Analysis of Culinary MSME Business Performance through Digital Entrepreneurship Academy (DEA) Training in South Kalimantan Sudirwo1.
Syahrial Shaddiq2 Sekolah Tinggi Ilmu Ekonomi Banjarmasin.
Indonesia Universitas Cahaya Bangsa.
Indonesia sudirwo@gmail.
Keywords Abstract DEA.
PLS.
COVID-19.
business performance.
This research focuses on examining the impact of the benefits provided by the Ministry of Communication and Informatics (Kemenkominf.
with data collected from Micro.
Small and Medium Enterprises (MSME.
in the South Kalimantan (Kalse.
region during the coronavirus disease 2019 (COVID-.
pandemic, especially MSMEs in the culinary industry.
The aim of this research is to ascertain how training, which is mediated by digital marketing skills and entrepreneurial motivation, influences business performance both directly and indirectly.
Quantitative method used in this research.
In order to collect data online, a survey from Google Form was given to respondents who were alumni of the 2021 DEA training participants in the South Kalimantan region as many as 47 people as a sample of a total population of 115 people.
At least Roscoe's 30% of the total population was used to determine the sample size.
SmartPartial Least Square (SmartPLS) 3.
0 with path analysis test, a statistical tool used in data processing.
The results of the descriptive analysis showed an increase in business turnover of 85.
11%, both before and after the respondents participated in DEA activities.
Based on the findings of the quantitative analysis, the exogenous variable DEA Training (X) has a positive and significant effect on the endogenous variable MSME Business Performance (Y), as well as the mediating variables Digital Marketing Capability (Z.
and Entrepreneurial Motivation (Z.
The indirect effect of all variables is beneficial but not statistically significant on MSME Business Performance, this indicates that there are additional factors other than the mediating variable that significantly affect business performance.
For example, respondents may have additional skills and methods of running a business.
Considering that there is no research on the DEA program for MSME actors, this research offers a new perspective to the Ministry of Communication and Informatics of the Republic of Indonesia Introduction After two years of the global outbreak of COVID-19.
Indonesia's economy is slowing The MSME sector has been negatively affected by the COVID-19 outbreak, causing actors to respond by reducing the production of goods and services, reducing the number of _____________________________________ DOI: https://doi.
org/10.
33258/birci.
Budapest International Research and Critics Institute-Journal (BIRCI-Journa.
Volume 6.
No 1.
February 2023.
Page: 334-353 e-ISSN: 2615-3076(Onlin.
, p-ISSN: 2615-1715(Prin.
bircu-journal.
com/index.
php/birci email: birci.
journal@gmail.
employees and working hours, and limiting the number of sales and marketing channels (Bahtiar, 2.
The Government of the Republic of Indonesia proposes to allocate a budget of 677 trillion rupiah to rebuild the economy which has been badly affected by the outbreak(Wikipedia, 2.
The use of digital technology worldwide is increasing, especially since the COVID- 19 pandemic in early 2020 (Yugo, 2.
Digital Entrepreneurship Academy or DEA for short, one of the government's initiatives through the Ministry of Communication and Informatics, aims to develop superior Human Resources (HR) to accelerate digital transformation in the field of entrepreneurship to strengthen the digital economy, with a target of training 60,000 people by 2022 (Ministry of Communication and Information, 2.
In addition, this program aims to encourage the growth of digital entrepreneurship in inclusive communities as well as new and advanced digital entrepreneurs.
When DEA was first introduced in 2020, its initial goal was to increase the capabilities of digital entrepreneurs .
and digitize MSMEs.
To help MSMEs with digital sales training.
DEA introduced the hashtag #BangkitDiMasaPandemi in 2021.
With the hashtag #PulihBersama.
DEA will train digital entrepreneurs to help MSMEs recover from the outbreak in 2022.
DEA's training program emphasizes hands-on experience and includes mini-class activities for businesses at beginner to intermediate levels.
The aim of this curriculum is to provide concise and thematic knowledge on topics such as business models, digital copywriting, digital marketing, product branding, and search engine optimizer (SEO).
(Ministry of Communication and Information, 2.
However, the researchers observed the challenges faced by MSME actors after the digital marketing training they attended, namely how big the impact it would be on their business performance during the COVID-19 pandemic by applying training materials in their daily operations.
Therefore, it is very important to conduct this research to understand how training affects business performance, digital marketing skills, and entrepreneurial In addition, although both are only partial mediators, entrepreneurial drive and digital marketing skills both influence company performance.
Therefore, the purpose of this research is to find out whether DEA training, digital marketing skills, and entrepreneurial motivation have an impact on business performance capabilities, both separately and in combination.
II Review of Literature 1 Business Performance Business performance is described by(Voss & Voss, 2.
as a measurement level at the business level, which includes sales turnover, customer base, revenue, and sales growth.
An indication of how well a corporation is performing in achieving its goals is organizational performance, which is often known as business performance or company performance.
Strong company performance shows the effectiveness and success of company operations.
Performance measure by(Chung et al.
, 2.
include profit rate, sales growth, product and service quality, customer retention rate, new product success rate, and return on investment.
Sales growth, market share, and sales to current clients are just a few examples of the many variables that shape the structure of marketing performance(Chang et al.
, 2.
Increasing profits from time to time, business competitiveness .
, product marketing from the number of consumers and marketing areas carried out, as well as the ability of businesses to maintain their existence are some of the business performance indicators that will be used in this study (Nursiah et al.
, 2.
2 Training By improving their abilities, knowledge and behavior, personnel are formed and prepared through training.
In other words, training will shape employee behavior to suit company goals(Kasmere, 2.
According to Kasmir, the purpose of the training itself is to increase knowledge, hone skills, and develop skills.
It also aims to increase responsibility, compliance, and selfconfidence while deepening the sense of belonging to the organization.
The variable dimensions of this training such as training materials, trainers or instructors, participants, training methodologies, and training facilities can be seen(Septiana.
Therefore, training is an effort to improve one's talents so that they have better information, skills, new ways of thinking, and attitudes that will enable them to overcome difficulties in the future.
3 Digital Marketing Capability For the ability to market using digital means to add value to products and services, adapt to changing market conditions and interests, compete by seizing market opportunities, and fending off threats from rivals.
Marketing capability is defined as an integrated process that applies a company's collective knowledge, skills and resources to markets and related needs(Kajalo & Lindblom, 2.
The marketing mix process and the creation and implementation of strategies are two important marketing capabilities, according to Vorhies & Morgan(Odhiambo et al.
, 2.
The retail business, especially in this modern era, must be able to create appropriate and appropriate advertising programs for target consumers(Sander, 2.
By enhancing marketing skills through digital technology, businesses can achieve this.
(Rahadis, 2.
came to the conclusion that the interaction between the three componentsAihardware, software, and usersAicannot be ignored in the creation of information technology, so that behavioral aspects need to be considered.
According to Lucas & Spitler .
in(Susilo & Adityawarman, 2.
to use information technology effectively and efficiently, consequently helping to increase performance, which can be influenced by the proper use of technology by members of social media organizations is one of the applications of information technology.
According to research findings(Sudirwo et al.
, 2.
Instagram provides positive benefits for the growth of product marketing, which leads to increased followers and sales.
In addition, it is easy to use and has a large user base, making it a useful, affordable, trustworthy and widespread medium of publicity.
Aspects of IT expertise and the relationship between corporate strategy and IT are used in this study(Tippins & Sohi, 2.
4 Entrepreneurial Motivation Strong entrepreneurial motivation is one of the keys to success as an entrepreneur according to (Rusdiana, 2.
Motivation to realize professional performance as an entrepreneur so that he becomes a person who is beneficial to himself, his family and society.
Someone will try harder to achieve if he feels that what he is doing has meaning for his life.
There are at least six levels of entrepreneurial motivation, each with a unique set of indicators of success, including the following:
Motivated materially, to earn income or wealth for a living.
Rational-intellectual motivation, recognizing market opportunities and potentials, and initiating products or services in response to them.
The emotional ecosystem motivates, creates added value and preserves environmental d.
Emotional-social motivation to relate or meet the needs of fellow human beings.
Emotional-interpersonal .
sychological-persona.
motivation to realize one's identity and/or potential in the form of products or services that can be marketed.
Spiritual motivation, realizing and spreading transcendental values, interprets it as a way of worship.
The researcher included a number of previous studies related to the variables used in this analysis (Table .
Table 1.
Previous Research No.
Name.
Year (Octavia, (Megracia, (Thesman & Ardianti, (Nursiah et al.
(Hendrawan & Siren, 2.
Title Research result Increasing Business Performance of Jambi Batik SMEs through Entrepreneurship Training If Jambi batik SMEs attend entrepreneurship training more often, the business performance will be better, according to the F Count regression test which is lower than the p-value of 0.
05 at a significant number.
The R square value of 43.
indicates that variations in the entrepreneurship training variable are able to explain the company's performance factors, while other variables explain the rest.
Characteristics and With a value of 0.
518, the Motivation of Entrepreneurs influence of entrepreneurial on Business Performance motivation on business success is considered acceptable.
Relationship between The Relationship between the Entrepreneurial Motivation Performance of SMEs in the on Micro and Small food and beverage sector in Business Performance in the Surabaya and Sidoarjo with Food and Beverage Sector Entrepreneurial Motivation.
in Surabaya and Sidoarjo Because the significance value is greater than 0.
05 and equal 670, greater than 0.
there is no correlation between entrepreneurial motivation and business performance.
Entrepreneurial Behavior in MSEs show entrepreneurial Tempe Micro Small behavior, including the Enterprises (UMK) in ambition to start a business.
Bogor.
West Java but large-scale production shows more entrepreneurial The Influence of The entrepreneurial knowledge Independent Attitude, variable has a large positive Motivation, effect on students' interest in No.
Name.
Year (Sander, 2.
(Syafe'i, 2.
Title Research result Entrepreneurship Knowledge on Interest in Entrepreneurship (Case Study of SWCU FEB Students Concentrating on Entrepreneurshi.
The Influence of Market Orientation on Company Performance with Organizational Commitment and Marketing Capability as Mediation Variables (Empirical Study of Retail Sector Companies in DKI Jakart.
The Influence of Training and Work Discipline on the Performance of Volunteers at the Ogan Komering Ulu Regency Office of the Regional Disaster Management Agency Independent attitude and motivation variables have no significant effect on students' interest in All research hypotheses, including H5 that marketing skills affect 9.
634381 company business performance, are Partially the variables of training (X.
and work discipline (X.
have an effect on performance.
the remaining 7% is influenced or explained by other factors not taken into account in this research model, such as leadership, work motivation, and work environment.
The Conceptual Framework of this study is shown in Figure 1.
Digital Marketing Skills (Z.
DEA Training (X) Business Performance (Y) Entrepreneuri al Motivation (Z.
Figure 1.
Research Conceptual Framework Sugiyono .
defines a hypothesis as a temporary assumption made during the conceptualization of a research problem.
Because it is still temporary, it needs to be confirmed using empirical evidence that has been collected.
The following hypotheses were proposed by the researchers based on the research model mentioned above:
H1: DEA training has a significant effect on business performance.
H2: DEA training has a significant effect on digital marketing skills.
H3: DEA training has a significant effect on entrepreneurial motivation.
H4: Digital marketing capabilities have a significant effect on business performance.
H5: Entrepreneurial motivation has a significant effect on business performance.
H6: DEA Trainingmediated digital marketing capabilities have a significant effect on business performance.
H7: DEA Trainingmediated entrepreneurial motivation has a significant effect on business i.
Research Method In South Kalimantan in 2021, this type of causal research will be carried out by distributing questionnaires to respondents who are alumni of DEA participants, especially MSMEs in the culinary industry.
Data from DEA participants from the Center for Human Resources Development and Research (BPSDMP) Ministry of Communication and Informatics Banjarmasin was used as secondary data in data collection using a purposive sampling method.
According to Roscoe in (Sugiyono, 2.
, the research sample is at least 30% of the total population studied in this study, or 30% x 115 = 35.
The population consists of DEA 2021 participants which can number up to 115 and come from all regions of South Kalimantan.
Samples from the population with the criteria for DEA participants who already own or run a business in the culinary field are taken from a population of 47 respondents.
SmartPLS 3.
0, a statistical tool, will be used during data processing.
Measurement model analysis .
uter mode.
and structural model analysis .
nner mode.
will be carried out in this study .
nner mode.
Convergent Validity.
Discriminant Validity, and Composite Reliability are used in testing the outer model.
While the Inner Model uses .
R-Square, .
F-Square, .
Mediation Effects, which include .
Direct Effects, .
Indirect Effects, .
Total Effects (Juliandi, 2.
1 Variable Operational Definitions The variables of Business Performance.
DEA Training.
Digital Marketing Capability and Entrepreneurial Motivation are presented in Table 2 along with their operational definitions, dimensions and indicators:
Table 2.
Variable Operational Definition Operational Variable Dimensions Indicator Business The series of Profit / Profit Generate higher Performance (Y) work leads to the 2.
Competitiveness implementation of 3.
Marketing Business (Nursiah et al.
business activities 4.
Business in accordance Resilience.
with authority and .
Based on the and in terms of number of Variable DEA Training (X) Operational development and Dimensions Efforts to enhance a person's talents so that they have skills, new ways of thinking, and attitudes that will enable them to overcome future Material/Material Method Trainer/Instructor Participant Means Digital An integrated Marketing Skills process designed (Z.
to bring together Information Business strategy (Septiana, 2.
Indicator customers and marketing channels used, product The company's ability to continue The right material for a particular job I believe the training materials offered are easy to understand The techniques offered are in accordance with the material offered I can understand the course material because of the training techniques The instructor conveys the knowledge during the training The instructor delivers instructions according to the course material I went to training because I saw the need for it I believe the training I receive will be useful in doing my I think program training is very The training facilities are very I am well versed in the basics of Variable (Sander, 2.
Operational resources and market needs so that companies can add value to their products or services and give them the flexibility to adapt to changing market conditions and opportunities to reduce threats to be Dimensions Indicator and information I have a certain set of information technology skills.
I have knowledge about innovation in I am equipped with the necessary knowledge to build and manage client interactions based on I may use technology based systems to collect and analyze market data about our I have set up a process to get client data from internet I have been successful in developing close bonds with I am able to establish close relationships with online media users.
(Tippins & Sohi, (Kajalo & Lindblom, 2.
(Tippins & Sohi, 2.
Variable Entrepreneurial Motivation (Z.
(Hendrawan & Sirine, 2017.
Rusdiana, 2.
Operational Motivation that comes from within a person and motivates them to take action to achieve a goal.
Dimensions Indicator Motivational One's drive to Material become rich through Intellectual drive and makes sense 2.
A person's drive Emotional-social comes from his ability to see available business The driving force behind a person's capacity to add value to a product.
Four data collection methods were used: .
interviews, which involve direct conversations with informants to collect information.
questionnaire, which is an instrument or technique for collecting data or information consisting of a list of questions given to research participants in the form of questions packaged in sheets of paper.
online interviews, which involve contacting participants by phone.
electronic forms, by distributing questionnaires or electronic questionnaires using one of the Google Forms 2 Data Analysis Technique A multivariate statistical methodology that compares a number of dependent .
variables with a number of independent .
To find out this mediating effect, the following research steps were carried out: .
analysis of the measurement model .
uter mode.
structural model analysis/structural model analysis .
nner mode.
Analysis and analysis of measurement models.
Utilizing the data analysis method with SmartPLS, three criteria of Convergent Validity.
Discriminant Validity, and Composite Reliability are used to evaluate the outer model.
Convergent Validity Based on the correlation between the suggested item scores, the convergent validity of the measurement model using the reflexive indicator was calculated.
When a person's reflexive measure exceeds 0.
70 and is connected to the concept being measured, it is considered high.
The most anticipated/best value for outer loading is a value > 0.
7, however a value > 0.
4 to 0.
4 requires removing the indication from the variable(Hair et al.
, 2.
In this investigation, a loading factor of 0.
60 will be applied.
Discriminant Validity To determine whether an indicator in a concept will have a loading factor when combined with other constructs, a Discriminant Validity test is performed.
Latent variables are considered to predict indicators more accurately than other latent variables if the correlation between each indicator .
anifest variabl.
and the latent variable is higher than the correlation with other latent variables.
It is considered to have good discriminant validity and the predicted value of AVE is more than 0.
5 (> 0.
if the square root value of the average variance extracted (AVE) for each construct is higher than the correlation value between the construct and the other constructs in the model.
Composite Reliability The measure of how much a measuring device can be trusted is called composite High reliability data is data that has a composite reliability of > 0.
Both internal consistency and Cronbach's Alpha can be used to assess the combined reliability of a block of indicators that assess a construct.
Structural or inner model analysis R-Square.
F-Square models, and three tests for mediating effectsAi.
direct effects, .
indirect effects, and .
total effectsAiwere used to analyze the structural model.
R-Square The magnitude of the variation in the value of the influence variable .
that can be explained by the influence variable .
is measured using the R-Square This is useful for determining how accurate the model is(Juliandi, 2.
The criteria for the R-Square are:
C If the value of R2 .
= 0.
75 and above, then the model is substantial .
C If the value of R2 .
= 0.
50 and above, then the model is moderate C If the value of R2 .
= 0.
25 and above, then the model is weak .
F Square The f-squared measurement, also known as the effect size f2, is a metric used to evaluate the relative effect of an exogenous .
variable on an endogenous .
The effect of modifying R2 is another name for the f2 .
To assess and decide whether the omitted variable has a significant impact on the endogenous construct, changes in the value of R2 when certain exogenous variables are excluded from the model can be used.
F-Square criteria according to Cohen in(Juliandi, 2.
are as follows :
C If the value of f2 = 0.
02 and above, it means that the exogenous variable has a small effect on the endogenous variable.
C If the value of f2 = 0.
15 and above, it means that the effect is moderate from the exogenous variables on the endogenous variables.
C If the value of f2 = 0.
35 and above, it means that the exogenous variable has a large effect on the endogen.
Mediation Effects Analysis.
The direct effect, also known as the path coefficient in PLS SEM analysis, is the value of the direct effect term.
Simultaneously with hypothesis testing, a path coefficient calculation between constructs was performed to determine the significance and strength of the association.
Path coefficient values vary from -1 to 1.
The closer the path coefficient is to 1, the more significant the relationship between the two constructs is.
relationship less than -1 indicates a negative relationship(Hair et al.
, 2.
The hypothesis that an influencing variable .
will have a direct impact on the affected variable can be tested using direct .
influence analysis.
The following criteria will be used to assess the direct effect theory:
Path Coefficients A If the path coefficient is positive, then the effect of a variable on other variables is unidirectional, meaning that when the value of one variable increases or decreases, so does the value of the other variable.
A If the path coefficient value of a variable is negative, the effect on other variables is for example, if the value of one variable increases or increases, the value of another variable will decrease or decrease.
Probability/Significance Value (P-Valu.
A If the P-Value <0.
05, then it is significant.
A If the P-Value is > 0.
05, then it is not significant.
Indirect effect analysis attempts to examine the idea that an influencing variable .
has an indirect influence on the affected variable .
, and that this indirect effect is mediated by/mediated by the intervening variable .
ediation variabl.
The following factors are used to determine the indirect effect:
C If the P-Values <0.
05, it is significant, meaning that the mediating variables Z1 (Digital Marketing Abilit.
and Z2 (Entrepreneurial Motivatio.
mediate the effect of exogenous variable X (DEA Trainin.
on endogenous variable Y (MSME Business Performanc.
other words, the effect is indirect.
C If the P-Values > 0.
05, then it is not significant, meaning that the mediating variables Z1 (Digital Marketing Abilit.
and Z2 (Entrepreneurial Motivatio.
mediate the effect of exogenous variable X (DEA Trainin.
on endogenous variable Y (MSME Business Performanc.
In other words, the effect is direct.
3 Total Effects The total effect .
otal impac.
is the total of the direct effect .
irect effec.
and indirect effect .
ndirect effec.
IV.
Discussion 1 Descriptive Analysis Information collected from respondents is described in the following section.
To fully understand the research findings, descriptive data detailing the circumstances or situation of the respondents must be considered.
Table 3.
Characteristics of Respondents Pendidikan Terakhir SLTP
SLTA
Sarjana Jumlah 0,00% 6,38% 51,06% 42,55% Asal Kabupaten Kota Banjarmasin Kota Banjarbaru Kab.
Banjar Kab.
Barito Kuala Kab.
Balangan Kab.
Hulu Sungai Selatan Kab.
Hulu Sungai Tengah Kab.
Hulu Sungai Utara Kab.
Kotabaru Kab.
Tabalong Kab.
Tanah Bumbu Kab.
Tanah Laut Kab.
Tanah Laut Jumlah 14,89% 27,66% 14,89% 0,00% 0,00% 0,00% 12,77% 2,13% 0,00% 27,66% 0,00% 0,00% 0,00% Mulai Usaha < 1 tahun 1-3 tahun 4-5 tahun > 5 tahun Jumlah 12,77% 40,43% 25,53% 21,28% 100,00% Omset Usaha Sebelum <1 juta 1-10 juta 10-50 juta 50-100 juta >100 juta Jumlah Jumlah 12,77% 31,91% 40,43% 6,38% 8,51% 0,00% 29,79% 44,68% 12,77% 12,77% Jumlah Jumlah 19,15% 2,13% 27,66% 29,79% 21,28% 100,00% 85,11% 14,89% 0,00% 100,00% Omset Usaha Sesudah <1 juta 1-10 juta 10-50 juta 50-100 juta >100 juta Peningkatan Omset Tetap <10% 10-50% 51-100% >100% Peningkatan Omset Naik Tetap Turun It is clear from Table 3 above that women make up the majority of respondents who are active in the DEA culinary profession in 2021.
Most of the respondents are aged between 31 and 35 years and have a high school diploma before continuing their education.
Respondents are spread geographically throughout South Kalimantan, with the majority living in Banjarbaru and Tabalong.
Most of the respondents' culinary businesses have been operating for 1-3 years, while some others have been established for 4-5 years.
According to the business turnover data of respondents, 40.
43% of respondents with a turnover of between $10 and $50 million and 8.
51% of respondents with a turnover of more than $100 million contributed to the total turnover prior to participating in DEA activities.
After attending the DEA training, respondents with a turnover of between 10 and 50 million grew to 44.
68%, while those with a turnover of more than 100 million increased to 12.
After attending the DEA training, the overall turnover of respondents increased by 85.
while it decreased by 14.
2 Results of Data Analysis The results of research data analysis processing using the SmartPLS program are listed Figure 2.
Results of the PLS Algorithm Table 4.
Convergent Validity Results Pernyataan Nilai R Hasil Pelatihan DEA Indikator X1.
0,939
(X.
X1.
0,917
X1.
0,930
X1.
0,947
X1.
0,953
X1.
0,944
X1.
0,939
X1.
0,958
X1.
0,952
X1.
0,954
Kemampuan Pemasaran Digital Z1.
0,855
(Z.
Z1.
0,857
Z1.
0,917
Z1.
0,934
Z1.
0,939
Z1.
0,890
Z1.
0,943
Z1.
0,896
Motivasi Berwirausaha Z2.
0,945
(Z.
Z2.
0,972
Z2.
0,975
Kinerja Bisnis UMKM
0,905
(Y)
0,854
0,953
0,946
Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid The results of data processing Table 4 above shows that each item in the questionnaire statement is genuine because it has a loading factor value greater than 0.
Therefore, a questionnaire can be used.
Discriminant Validity Table 5.
Discriminant Validity Results Konstruk Average Variance Extracted (AVE) Kemampuan Pemasaran Digital Kinerja Bisnis UMKM Motivasi Berwirausaha Pelatihan DEA Table 5 above shows that all variables have an AVE value for all variables greater than or equal to 0.
So, each variable has strong discriminant validity, so to speak.
Composite Reliability Table 6.
Composite Reliability Results Cronbach's Alpha Composite Reliability Kemampuan Pemasaran Digital Kinerja Bisnis UMKM Motivasi Berwirausaha Pelatihan DEA From the data in table 6 above it can be seen that the composite reliability value for all research variables is greater than 0.
These findings indicate that each variable has achieved composite reliability, supporting the statement that each variable has a high level of 3 Analysis of the Inner Model or Structural Model R-Square Table 7.
R Square Results R Square R Square Adjusted Kemampuan Pemasaran Digital Kinerja Bisnis UMKM Motivasi Berwirausaha The following conclusions can be drawn from testing the R-Square value in table 4.
R-Square Adjustedfor line I, is 0.
This shows that the variable X (DEA Trainin.
can explain Z1 (Digital Marketing Abilit.
up to a level of 79.
2%, which fulfills the requirements of a fairly large .
R-Square Adjustedfor line II = 0.
This model is still categorized as moderate because the variables X (DEA Trainin.
and Z1 (Digital Marketing Skill.
are able to explain Y (MSME Business Performanc.
to a level of 68.
R Square Adjustedfor path II = 0.
831 This means that the model is still considered quite good because the ability of the variables X (DEA Trainin.
Z1 (Digital Marketing Abilit.
, and Z2 (Entrepreneurial Motivatio.
F Square Table 8.
F Square Results Kemampuan Pemasaran Digital Kinerja Bisnis Motivasi
Pelatihan DEA
UMKM
Berwirausaha
Kemampuan Pemasaran Digital 0,011 Kinerja Bisnis UMKM
Motivasi Berwirausaha
Pelatihan DEA
0,006
3,906
0,152
5,033
Table 8 shows the results of the f-square values as follows:
Variable X (DEA Trainin.
to Z1 (Digital Marketing Abilit.
has a value of f2 = 3.
so the effect is large.
Variable X (DEA Trainin.
to Z2 (MSME Business Performanc.
has a value of f2 = 033, so the effect is large.
Variable X (DEA Trainin.
to Y (MSME Business Performanc.
has a value of f2 = 152, so the effect is moderate from exogenous variables to endogenous variables.
Variable Z1 (Digital Marketing Abilit.
to Y (MSME Business Performanc.
has a value of f2 = 0.
011, so the effect is small.
Variable Z1 (Entrepreneurial Motivatio.
versus Y (MSME Business Performanc.
has a value of f2 = 0.
006, so the effect is small.
4 Mediation Effects Figure 3.
Bootstrapping Results Following are the results of the direct effects analysis in this study:
Table 9.
Direct Effects Results Original Sample (O) P Values Kemampuan Pemasaran Digital -> Kinerja Bisnis UMKM
0,128
0,513
Motivasi Berwirausaha -> Kinerja Bisnis UMKM
0,104
0,576
Pelatihan DEA -> Kemampuan Pemasaran Digital 0,892 0,000 Pelatihan DEA -> Kinerja Bisnis UMKM
0,626
0,000
Pelatihan DEA -> Motivasi Berwirausaha
0,913
0,000
The path coefficients reveal that all path coefficient values are positive .
een in the original sampl.
based on the direct effect study findings in Table 4.
7 above, leading to the following conclusions:
The direct effect of X (DEA Trainin.
on Z1 (Digital Marketing Abilit.
is path coefficient = 0.
892 and P value = 0.
000, so this influence is positive and significant.
The direct effect of X (DEA Trainin.
on Z2 (Entrepreneurial Motivatio.
is path coefficient = 0.
913 and P value = 0.
000, so this effect is positive and significant.
The direct effect of X (DEA Trainin.
on Y (MSME Business Performanc.
is the path coefficient = 0.
353 and the P value = 0.
000, so this effect is positive and significant.
The direct effect of Z1 (Digital Marketing Abilit.
on Y (MSME Business Performanc.
is a path coefficient = 0.
128 and a P value = 0.
513, so this effect is positive but not The direct effect of Z2 (Entrepreneurial Motivatio.
on Y (MSME Business Performanc.
is path coefficient = 0.
104 and P value = 0.
576, so this effect is positive but not significant.
Table 10.
Indirect Effects Results Original Sample (O) P Values Pelatihan DEA -> Kemampuan Pemasaran Digital -> Kinerja Bisnis UMKM
0,114
0,518
Pelatihan DEA -> Motivasi Berwirausaha -> Kinerja Bisnis UMKM
0,095
0,580
So, it can be concluded that the indirect effect value in Table 4.
8 has an indirect effect on DEA Training.
Digital Marketing Capability, and MSME Business Performance of 0.
, with P-Values 0.
518 > 0.
ot significan.
, and Digital Marketing Capability mediate the effect of DEA Training on MSME Business Performance.
Entrepreneurial Motivation then mediates the effect of DEA Training on MSME Business Performance, seen from the indirect effect of DEA Training.
Entrepreneurial Motivation, and MSME Business Performance which is equal to 0.
and P-Values 0.
580 > 0.
ot significan.
5 Total Effects Table 11.
Results of Total Effects Original Sample (O) P Values Kemampuan Pemasaran Digital -> Kinerja Bisnis UMKM
0,128
0,513
Motivasi Berwirausaha -> Kinerja Bisnis UMKM
0,104
0,576
Pelatihan DEA -> Kemampuan Pemasaran Digital 0,892 0,000 Pelatihan DEA -> Kinerja Bisnis UMKM
0,835
0,000
Pelatihan DEA -> Motivasi Berwirausaha
0,913
0,000
The overall effects in Table 4.
9 lead to the conclusion that all variables have positive However, none of the mediating factors is significant in relation to endogenous factors (MSME Business Performanc.
While all endogenous factors (MSME Business Performanc.
and mediating variables are positively and significantly influenced by exogenous variables (DEA Trainin.
(Digital Marketing Capability and Entrepreneurial Motivatio.
6 Discussion .
Effect of DEA Training on Business Performance It is accepted that DEA training has a beneficial and sizeable impact on company The results of this study are different or inconsistent with previous studies(Octavia, 2.
While the research results(Syafe'i, 2.
comparable or in accordance with this study.
Effect of DEA Training on Digital Marketing Ability Acceptable digital marketing skills are positively and significantly influenced by DEA .
Effect of DEA Training on Entrepreneurial Motivation Entrepreneurial motivation is positively and significantly influenced by DEA training.
The findings of this study support the findings of previous or similar studies(Thesman & Ardianti, 2.
Effect of Digital Marketing Capabilities on Business Performance Digital Marketing Ability has a positive but not significant effect on Business Performance, so the hypothesis is not accepted.
The results of this study are different or inconsistent with previous studies(Sander, 2.
The Effect of Entrepreneurial Motivation on Business Performance The hypothesis is rejected because entrepreneurial motivation has a small but beneficial effect on business performance.
The results of this study are different or inconsistent with previous studies(Megracia, 2.
The Effect of DEA Training Mediated by Digital Marketing Capabilities on Performance The hypothesis was rejected because DEA Training with Mediated Digital Marketing Capability Has a Positive but Not Significant Effect on Business Performance.
The Effect of DEA Training Mediated Entrepreneurial Motivation on Business Performance The hypothesis is rejected because DEA Training mediated entrepreneurial motivation has a slightly beneficial impact on business performance.
Conclusion The following can be concluded based on the findings of the study and debate on the performance analysis of culinary MSME companies through the Digital Entrepreneurship Academy (DEA) Training in South Kalimantan:
There was an increase in business turnover before and after participating in DEA activities, namely 85.
11%, according to the results of a descriptive analysis of the culinary business performance of MSMEs from participants in the Digital Marketing Training Program from the 2021 Digital Entrepreneurship Academy (DEA) organized by the Ministry of Information and Communication through BPSDMP Banjarmasin Kominfo.
The endogenous variable MSME Business Performance (Y), as well as the mediating variables Digital Marketing Capability (Z.
and Entrepreneurial Motivation, are all positively and significantly influenced by all exogenous DEA Training variables (X) (Z.
While all of the indirect variables' effects on MSME Business Performance were good, they were not statistically significant, indicating that other factors, such as the skills and business methods of other respondents, may have a greater impact than the mediating This research is expected to encourage quality improvement, improve digital marketing capabilities, and provide deeper entrepreneurial motivation for DEA program organizers, namely the Ministry of Communication and Informatics through the Banjarmasin Center for Human Resource Development and Communication and Informatics Research (BPSDMP Kominf.
Future researchers posing the same problem should consider additional variables outside our model and additional samples from fields other than cuisine.
References