value greater than 0.05. This very minimal and statistically insignificant increase indicates that without the mentoring intervention, MSEs' understanding of the People's Business Credit (KUR) did not change significantly. This finding is consistent with a report by the Financial Services Authority (2017), which states that without special education or training programs, the level of financial literacy and understanding of financial products among micro and small business actors tends to stagnate. Therefore, interventions such as mentoring and financial education are crucial to improve MSEs' understanding and access to available financing facilities. 2. Age of MSEs Treatment Group: The regression coefficient for the MSE age variable decreased slightly from 0.004 to 0.002 with a p value of 0.048. Although statistically significant, the effect is very small. This shows that the age of MSEs is not the main determining factor in the ease of accessing financing after the FGD assistance. Business age tends not to be a critical factor in accessing financing compared to other factors such as understanding of KUR and the quality of financial statements. Financial institutions prioritize the viability of the current business and its future prospects.(Wibowo and Paramita, 2020). Control Group: In the control group, the coefficient remained at 0.004 with a p value of 0.048, confirming that the age of MSEs did not change without the intervention. 3. Have Financial Report Treatment Group: After mentoring, the coefficient for the variable having financial statements increased significantly from 0.22 to 0.45 with a p value of 0.001. This increase shows that the ability of MSEs to prepare good Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 495 https://internationalpubls.com financial reports greatly affects the ease of access to financing. Transparent and accountable financial reports make it easier for financial institutions to assess creditworthiness. FGD assistance helps MSEs understand the importance of financial statements and improve their skills in preparing them. This is in line with the literature which states that financial statements are one of the main requirements in MSE credit applications. Control Group: In the control group, the coefficient only increased from 0.23 to 0.24 with a p value of 0.05, indicating no significant change without mentoring. In the control group, the regression coefficient for the variable Having Financial Statements only increased slightly from 0.23 to 0.24 with a p value greater than 0.05, indicating that the increase was not statistically significant. This indicates that in the absence of assistance, the ability of MSEs to prepare and utilize financial statements does not experience significant changes, and thus does not have a significant impact on ease of access to financing. This finding is consistent with the Financial Services Authority (2017) report, which states that without special intervention or education, the level of financial literacy and accounting practices among MSEs tends to be low and stagnant. Therefore, assistance in preparing financial statements is crucial to improve the quality of MSEs' financial information, which in turn can increase the trust of financial institutions and facilitate access to financing. 4. Marketing Using Technology Treatment Group: The regression coefficient for the marketing variable using technology increased significantly from 0.15 to 0.35 with a p value of 0.001. This shows that the use of technology in marketing significantly increases the ease of access to financing. The use of digital platforms increases the visibility of MSEs and attracts the attention of financial institutions. The significant increase in the treatment group indicates that the FGD mentoring is effective in encouraging MSEs to adopt technology in marketing. This is in line with the trend of digitalization of MSEs that can increase competitiveness and access to a wider market. (Wijaya & Kurniawan, 2020) Control Group: In the control group, the coefficient increased from 0.16 to 0.17 with a p value of 0.05, which is not statistically significant. In the control group, the regression coefficient for the Marketing Using Technology variable only increased slightly from 0.16 to 0.17 with a p value greater than 0.05, indicating that the increase was not statistically significant. This indicates that without any special assistance or intervention, MSEs did not experience any significant changes in the use of technology for marketing. As a result, the role of technology in facilitating easy access to financing remains minimal. The level of digital technology adoption among MSEs is still low due to limited digital knowledge and skills. Without structured assistance, MSEs are likely to face barriers in utilizing technology to improve competitiveness and access to financing sources. Therefore, interventions in the form of mentoring and training in the use of marketing technology are crucial to increase the capacity of MSEs in the digital era. The results of model 2 estimation using macro aggregate data in Depok City are as follows: poverty gap and growth in Gini coefficient. 𝑌𝑌1 = 2.95 - 1.67𝑋1 - 2.062𝑋2 - 0.06𝑋3 + 0.17𝑋4 (0.12) (0.000)*** (0.106)* (0.042)** (0.002)*** Analysis of the macro results reveals that several key variables have a significant impact on the poverty gap in Depok City. These variables include the number of MSEs, the amount of credit for MSEs, Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 496 https://internationalpubls.com inflation in Depok City, and the BI rate. Specifically, the number of MSEs, the amount of credit for MSEs, and inflation in Depok City are all found to have a negative effect on the poverty gap in Depok City. For the most robust results in estimating model equation 2, it should be estimated using the Y2 variable, which is the Gini coefficient of Depok City. 𝑌𝑌2 = 0.95 - 2.057𝑋1 - 3.215𝑋2 - 0.078𝑋3 + 0.20𝑋4 (0.034) (0.000)*** (0.06)* (0.012)** (0.007)*** Based on the results of robustness equation model 2 using the Y2 variable, which is the Gini coefficient of Depok City, it is evident that the variables significantly affecting the Gini coefficient of Depok City are the number of MSEs, the amount of credit for MSEs, inflation in Depok City, and the BI rate value. The number of MSEs, the amount of credit for MSEs, and inflation in Depok City have a negative impact on the poverty gap in Depok City. Number of MSEs The regression coefficient for the variable number of MSEs (X1) is -1.67. This negative coefficient indicates that an increase in the number of MSEs has a significant effect in reducing the poverty gap in Depok City. Specifically, every one percent increase in the number of MSEs will reduce the poverty gap by 1.67 units, assuming other variables are constant. This improvement in the poverty gap can be attributed to various factors, including enhanced local economic activities and increased access to education. For example, as small and medium enterprises (MSEs) flourish, they create job opportunities that empower residents financially, subsequently reducing reliance on social welfare programs. Additionally, the correlation between educational attainment and poverty alleviation becomes evident; higher literacy rates often lead to better employment prospects and income stability, which are crucial for sustainable development (Puspitasari, 2022). As such, fostering a supportive environment for entrepreneurship alongside educational initiatives could further accelerate this positive trend in Depok's socio-economic landscape. Moreover, community engagement and government support play vital roles in sustaining these advancements, ensuring that the benefits of growth are equitably distributed among all residents. This collaborative approach not only strengthens local economies but also builds resilience against economic fluctuations, ultimately contributing to a more robust and inclusive community. Furthermore, investing in infrastructure and access to technology can enhance these efforts, providing residents with the tools necessary to thrive in an increasingly digital economy.Additionally, promoting partnerships between local businesses and educational institutions can create a pipeline of talent that meets the demands of emerging industries, ensuring that the workforce is well-prepared for future challenges." (Lubis, 2020) Moreover, fostering a culture of innovation through grants and mentorship programs can empower entrepreneurs to develop new solutions that address local needs, further driving economic growth and community engagement (Jauhari & Perinsya, 2021). By prioritizing sustainability in these initiatives, communities can also ensure that their growth is environmentally responsible, paving the way for a healthier future.This holistic approach not only strengthens the local economy but also enhances the quality of life for all residents, creating a vibrant and resilient community that can adapt to changing circumstances.By integrating education, industry collaboration, and community involvement, we can cultivate a dynamic ecosystem that supports continuous learning and adaptation, ultimately leading to long-term prosperity. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 497 https://internationalpubls.com Credit score of MSEs in Depok City The regression coefficient for the MSE credit value variable (X2) is -1.67. This negative coefficient indicates that a 1% increase in the value of credit disbursed to MSEs contributes to a decrease in the poverty gap. This means that every one billion rupiah increase in the value of MSE credit will reduce the poverty gap by 1.67 units. As the increase in microcredit for small and medium enterprises (SMEs) in Depok contributes to a reduction in the poverty gap, it is essential to consider how access to financial resources can empower local entrepreneurs. This empowerment not only fosters economic growth but also enhances social mobility within communities that have historically faced barriers to entry in formal markets. Furthermore, the role of institutions like credit from syariah banking becomes crucial as they provide financing products tailored to the needs of market traders and SMEs, effectively combating exploitative lending practices (Setiawan et al., 2022). Facilitating better access to credit while ensuring compliance with ethics. This resilience is further enhanced by fostering partnerships between MSMEs and larger corporations, which can facilitate knowledge transfer and resource sharing, thereby amplifying the impact of local businesses on the broader economic landscape.al standards, these initiatives could potentially lead to sustainable development and a more equitable distribution of wealth across various strata of society. Moreover, the impact of targeted financial products extends beyond mere economic upliftment; it also plays a significant role in enhancing technical efficiency among micro enterprises. Research indicates that access to credit options such as Kredit Usaha Rakyat (KUR) can lead to improved operational efficiencies and profitability for small businesses, ultimately contributing to poverty alleviation (Purmiyati et al., 2019). Focusing on factors such as geographical location and business type, these financial programs can be tailored to address specific local needs, ensuring that support reaches those who are most vulnerable. As local entrepreneurs become more proficient in managing their resources, the ripple effect could transform entire communities, fostering an environment where innovation thrives and collective prosperity becomes attainable. As these financial initiatives gain traction, it is vital to assess their broader implications on income inequality within the region. Evidence suggests that increased lending to micro, small, and medium enterprises (MSMEs) not only bolsters individual business performance but also plays a pivotal role in reducing income disparity among community members (Pamungkas et al., 2016). This interconnectedness highlights the importance of designing financial products that are inclusive and accessible, particularly for marginalized groups who may lack traditional collateral or credit histories. By prioritizing such targeted support, policymakers can catalyze an environment where economic opportunities are equitably distributed, ultimately leading to sustainable progress across socioeconomic divides. Furthermore, as local entrepreneurs harness improved operational efficiencies through programs like KUR, they contribute to a more resilient economy capable of withstanding external shocks and fostering long-term growth. In addition to enhancing operational efficiencies, the integration of financial literacy programs is paramount for maximizing the benefits derived from credit access. By equipping entrepreneurs with essential skills in budgeting, investment planning, and risk management, these initiatives can further empower MSMEs to make informed decisions that stimulate sustainable growth. For instance, studies indicate that improved financial literacy directly correlates with better business performance and sustainability among MSMEs in regions like Depok, where many face challenges related to financial access and knowledge gaps (Finatariani et al., 2024). Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 498 https://internationalpubls.com This holistic approach not only strengthens individual enterprises but also fosters a culture of entrepreneurship that can lead to innovation and diversification within local economies. As such, combining targeted financial products with robust educational resources could serve as a catalyst for long-term economic resilience, ultimately transforming the landscape of small businesses into one characterized by stability and collective advancement.Moreover, partnerships between financial institutions and educational organizations can enhance the reach and effectiveness of these initiatives, ensuring that entrepreneurs are equipped with the necessary tools to navigate an increasingly complex market.These collaborations can also facilitate mentorship programs, where experienced entrepreneurs share insights and strategies, further empowering the next generation of business leaders. Depok city inflation The regression coefficient for the inflation variable (X3) is -0.06. In general, high inflation is associated with increased poverty. However, this small negative coefficient shows that inflation in Depok City has a very weak negative effect on the poverty gap. Inflation has an unidirectional effect on the poverty gap, indicating that higher inflation has little impact on increasing the poverty gap. This means that the higher the inflation in Depok City, the smaller the poverty gap. This situation is influenced by factors such as uneven price increases, negative impacts on purchasing power, and ineffective policies. This study is in line with research by (Fauzi, A., & Wicaksono, 2022c; Lestari, 2021; Prabowo, Y., & Hidayat, 2020a) which found that inflation contributes to an increase in the poverty gap, mainly due to the increase in the price of basic necessities that is not offset by an increase in income and the impact is more heavily felt by low-income groups. Inflation in Depok city has an unidirectional effect on the growth of the Gini coefficient, indicating that inflation contributes to an increase in inequality. This means that the higher the inflation in Depok city, the smaller the growth of the Gini coefficient, due to factors such as uneven price increases, the impact on fixed incomes, and ineffective policies. This study is in line with research by (Aji, L., & Santoso, 2021a; Fauzi, A., & Wicaksono, 2023; Hidayat, N., & Widyastuti, 2022). The findings suggest that high inflation can worsen the Gini coefficient due to its greater impact on low-income groups, especially if it is not matched by equitable income growth. BI Rate The regression coefficient for the BI Rate variable (X4) is +0.17. This positive coefficient indicates that an increase in the national benchmark interest rate has an effect on increasing the poverty gap. Every 1% increase in the BI Rate will increase the poverty gap by 0.17 units. BI Rate has a unidirectional effect on the poverty gap, indicating that an increase in the BI Rate is associated with an increase in the poverty gap. This condition is possible due to its impact on borrowing costs, purchasing power, and economic growth. This study is in line with research by (Fauzi, A., & Wicaksono, 2022b; Prabowo, Y., & Hidayat, 2020b; Setiawan, D., & Rahmawati, 2021) which states that an increase in the BI Rate worsens the poverty gap, especially for low-income groups who depend on loans because it can increase borrowing costs and reduce people's purchasing power. BI Rate has a unidirectional effect on the growth of the Gini coefficient, indicating that an increase in BI Rate contributes to an increase in income inequality. This condition is possible due to its impact on borrowing costs, access to capital, and investment patterns. The same research was conducted by (Fauzi, A., & Wicaksono, 2022a; Kurniawan, A., & Sari, 2023; Lestari, N., & Haryanto, 2021) which states that higher interest rates worsen inequality, especially for more vulnerable groups. The increase in BI Rate contributes to an increase in the Gini coefficient because it increases borrowing costs and reduces access to capital. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 499 https://internationalpubls.com Conclusion This study has provided valuable insights into the challenges faced by micro and small enterprises (MSEs) in accessing the Kredit Usaha Rakyat (KUR) program in Depok, Indonesia, and how targeted interventions can address these barriers. The findings reveal that access to financing remains a significant challenge for many MSEs, largely due to limited understanding of KUR procedures, inadequate financial reporting, and the slow adoption of technological tools for business operations. These barriers contribute to the widening of the poverty gap, as MSEs struggle to grow and access the capital needed to scale their operations. The experimental design employed in this research allowed for a clear comparison between the treatment group, which received targeted interventions through Focus Group Discussions (FGDs), and the control group, which did not receive any such interventions. The treatment group showed marked improvements in several key areas, including a better understanding of KUR procedures, improved financial literacy, and greater adoption of technology for marketing. These improvements were found to significantly enhance MSEs' ability to access KUR and secure financing, which is critical for business expansion and sustainability. Regression analysis further supports the conclusion that factors such as understanding of KUR procedures and financial reporting practices have a statistically significant impact on financial accessibility. In contrast, the business age, which was initially hypothesized to influence access to financing, was found to have a minimal effect. This suggests that the capacity to access financing is more closely tied to operational and managerial competencies than to the longevity of the business. These findings underscore the importance of capacity-building programs tailored to improving financial literacy and technological adoption among MSEs. The control group, in contrast, exhibited no significant changes in KUR access, highlighting the critical role that structured interventions play in facilitating financial inclusion. Without external support, MSEs are likely to continue facing challenges in navigating financial systems and accessing the capital needed for growth. This points to the necessity of continued institutional support for MSEs, particularly in the areas of financial education and technological integration. Furthermore, the results emphasize that structured interventions such as FGDs are not only beneficial in the short term but could also have long-lasting impacts on the financial stability and growth of MSEs. By improving access to financing, these interventions contribute to poverty alleviation and promote economic inclusion. The findings suggest that the effectiveness of such programs could be further enhanced by integrating digital tools and platforms into the support mechanisms for MSEs, making them more adaptable to the demands of the modern economy. In conclusion, this study advocates for the implementation of sustained training and support programs designed to improve MSEs' financial capabilities, specifically through the enhancement of their understanding of financing programs such as KUR and the adoption of technological innovations. Policy-makers, financial institutions, and development agencies should consider these findings when designing future programs aimed at strengthening the financial inclusion of MSEs. Through ongoing capacity building and support, MSEs can play a pivotal role in driving economic growth, reducing inequality, and alleviating poverty in Indonesia. Given these findings, it is essential for future research to examine the long-term impacts of financial literacy initiatives and technological support on the sustainability of MSEs. The dynamic economic environment, driven by rapid technological progress and shifting market conditions, demands that MSEs continually adapt and innovate to remain competitive. Consequently, policy strategies should extend beyond immediate financial inclusion and focus on equipping MSEs with the skills and Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 7s (2025) 500 https://internationalpubls.com knowledge necessary to succeed in an increasingly challenging market. This study adds to the growing literature on financial accessibility and poverty reduction, highlighting the pivotal role of structured interventions in enhancing the financial and operational capabilities of small enterprises. 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