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THE EFFECT OF CAPITAL AND LICENSING ON THE PRODUCTIVITY OF
UMKM IN MAJALENGKA REGENCY
Muhammad Khoirul Umam1.
Abdurokhim2
International Cyber Polytechnic Article Information IMWI STUDENT RESEARCH
JOURNAL
Volume 5.
Number 2 August 2024 Pages: 97-110 Wiyata Indonesia Institute of Management .
Jl.
Gudang No.
7-9,
City of Sukabumi .
West Java.
Keywords:
Capital .
Licensing and Productivity of MSMEs Corresponding Author:
Abstract This research aims to determine the effect of Capital and Licensing on the Productivity of MSMEs in Majalengka Regency.
The study was conducted on MSMEs in the Majalengka Regency with a sample size of 100 respondents.
Using the Simple Random Sampling technique, the respondents were selected to obtain a representative sample from 211,749 MSMEs in the Majalengka Regency.
The data analysis method used validity tests, reliability tests, classical assumptions, regression analysis, and T-tests and F-tests processed through IBM SPSS The research results indicate that partially there is a significant positive effect of the Capital and Licensing variables on the Productivity of MSMEs.
At the same time, simultaneously there is a significant positive effect of 77.
2%, with other factors not examined in this study To that end.
MSMEs must strive to improve access to capital by preparing attractive business proposals, and they also need to ensure that all necessary permits have been properly arranged.
Furthermore, support from the government is crucial in reducing the bureaucratic burdens faced by MSMEs, simplifying the requirements for KUR, and lowering interest rates muhammad_khoirul@polteksci.
, abdurokhim@polteksci.
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INTRODUCTION
Poverty is inability from corner view economic, material and physical to meet need life , which is measured with ability purchasing power .
BPS .
Growth rate Poor people in Majalengka decrease but No significant, with a total of 147,121 people in 2022, 138,740 in 2023, and 134,580 in 2024.
Regardless from decline poor population , level growth in Majalengka still below the national average , with population 11.
21% of the total 1.
3 million Occupation Majalengka.
Table 1: Total Poor Population in the District Majalengka ( Thousand Soul.
Source : BPS Majalengka Regency Micro.
Small and Medium Enterprises (MSME.
form absorption workforce and development economy local, contributing and potential big to speed up National Economic Growth, the two most important cluster components in influencing MSMEs are Capital and licensing, which helps MSMEs invest and grow while access Complicated and bureaucratic capitalization and licensing become obstacles for MSMEs in business growth.
MSMEs face challenge like lack of knowledge law ,problem compatibility system and shortcomings knowledge business in accessing (Judijanto, 2.
54% of MSMEs stated that they face problem Problems This preventing MSMEs from expanding their markets and disrupting operational business (Gusriyana , 2.
Table 2: Number of MSMEs in the Regency 2021
Year
Amount
156,841
166,545
176,850
187,792
211,749
Source: opendata.
Table 2 shows growth significant UMKM in the Regency The Great Plains from 2016 to 2021.
MSMEs in the Regency The Great Plains can absorb workforce of 16,030 people, ( Research and Developmen.
Regional Development Planning Agency Majalengka , 2.
This show importance capital and licensing in increasing development of UMKM.
Limitations access to sources financing become UMKM problems to expand business , improve production , and adopt New
AuThe licensing process business according to Asep MSME experts in the Regency The Great Plains Still considered complicated and full bureaucracy , so that WINTER JOURNAL
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makes it difficult for MSMEs to comply rules and get permission the effort required .
The situation This the more critical Because Lots MSME actors who do not understand rules and requirements licensing .
As a result , many from they operate without valid permission or delay the licensing process .
This ultimately limit ability them to get support finance and access to formal marketsAy Figure 1: Taking a photo with Mr.
Asep.
District MSME Expert The Great Plains According to the Indonesian Dictionary, capital is principal money.
or funds used as the basis for doing business, spending money, and various activity others.
Capital includes all forms wealth that can utilized in the production process to increase According to Prawirosentono in Loho .
, capital is goods or money combined with factor production like land and labor to create new goods and services.
Business capital, according to Nugraha in Windasari .
, is the money used as the main thing for trading, spending money, etc.
property object such as money, goods, and so on that can utilized to produce something that can add wealth.
In the context of this, capital can interpreted as the amount of money used to run operation Here is Indicators for Company Capital: a.
) Structure capital: own capital and loan capital.
) Utilization of additional capital, c.
) Barriers in accessing external capital , and d.
) Conditions business after add capital.
Then Business capital indicators , according to Bambang Riyanto in Nurfiana .
, consist of from : a.
) Easy capital obtained b.
) Effective capital c.
) Large capital Condition Licensing should based on the principle convenience for MSMEs.
This is show that the more Lots the requirements set , the more low interest of MSMEs to take care of Licensing.
On the other hand, if condition more simple and the amount more little, possibility perpetrator business will more interested in taking care of Licensing.
Sutedi in Nurhayati .
A study conducted by Bank Indonesia regarding Procedure MSME licensing shows that from eight determining indicator quality bureaucracy and service licensing , part large UMKM provides evaluation positive to four indicators : .
hospitality officer licensing .
clarity procedure service .
ability officers in explaining .
availability equipment .
On the other hand , there are four factor additional still considered not enough satisfied by some large UMKM, namely : .
the existence of WINTER JOURNAL
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levy No official which varies .
lack of facilities to accommodate complaints .
the existence of duplication in requirements and procedures .
Nurhayati, .
Relevance between consequence licensing and interest in making licensing lies in power the attraction offered by the consequences The attraction This will become factor booster for MSMEs to take care of licensing.
According to Sutedi in Nurhayati .
, rights and obligations between applicants and agencies must be regulated in regulations and deregulation licensing.
In the context of this , some things to note is :
Written with clear.
Balanced between second parties.
Must be fulfilled by all From various definition said, can concluded that Power pull and clarity consequence existing permits will influence SMEs interest in managing licensing.
Productivity is ability to produce more same quality as the same effort .
Humans have the most important role in improving productivity , because tool production , technology and capital are the results of human work Human .
Goddess in Gsriyana .
Production is component from productivity , together quality and Improvement productivity and efficiency is source main growth to achieve development sustainable , principles in management productivity is effective.
The elements are: Productivity are: a.
) Efficiency, b.
) Effectiveness and c.
) Quality.
Kamriah in Setiawan .
, work productivity can measured with compare the results achieved by Entrepreneurs with role them and their contributions towards MSMEs in units time certain.
Production considered as element important in demonstrating and improving quality of MSMEs.
Therefore efforts to improve productivity considered as step going to welfare and improvement quality of MSMEs.
Research by Putra .
shows that capitalization own influence high significance and can increase production output as well as amount portion food is sold, so contribute to the improvement income.
Gabriel F.
Loho .
in his research explain that the influence of capital on income business show impact positive and significant for income UMKM entrepreneurs in the District East Langowan.
Furthermore.
Gusriyana .
found that capital also has an effect significant to productivity MSME business in the field craft hands in the District The thorns.
Nurhayati .
shows that licensing influential to development of MSMEs.
Although its influence Still small, thing This show that licensing own role in supporting growth of MSMEs.
Rizki .
M .
stated that service licensing through Jakevo own influence significant to satisfaction MSME entrepreneurs.
Furthermore.
Loso Judijanto .
explained that licensing influential significant positive in a way statistics to sustainability of MSMEs.
Mr.
Hasyim.
Coordinator of Village Patriots of the Regency Majalengka, in his interview state that " Capital and licensing become a major obstacle for growth of MSMEs in Majalengka.
" Based on statement said, research This will to study more about how much big influence second factor the to performance of MSMEs, especially from aspect productivity.
This research is very crucial to understand various factors that influence MSMEs in Majalengka.
This is aims to improve planning and implementation, as well
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as allow development of strategies that can increase efficiency, creating more Lots job opportunities, and provide significant contribution to growth economy local.
This research focus on analysis deep regarding two factors main influencing factors growth of MSMEs in the Regency Majalengka, namely capital and licensing, research This offer novelty.
Different from study previously more often discuss challenges faced by MSMEs, studies This in a way special identify problems that arise when SMEs try access capital and licensing, such as procedure complicated bureaucracy and lack of understanding UMKM actors about existing regulations.
addition, research this is also unique because it uses the latest data about amount poor population and the growth of MSMEs in Majalengka, so that give a better picture comprehensive about context economy local.
Previous research has not fully explore influence direct between Productivity of MSMEs in the Regency The Great Plains with aspect Capital and Licensing.
This research aims to provide more analysis deep about condition real in the Regency Majalengka.
Currently, there is no integrated and focused policies for MSMEs in the regions in overcoming problem Capital and Licensing at the level local.
This research done with the goal is to find out How capital and licensing influence MSME productivity in the Regency Majalengka, to understand influence between capital and licensing to Productivity of MSMEs in Kumbung Village.
Regency Majalengka, literature that has discussed can used to compose framework conceptual.
Framework conceptual This will be very useful in analysis empirical and testing hypothesis in part furthermore from study This.
Figure 2: Conceptual Framework Information:
H1 = Capital (X.
has an effect positive in a way Partial to MSME Productivity (Y) H 2 = Licensing (X.
has an effect positive in a way Partial to MSME Productivity (Y) H3 = Capital (X.
and Licensing (X.
have an influence positive in a way Simultan to MSME Productivity (Y) WINTER JOURNAL VOL.
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METHOD
Quantitative research methods are the basis of this study and use the Simple Random Sampling method in taking representative samples from 211,749 MSMEs in Majalengka Regency .
To maintain a balance between accuracy and resource efficiency in data collection, we set the Margin of Error (MoE) at 10% .
Given that direct access to all MSMEs in the population is limited, because some MSMEs are not officially registered or are difficult to reach, the use of a Margin of Error (MoE) of 10% allows researchers to still get a representative sample of the population.
Research involving a very large population such as 211,749 MSMEs, the use of a smaller Margin of Error (MoE) , such as 5% or 3%, will require a much larger sample size to obtain representative Collecting data from a very large sample requires more time, cost, and effort.
The desired population sample size with a certain level of confidence and margin of error (MoE) can be calculated using the Slovin formula.
Sugiyono .
Figure 3: Slovin's Formula With N = 211,749 .
otal MSME.
and e = 10% = 0.
10, we now plug these values into the Slovin formula:
The required sample size is approximately 100 MSMEs, with a margin of error of 10% and a total population of MSMEs of 211,749, rounded to the nearest whole number.
Several data collection methods in this study include interviews, questionnaires, observations, or a combination of all these methods.
Data analysis using IBM SPSS Statistics, with assumption n is amount sample .
and alpha = 5% .
Significance Test Validity can done with compare R value calculation with R table .
Reliability test done with Cronbach Alpha method .
Data
analysis using Assumption Test Classical , which includes Normality and WINTER JOURNAL
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Multicollinearity Tests as condition analysis .
This study uses Analysis Multiple Linear Regression to determine whether there is influence between Capital (X.
and Licensing (X.
against Productivity of MSMEs (Y).
Hypothesis Test done with the T-test ( Partial ) model.
F-test ( Simultaneous ) and Coefficient Determination .
RESULT AND DISCUSSION
The Product Moment Correlation Method developed by Karl Pearson is used to test Validity study this .
If the result of the R count test more big from the R table , then the data is considered valid.
Testing This done with compare R value calculation with R table for degrees freedom ( df ) = n Ae 2, i.
e df = 100 Ae 2 = 98, so generate R table of 0.
The following is the result of the validity test .
Table 3: Validity Test Results Variables Statement
R- Count R-Table STATUS
X1_1
VALID
X1_2
VALID
X1_3
VALID
(X.
X1_4
VALID
CAPITAL
X1_5
VALID
X1_6
VALID
X1_7
VALID
X1_8
VALID
X2_1
VALID
X2_2
VALID
X2_3
VALID
X2_4
VALID
X2_5
VALID
(X.
X2_6
VALID
PERMITS
X2_7
VALID
X2_8
VALID
X2_9
VALID
X2_10
VALID
X2_11
VALID
VALID
VALID
VALID
(Y)
VALID
PRODUCTIVITY OF
VALID
UMKM
VALID
VALID
VALID
Source : (Primary data from processed questionnaires , 2.
Reliability Test serves to assess questionnaire as indicator variable .
questionnaire considered reliable or reliable If answer individual to statement still consistent or stable along time .
The Cronbach alpha statistical test is used to measure WINTER JOURNAL
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level reliability a variable .
Variable the considered reliable If Cronbach 's alpha value more big from 0.
The following table presenting the results of reliability testing .
Table 4Reliability Test Results Cronbach's Alpha (> 0.
Status Capital (X.
RELIABLE Licensing (X.
RELIABLE Productivity (Y) RELIABLE Source : (Primary data from processed questionnaires , 2.
Variable Normality is aspect crucial in analysis statistics , research data needs to meet Assumptions Normality before done Analysis Regression ( Arianto , 2.
Data is considered normally distributed if p-value > 0.
05, if the histogram graph shows balanced slope , both on the sides left and also right , and shape the curve almost resemble the perfect bell , and if unidirectional data points following the diagonal line then the data is normally distributed .
The following is the result of the normality test :
Table 5: Tests of Normality One-Sample Kolmogorov-Smirnov Test Normal Parameters a,b Mean Std.
Deviation Most Extreme Differences Absolute Positive Negative Test Statistics Asymp .
Sig.
- taile.
Test distribution is Normal.
Source : (Primary data from processed questionnaires , 2.
Based on Table 5, the results of the Normality Test Kolmogorov Smirnov showed mark of 0.
036, which is more big from 0.
05, so that can concluded that the data is normally distributed .
Figure 4: Probability Plot of Normality Source : (Primary data from processed questionnaires, 2.
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Figure 3 shows data points in the same direction following the diagonal line, which also indicates that the data normally distributed.
Figure 5: Histogram of Normality Test Results Source: (Primary data from processed questionnaires, 2.
Based on Figure 4, all existing data show normal distribution.
This is seen from curve Productivity of MSMEs in the Regency Majalengka which has balanced slope between side right and left, and its shape resembles bell.
Multicollinearity Test can seen through mark tolerance and factors inflation variables (VIF).
The purpose of the multicollinearity test is to determine whether there is correlation between variable free .
in the regression model, where it should be No There is correlation between variable independent.
Data presentation for multicollinearity test can seen in the table following.
Table 6Multicollinearity Test Results Collinearity Statistics Model Tolerance VIF (Constan.
CAPITAL
PERMITS
Dependent Variable: UMKM PRODUCTIVITY Based on Table 6, all variables free show mark tolerance of 0.
401 which is more big of 0.
10 and a VIF value of 2.
496 which is greater small of 10.
This is show that in the regression model in the study This No happen multicollinearity.
Hypothesis study This to study connection between Variables Capital and Licensing with Productivity of MSMEs, which is tested through analysis regression The result of analysis regression multiple done by using the SPSS 26 program you can seen in the table following:
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Table 7Analysis Test Results Regression Unstandardized Standardized Coefficients Coefficients Model Std.
Error Beta (Constan.
-1,943 1,877 CAPITAL
PERMITS
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Sig.
<,001
<,001
Based on Table 7, the equation Multiple Linear Regression obtained is : Y = 1.
459X1 0.
475X2.
Equality mentioned show that mark Variables The productivity of MSMEs is -1.
943 if variable Capital and Licensing remains.
In other words, if Capital and Licensing increase by 1 point, then The productivity of MSMEs will also increases by 1 point, and vice versa.
T-test is conducted to test hypothesis study about the influence of each variable free in a way partial to variable bound.
T-statistics is values used to assess level significance in testing hypothesis with method count T-statistics value through bootstrapping procedure.
In testing hypothesis, can it is said significant If T-statistics value is more big from 1.
96, while If T-statistics value is less from 1.
96, then considered No significant.
Taking decision done with refer to value significance contained in the table Coefficient.
Generall , the basis regression result testing done with level trust by 95% or level significance of 5% ( = 0.
The following is criteria from the T Statistic Test ( Ghozali , 2.
: If the value significance of the t-test > 0.
05, then HCA is accepted and Ha is rejected.
This means that there is no There is influence between variable independent and variable dependent.
On the other hand , if mark t-test significance is less 05, then HCA is rejected and Ha is accepted, which shows existence influence between variable independent and variable dependent.
Table 7 shows that Capital Sig value .
001<0.
and T count value .
= T
, as well as Licensing Sig ( 0.
001<0.
and T count value .
< .
This is indicates that HCA is rejected and Ha is accepted, which shows existence influence between variable Capital and Licensing to Productivity of MSMEs in Majalengka at the level 5% significance.
The F test is conducted to test significance coefficient regression of all variables free in a way simultaneously so that can evaluate influence Capital and Licensing to Productivity of MSMEs in Majalengka in a way simultaneously.
Here is the result of the F Test.
Table 8: Results of simultaneous F test Model Sum of Squares df Mean Square Regression Residual 14,060 Total Dependent Variable: UMKM PRODUCTIVITY Predictors: (Constan.
LICENSING.
CAPITAL
164,332
Sig.
<,001 b
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Level of significance in research This set at 5% or 0.
From table 8, it can be seen that The Sig value of the F Test result is 0.
001, which indicates that Sig value more small from probability 0.
001 < 0.
Furthermore, based on F table searched with the formula F( k.
n -k ) = F.
= F.
in column 2 row 98, it is known that F table value is 3.
With Thus, the results of the F test show that sig value 0.
001 < 0.
and the calculated F value .
> T table .
, then H0 is rejected and it is concluded that there is influence significant between Capital and Licensing to MSME Productivity.
Coefficient determination serves to measure how much big influence Variables Free, like Capital and Licensing, regarding Productivity of MSMEs.
Table 9 presents the results of the determination test the Table 9: Coefficients Determination Model R Square Adjusted R Square Predictors: (Constan.
LICENSING.
CAPITAL Dependent Variable: UMKM PRODUCTIVITY Std.
Error Estimate 3,750 Table 9 shows The R Square or R2 value is 0.
2%), which means that variable MSME productivity can explained by 77.
2% by variation variable Capital and Licensing .
Meanwhile , other factors that are not studied in research This contribute amounting to 22.
8% of the total.
Discussion Instrument study have all valid question items.
The coefficient value correlation , or r count , which is far more big from The r value of the table for each item shows matter This means that each question item succeed measure the construct in question .
Research tools are also considered reliable If every variable own Cronbach's Alpha value is above This indicates that tool measurements used No only consistent , but also can reliable.
Data has normal distribution based on the results of the normality test .
This is a condition important to do analysis regression then , no there is multicollinearity between variable independent ( capital and licensing ), because second variable the No own significant correlation each other then interpretation of regression results No will Analysis results regression show that variable capital and licensing own significant influence to productivity of MSMEs.
In other words, if variable capital and licensing increases , then MSME productivity will also increased .
The R-squared value 2% indicates that 77.
2% of the variation in MSME productivity can be explained by variations in the variables capital and licensing .
The remaining 22.
8% is influenced by other factors that are not included in the research This .
CONCLUSION AND RECOMMENDATION
Based on data analysis , can concluded that capital and licensing own significant influence to productivity of MSMEs.
To increase productivity .
MSMEs require adequate capital as well as completeness the necessary permits .
They must make efforts increase WINTER JOURNAL
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access capitalization with prepare an attractive business proposal and SMEs also need to ensure that all necessary permits are in place has taken care of completeness with good .
In addition, support from government is very important to reduce burden bureaucracy faced by MSMEs, making it easier KUR requirements , and reduce ethnic group flower Limitations of this research only research influence Capital and Licensing to Productivity of MSMEs.
However , there are Lots other factors that can also influence productivity , such as technology , quality source Power humans and the environment then There is possibility that sample study No fully represent population of MSMEs in general Overall , this study uses a simple linear regression model , but Possible there are more models complex that can give more explanation Good about connection between variable .
Suggestions for research then you can consider including variable like condition environment business , quality source Power humans , and technology .
Using a more complex regression model complex , such as non -linear regression models or regression models involving variable moderation or mediation to analyze connection .
REFERENCES