ISSN 2528-2433 .
ISSN 2599-283X .
Volume 8.
Number 2 Desember 2023, pp.
THE EFFECT OF INTERNSHIP AND ENTREPRENEURSHIP
TRAINING ON START-UP PERFORMANCE WITH
ENTREPRENEURIAL MOTIVATION AS AN
INTERVENING VARIABLE
Intan Widia Puro*.
Kussudyarsana.
Moechammad Nasir.
Anton Agus Setyawan Faculty of Economics and Business.
Muhammadiyah University of Surakarta
Article Info
ABSTRACT
Article History:
This research aims to analyze the influence of internships and entrepreneurship training on start-up performance, both directly and through entrepreneurial motivation.
This research used a quantitative approach with a sample of the first batch of UMS Independent Entrepreneurial Students in 2022, involving 869 Sample selection criteria included full participation in the program and having an active business.
The results of the analysis show that internships have a positive and significant impact on start-up performance and entrepreneurial motivation.
While entrepreneurship training does not have a significant direct impact on start-up performance, it does influence entrepreneurial motivation significantly.
Entrepreneurial motivation also has a significant positive impact on start-up performance.
Interestingly, both internships and entrepreneurship training provide a significant positive impact on start-up performance when mediated by entrepreneurial motivation.
Internships and entrepreneurship training have an important role in influencing start-up performance, especially when linked to entrepreneurial This emphasizes the importance of experience-based learning and formal training in supporting entrepreneurial spirit and performance among students in Indonesia.
Received 12 Sep, 2023 Accepted 13 Nov, 2023 Keywords:
Internship.
Entrepreneurship Start-up performance.
Entrepreneurial Motivation.
Skill evelopment This is an open access article under the CC BY 4.
0 license Corresponding Author Intan Widia Puro Email: intanwidia26@gmail.
INTRODUCTION
Entrepreneurship development has become a major focus of the Indonesian government in the last decade.
One of the prominent phenomena in entrepreneurship is the success of local start-ups in achieving the decacorn title, such as Gojek.
According to Peter F.
Drucker's definition, entrepreneurship is the process of creating something new and different that produces value by identifying business opportunities, taking risks, and Journal homepage http://mebis.
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managing human, financial and goods resources effectively.
Creativity and innovation, although often considered similar, have different meanings.
Creativity refers to the creation of new ideas, while innovation relates to the implementation of these ideas (Hastuti et al.
, 2.
Entrepreneurship in Indonesia itself is stated in the Decree of the Minister of Cooperatives and Small Entrepreneur Development Number 961/KEP/M /XI/1995 as a person's spirit, attitude and ability in handling business which aims to create the latest products or technology for better service, or gain greater profits (Khamimah, 2.
To overcome the problem of unemployment, it is necessary to foster an entrepreneurial spirit as a means of creating an independent attitude and will to improve the quality of life without depending on other people (Darlin Rizki, 2.
Alma .
revealed that the more advanced a country is, the more educated and unemployed people are, so the importance of the world of entrepreneurship is increasingly felt.
Development will be more successful if it is supported by entrepreneurs who can create jobs because the government is limited in its capabilities.
Therefore, instilling an interest in entrepreneurship is an important step in cultivating an entrepreneurial spirit.
Although the BPP HIPMI survey shows that most student respondents .
%) tend to want to become employees, only 4% are interested in becoming entrepreneurs.
Even after graduating from bachelor's degrees, they prepare more for tests administered by employers, both government and private agencies.
The millennial generation has an important role in nation building today.
The creative and innovative way of thinking of the millennial generation can bring change and become pioneers, not just following existing trends.
However, becoming a young entrepreneur is not easy.
Apart from issues of capital, technology, markets and creativity, a strong entrepreneurial mentality, attitude and characteristics must also be deeply embedded in order to become a strong Therefore, an approach needs to be taken to motivate students to become young entrepreneurs (Farida et al.
, 2.
Currently the government is launching the Independent Campus program to encourage young people's entrepreneurial creativity.
Independent Campus is not just a method or tool, but rather a concept of independence and contemporary style.
The concept of independence has the understanding that each campus must have independent and collaborative capabilities to produce a generation that is able to be independent with the skills they have.
Progress and sophistication on campus will only function well if it is able to provide benefits to society at large (Sintiawati et al.
, 2.
Internship activities are generally a means for universities to help students get used to the work environment and society.
The internship program is beneficial for the parties concerned, both from intern students who are given the opportunity to learn, and from employees whose workload is lightened due to the assistance provided by the internship students (Suyanto et al.
, 2019.
Rizki et al.
, 2.
There are training programs to improve student abilities and creativity.
It is hoped that entrepreneurship training programs carried out by the government and universities can motivate students to be interested in entrepreneurship.
Instilling an entrepreneurial spirit requires enthusiasm or encouragement, coaching, entrepreneurship training, and providing facilities as motivation (Robbins, 2.
Training is a means to change perceptions, attitudes, and improve skills, as well as increase the ability to assess and understand performance.
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Corporate Entrepreneurship can be defined as entrepreneurial action in creating new businesses, products or services within an organization with the aim of increasing income through sustainable growth.
This concept is important in maintaining inclusive economic, social and environmental prosperity, as well as ensuring an improved quality of life for current and future generations (Ramdani, 2.
According to Jose et al.
, .
individuals who are motivated to enter the world of entrepreneurship are often categorized as those whose motivation is based on need or opportunity.
This concept is called pushpull or opportunity-needs differentiation by Stephan et al.
, .
and is a long-standing conceptualization of entrepreneurial motivation.
Individuals' motivation to become entrepreneurs can influence their aspirations and ultimately influence company performance and their subjective well-being (Jose 2.
The relationship between attitudes and behavior mutually influences each other, and motivation can trigger latent intentions into real action.
Despite this, research on how these motivations influence entrepreneurs' behavior is still very limited, but some research is currently being conducted in this area (Edelman et al.
, 2.
Work design according to Carsrud .
research has not been applied to how entrepreneurs design their businesses, although they are motivated to create the type of company, they want to work Research on start-up performance in the scope of start-ups founded by students has not been carried out much by previous researchers, like research conducted by (Kolokas et , 2.
with the results of hypothesis testing in the form of a positive and significant influence on start-up performance with venture capital.
However, other research conducted by Makarevich in 2018 gave different research results.
The results of their research state that venture capital and start-up performance have a negative relationship.
Makarevich .
also suggested further research into the effects of motivation on company performance to obtain more comprehensive results.
From these descriptions, it is necessary to conduct research related to start-up performance which is influenced by internship and Entrepreneurship Training with entrepreneurial motivation as an intervening variable.
The hypotheses in this research are as follows:
Internship has a positive and significant effect on Start-up Performance Entrepreneurship Training has a positive and significant effect on Start-up Performance Internship has a positive and significant effect on Entrepreneurial Motivation Entrepreneurship Training has a positive and significant effect on Entrepreneurial Motivation Entrepreneurial motivation has a positive and significant effect on Start-up Performance Internship and Entrepreneurship Training have a positive and significant effect on Start-up Performance which is mediated by Entrepreneurial Motivation.
LITERATURE REVIEW
Based on literature searches, in-depth internships in leading companies have been proven to play a crucial role in preparing aspiring entrepreneurs with a strong practical understanding of day-to-day business operations.
Additionally, entrepreneurship training provides the knowledge and skills needed to manage and develop their business.
However, what is of concern in this research is how entrepreneurial motivation as an Journal homepage http://mebis.
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interacting variable can mediate the positive influence of internship and entrepreneurship training on start-up performance.
Research by Purnawaningsih and Moebari .
explains that entrepreneurship training can give birth to new, independent entrepreneurs in both the goods and services sectors.
Other research reveals that SECURE components in the form of desire, confidence, marketability, scalability, and viability show statistically significant effects on financial and non-financial start-up performance (Arshi et al.
, 2.
To improve organizational performance.
Agustina & Nelloh .
suggest that companies collaborate with universities to attract high-quality internship students to achieve optimal organizational To achieve more optimal company performance, companies adopt Business Intelligence to operate their organizations.
Caseiro & Coelho .
states that there are positive effects that have a direct impact on network learning, innovation and These findings provide clues that companies need to pay attention to business intelligence capacity in start-up companies, considering its impact on company The desire for entrepreneurship is often found among students or students at universities.
They are encouraged to develop themselves in various development activities either through programs organized by universities or the government.
Angki Adi Tama .
found that the factors of self-success in entrepreneurship, tolerance for risk, and the desire to experience free work had a positive and significant effect on students' motivation to become entrepreneurs.
Other research states that creativity and entrepreneurship training have a positive and significant effect on interest in entrepreneurship among students, while the religiosity factor has a positive but not significant effect (Laksono & Soleh.
Apart from increasing entrepreneurial motivation, the training carried out can also increase work commitment (Sri et al.
, 2.
This literature study reveals that internships in leading companies and entrepreneurship training play a crucial role in preparing prospective entrepreneurs with the strong practical knowledge and skills needed to manage a start-up business.
However, what is more interesting is the important role of entrepreneurial motivation as a mediating factor in connecting internships and training with start-up performance.
This confirms that an individual's passion and determination play a central role in their success as entrepreneurs.
Additionally, elements such as desire, confidence, marketability, scalability, and viability have also been shown to have a significant impact on start-up performance, underscoring the importance of a comprehensive understanding of these factors in sustainable business On the other hand, collaboration between companies and universities in recruiting quality interns has great potential to improve organizational performance.
Additionally, the use of Business Intelligence was also found to have a direct positive effect on network learning, innovation, and performance, demonstrating the importance of technology and data analysis in startup operations.
Overall, this literature study provides important insights for businesspeople, educators, and aspiring entrepreneurs about the factors that influence start-up performance and the steps that can be taken to improve it.
RESEARCH METHODS
The type of research used in the research uses quantitative methods.
Quantitative methods are a type of research whose specifications are systematic, planned and clearly structured from the start until the creation of the research design.
According to Sugiyono .
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quantitative research methods can be interpreted as research methods that are based on samples of positivism philosophy, used to research certain populations or samples, collect data using research instruments, analyze quantitative or statistical data, with the aim of testing predetermined hypotheses.
The population in this study was the first batch of UMS Independent Entrepreneurial Students.
The first batch of the UMS Independent Entrepreneurial Student Program will be implemented in 2022, attended by 869 participants from various universities.
The sampling technique used was purposive sampling, through Hair calculations the minimum sample size required was 180 Data collection in this research used a questionnaire or closed questionnaire.
A closed questionnaire itself means a request for respondents to make a choice between a series of alternatives that have been given by the researcher (Sekaran & Bougie, 2.
The questionnaire was created using a Likert scale format with a score of 1 for Strongly Disagree (STS) answers and a score of 5 for Strongly Agree answers.
The dependent variable in this research is Start-Up Performance (Y).
Then the independent variables consist of Internship (X.
Entrepreneurship Training (X.
, and the Mediation variable in the form of Enterpreneurial Motivation.
This research uses Structural Equation Model (SEM) analysis with Partial Least Square (PLS) with the help of SMARTPLS 3.
0 software.
PLS (Partial Least Squar.
is a powerful analysis method because it does not assume that the data must be measured on a certain scale (Ghozali, 2.
SEM essentially offers the ability to perform path analysis with latent variables.
The number of tests carried out is.
Outer model analysis .
easurement model evaluatio.
which consists of validity tests and reliability tests.
Inner model analysis .
tructural model evaluatio.
which consists of goodness of fit test.
Coefficient od Determinant (R.
Path Coefficient (Direct Effec.
and Specific Indirect Effects.
RESULTS AND DISCUSSION
This research is quantitative research where the data produced is in the form of numbers and then analyzed using SmartPLS 3.
0 software.
The aim of this research is to analyze the role of Internship and Entrepreneurship Training on Start Up Performance which is mediated by the Entrepreneurial Motivation variable.
The population used was MSMEs in Soloraya as many as 120 respondents using a questionnaire distributed via Google Form using a linkage scale of 1 Ae 5.
This research consists of 2 independent variables, namely Internship and Entrepreneurship Training, 1 mediating variable, namely Entrepreneurial Motivation, and 1 dependent variable, namely start up performance.
Respondent Characteristics Respondent characteristics are the variety of backgrounds that the respondents themselves In this research, the characteristics of respondents who own MSMEs include type of business, address and social media used.
The results obtained are:
Characteristics of Respondents Based on Business Type Based on the data obtained from respondents, the types of businesses that were respondents in this study are described in table 1.
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Table 1.
Characteristics Based on Business Type
No Type
Total
Precentage 1 Culinary 45,00% 2 Fashion
28,00%
3 Craft
16,00%
4 Cosmetics 11,00% Total Based on table 1, the characteristics of respondents according to the type of business they own are the most 58.
3% in the form of culinary, then 16.
7% in the form of fashion, 16.
crafts, 7% cosmetics, and the least are department stores, barbershops, and services, each of which is 0.
Characteristics of Respondents Based on Address Based on the data obtained from respondents, the business addresses of the respondents in this study are described in table 2.
Table 2.
Characteristics by Address
No Address
Total
Precentage Klaten
12,00%
Wonogiri 8,00% Surakarta
Sukoharjo
14,00%
Boyolali 7,00% Karanganyar
12,00%
Total Based on the data in table 2, the characteristics of respondents according to address show 15% have addresses in Klaten, 35.
83% in Wonogiri.
15% in Surakarta, 11.
67% in Sukoharjo, 5.
83% in Boyolali, 5% in Karangayar, and 2.
5% in Sragen.
Characteristics of Respondents Based on Social Media Used Based on data obtained from respondents, the social media used by MSME owners who were respondents in this research are described in table 3.
Table 3.
Characteristics Based on Social Media Used NoNo Social Media Total
Precentage 1 WhatsApp
26,00%
2 Instagram
27,00%
3 Facebook
4 Tiktok
32,00%
6 Lainnya 1,00% From table 3, the characteristics of respondents based on the social media used show that respondents use Instagram the most at 84.
16% followed by Whatsapp at 66.
Facebook at 35%.
Tiktok at 5.
83%, websites at 5.
83%, and e-commerce at 4.
PLS Program Scheme In this study, hypothesis testing uses Partial Least Square (PLS) data analysis techniques with the SmartPLS 3.
0 program.
The following is the model scheme of the PLS program Journal homepage http://mebis.
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Figure 1.
Outer Model Outer model testing is used to determine the specification of the relationship between latent variables and indicators, this test includes validity, reliability and multicollinearity.
The inner model is used to test the effect between one latent variable and another latent Testing the inner model can be done with three analyses, namely measuring the value of R2 (R-squar.
Godness of Fit (Go.
Hypothesis Test (Direct Effect and Indirect Effec.
and path coefficient.
Figure 2.
Inner Model Test Instruments The test instrument used in this study is a validity and reliability test using MSMEs in Soloraya, which is as many as 120 respondents, to be analyzed for validity and reliability and the results of the analysis are used as material in obtaining data for further analysis.
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the effect of Internship and Entrepreneurial Motivation creativity on Start-Up Performance mediated by Entrepreneurial Motivation was analyzed using the SmartPLS 0 analysis tool.
Outer Model Analysis The stages in SmartPLS analysis evaluate the outer model using 5 criteria, namely testing validity, variable reliability and Multicollinearity by looking at Cronbach's Alpha.
Composite Reliability.
Average Variance Extranced (AVE) and VIF on each variable (Ghozali et al.
, 2015.
The test results are as follows:
Convergent Validity To test convergent validity, an outer loading or loading factor value is used.
An indicator is declared to meet convergent validity in the good category if outer loadings > 0.
(Ghozali et al.
, 2015.
Here are the outer loading values of each indicator on the research Table 4.
Outer Loadings Outer Variabel Indicator Information Loadings X1.
0,897
Valid X1.
0,902
Valid Internship (X.
X1.
0,893
Valid X1.
0,902
Valid X2.
0,908
Valid X2.
0,899
Valid Entrepreneurship Training (X.
X2.
0,899
Valid X2.
0,904
Valid X2.
0,882
Valid
0,905
Valid
0,901
Valid
Start Up Performance (Y) 0,902 Valid
0,893
Valid
0,899
Valid
0,905
Valid
0,893
Valid
Entrepreneurial Motivation (Z) 0,890 Valid
0,911
Valid The results of processing using SmartPLS can be seen in Table 4 above the outer loadings value of all indicators above 0.
7 so that all indicators are declared valid.
Convergent validity can also be known through the Average Variance Extracted (AVE) method for each indicator to have a criterion of > 0.
5 to be said to be valid ((Ghozali et al.
, 2.
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Table 5.
Average Variance Extracted Average Variance Extracted (AVE) Internship (X.
0,808 Entrepreneurship Training (X.
0,807 Start Up Performance (Y) 0,809 Entrepreneurial Motivation (Z) 0,810 Description Valid Valid Valid Valid Based on table 4.
5 above, the AVE value of the Internship variable > 0.
5 with a value of 808, the Entrepreneurship Training variable > 0.
5 with a value of 0.
807, for the value of the Entrepreneurial Motivation variable > 0.
5 with a value of 0.
810, and for the Start Up Performance variable > 0.
5 with a value of 0.
This shows that all variables have good discriminatory validity.
Discriminant Validity Discriminant Validity is a test to ensure that each concept of each latent variable is different from other variables.
Discriminant Validity can be determined by assessing cross loading, for each indicator has a criterion of > 0.
7 to be said to be valid (Fornell and Larcker 1.
Table 6.
Cross Loading Indicator Internship Entrepreneurshi Start-Up Entrepreneurial (X.
p Training (X.
Performance Motivation (Z) (Y) X1.
X1.
X1.
X1.
X2.
X2.
X2.
X2.
X2.
Y1.
Y1.
Y1.
Y1.
Y1.
Z1.
Z1.
Z1.
Z1.
Source: Primary data processed, 2023 From the results of cross loading estimates in table 6 shows that the correlation value of the construct with the indicator is greater than the correlation value with other constructs.
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It can be concluded that all constructs already have discriminant validity which indicators in the block are better than indicators in other blocks.
Composite Reliability Test Composite Reliability is a section used to test the reliability of variable indicators.
The variable can be said to meet composite reliability if the composite reliability value of each variable is > 0.
70 (Ghozali et al.
, 2015.
The following is the Composite Reliability value of each variable:
Tabel 7.
Composite Reliability Composite Reliability Internship (X.
0,944 Entrepreneurship Training (X.
0,954 Start Up Performance (Y) 0,941 Entrepreneurial Motivation (Z) 0,945 Description Reliable Reliable Reliable Reliable Based on table 7 above, it can be seen that the value of Composite Reliability and the Internship variable has a value greater than 0.
7 which is 0.
944, the Entrepreneurship Training variable > 0.
7 with a value of 0.
954, for the Entrepreneurial Motivation variable has a > value of 0.
7 which is 0.
945 and for the Start Up Performance variable has a value of > 0.
7 which is 0.
941 , this shows that each variable has a Composite Reliability > 70, indicating that all four variables are reliable.
CronbachAos Alpha The Composite Reliability test above can be strengthened by using Cronbach's Alpha A variable can be said to be reliable if it has Cronbach's Alpha > 0.
70 (Ghozali et , 2015.
Here are Cronbach's Alpha values of each variable.
Table 8.
CronbachAos Alpha Cronbach's Alpha Internship (X.
0,921 Entrepreneurship Training (X.
0,940 Start Up Performance (Y) 0,941 Entrepreneurial Motivation (Z) 0,922 Description Reliable Reliable Reliable Reliable Based on table 4.
8 above, it can be seen that Cronbach's Alpha value of the Internship variable has a value greater than 0.
7 which is 0.
921, the value of the Entrepreneurship Training variable > 0.
7 with a value of 0.
940, for the Entrepreneurial Motivation variable has a > value of 0.
7 which is 0.
922, for the Start Up Performance variable it also has a value of > 0.
7 which is 0.
This shows that all variables have Cronbach's Alpha > 70, which means that all variables are considered reliable.
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Entrepreneurial Motivation_Z Entrepreneurship Training_X2 Internship _X1 Start-Up Performance_Y Cronbach's Alpha
0,922
0,940
0,921
0,941
Composite Reliability 0,945 0,954 0,944 0,955 Average Variance Extracted (AVE) 0,810 0,807 0,808 0,809 Inner Model Analysis The evaluation of this model was carried out using Coefficient Determination (R.
Goodness of Fit, and Hypothesis Test (Direct Effect and Indirect Effec.
, the following is the proposed PLS program model scheme:
Coefficient Determination (R.
The magnitude of the coefficient of determination (R-squar.
is used to measure how much the dependent variability is affected by other variables.
Chin said the R2 result of 67 and above for the dependent latent variable in the structural model identified the influence of the independent variable .
hich influence.
on the dependent variable .
hich is influence.
is included in the good category.
Meanwhile, if the result is 0.
67 then it is included in the medium category, and if the result is 0.
33 then it is included in the weak category.
Based on data processing that has been carried out using SmartPLS 3.
0, the R-Square value is obtained as follows:
Table 9.
Coefficient Determination Entrepreneurial Motivation_Z Start-Up Performance_Y Description Strong Strong The R-Square table is used to see the magnitude of the influence of variables simultaneously, the R-square value of the influence of Internship and Entrepreneurship Training on Entrepreneurial Motivation with a value of 0.
898 or 89.
8% is stated to have a strong influence.
Then the R-square value of the influence of the variables Internship.
Entrepreneurship Training and Entrepreneurial Motivation on Start Up Performance with a value of 0.
904 or 90.
4% is stated to have a strong influence.
Effect Size (F.
F Square testing is used to determine the effect of all exogenous variables on endogenous variables, the influence of all exogenous variables on mediation variables and the influence of mediation variables on endogenous variables, whether the influence of variables is classified into small, medium, or large.
F-Square values of 0.
02 are categorized as small, 0.
15 as medium and 0.
35 as large category.
Effect Size testing is performed and described in the following table:
Table 10.
Effect Size (F.
Internship (X.
Entreprenurship Training (X.
Start Up Performance (Y) Entrepreneurial Motivation (Z) Journal homepage http://mebis.
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Based on Table 10 shows that the effect size with a large value is the influence of X2 on Z because it has a value above 0.
The influence with a medium value is X1 on Z because it has a vulnerable value of 0.
02 to 0.
15, ending with a small effect size value, namely the influence of X1 on Y.
X2 on Y and Z to Y because it has a small effect size.
Goodness of Fit The assessment of goodness of fit is said to be based on the Q-square value.
The Q-Square value means that it can be said that the better or more fit with the data The Goodness of Fit value is divided into 3 categories, namely, small = 0.
1, medium = 0.
25, large = 0.
Based on data processing that has been carried out using smartPLS 3.
0, the Q-Square value is obtained as follows:
Tabel 11.
Predictive Relevance (Q.
SSO
SSE
Entrepreneurial Motivation_Z Entrepreneurship Training_X2 Internship _X1 Start-Up Performance_Y QA (=1-SSE/SSO) From the results of table 11 above shows the value of Q-Square / Predictive Relevance endogenous variables more than 0 or 0.
724 which means it has a good observation value.
The mediation variable based on the Q-Square table shows a value of 0.
721 which means that the vaiable has a good observation value.
Test the hypothesis Based on the data processed, the results can be used to answer the hypothesis in this study carried out by looking at T-Statistics and P Values.
The hypothesis is accepted when the P Value < 0.
In this study there are direct and indirect influences because there are independent variables, dependent variables, and mediation variables.
Direct Effect Testing This study proposed as many as 5 hypotheses.
Hypothesis testing using bootstrapping analysis techniques.
Through the results of the t-statistics obtained, a significant level of influence can be obtained between the independent variable to the dependent variable.
When the value of the t-statistic > 1.
(=TINV.
-table significance 5%) then the effect is significant.
Furthermore, through the results of the P-Value obtained if the P Value on each variable < 0.
H0 is rejected.
The positive influence can be seen through Original Sample.
The summary results of direct influence testing are as follows:
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Hypothesis Table 12.
Path Coefficient Original T Sample Statistics 0,270 4,455 Internship (X.
-> Start Up Performance (Y) Internship (X.
-> Entrepreneurial Motivation (Z) Entrepreneurship Training (X.
-> Start Up Performance (Y) Entrepreneurship Training (X.
-> Entrepreneurial Motivation (Z) Entrepreneurial Motivation (Z) -> Start Up Performance (Y) Values 0,456 8,955 0,000 0,384 7,500 0,000 Positive and Positive and Positive and Positive and 0,000 Description 0,508 9,922 0,000 0,319 5,412 0,000 Positive and The t-statistical value of the direct influence of Internship on Start Up Performance is greater than the t-table .
which is 4.
455 with an influence of 0.
270 and P-value < 05 of 0.
000 so that it can be concluded that the effect of Internship on Start Up Performance is positive and significant.
So, the H1 Internship hypothesis has a positive and significant effect on Start Up Performance accepted.
Based on table 12 above, it can be said that the t-statistical value of the effect of Internship on Entrepreneurial Motivation is greater than the t-table .
, which is 8.
955 with an influence of 0.
456 and a P-value of < 0.
05 of 0.
So, it can be concluded that the direct influence of Internship on Entrepreneurial Motivation is positive and significant.
So.
Hypothesis H2: Internship has a positive and significant effect on Entrepreneurial Motivation is accepted.
The t-statistical value of the influence of Entrepreneurship Training on Start Up Performance is smaller than the t-table .
which is 7.
500 with a magnitude of 0.
and the P-value of > 0.
05 which is 0.
000 so that it can be concluded that the direct influence of entrepreneurship training on start-up performance is positive and significant.
So the H3 Entrepreneurship Training hypothesis has a positive and significant effect on Start Up Performance.
The t-statistical value of the direct influence of Entrepreneurship Training on Entrepreneurial Motivation is greater than the t-table .
which is 9.
922 with a magnitude of 0.
508 and a P-value of > 0.
05 of 0.
000 so that it can be concluded that the direct influence of Entrepreneurship Training on Entrepreneurial Motivation is positive and significant.
So, hypothesis H4: Entrepreneurship Training has a positive and significant effect on Entrepreneurial Motivation is accepted The t-statistical value of the influence of Entrepreneurial Motivation on Start Up Performance is greater than the t-table .
which is 5.
with a magnitude of influence of 0.
319 and P-value < 0.
05 of 0.
000 so that it can be concluded that the direct influence of Entrepreneurial Motivation on Start Up Performance is positive and So, the hypothesis of H5 Entrepreneurial Motivation has a positive and significant effect on Start Up Performance is accepted.
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Indirect Effect Testing Testing the indirect influence of Internship and Entrepreneurship Training variables on Start Up Performance through Entrepreneurial Motivation.
The results of the analysis can be seen from the indirects effects of the boostrrapping technique.
The summary results are as follows:
Tabel 13.
Indirect Effect Original T Hipotesis Sample Statistics Internship (X.
-> H6 0,145 4,609 Entrepreneurial Motivation (Z) -> Start Up Performance (Y) Entrepreneurship Training H7 0,162 4,726 (X.
-> Entrepreneurial Motivation (Z) -> Start Up Performance (Y) Values 0,000 Descrioption 0,000 Positive and Positive and Based on table 13 above, the t-statistical value of the influence of Internship has a positive effect on Start Up Performance mediated by Entrepreneurial Motivation greater than the statistical value of t-table .
, which is 4.
609 with an influence of 0.
145 and p-value < 0.
05 spread 0.
So, it can be concluded that Entrepreneurial Motivation has a positive and significant effect in mediating Internships for Start Up Performance, then H6 is accepted.
The statistical value of the influence of Entrepreneurship Training has a positive effect on Start Up Performance mediated by Entrepreneurial Motivation greater than the statistical value of t-table .
which is 4.
726 with an influence of 0.
145 and p-value < 0.
05 spread 0.
So, it can be concluded that Entrepreneurship Training has a positive and significant effect in mediating Internships for Start Up Performance, then H7 is CONCLUSION The results of data analysis and discussion of the effect of internship and entrepreneurship training on start-up performance mediated by entrepreneurial motivation show important findings.
In this context, it can be concluded that internships have a significant positive influence on start-up performance, as well as have a significant positive impact on entrepreneurial motivation.
Meanwhile, entrepreneurship training does not show a significant influence directly on start-up performance but has a significant positive influence on entrepreneurial motivation.
Furthermore, entrepreneurial motivation itself is proven to have a significant positive influence on start-up performance.
In addition, internships also act as a significant mediator between student involvement in internship programs and increased entrepreneurial motivation which in turn contributes positively to start-up performance.
Similarly, entrepreneurship training is also a significant mediator between entrepreneurship training and start-up performance improvement through increased entrepreneurial motivation.
The results of this study underscore the importance of entrepreneurial motivation in the context of startup performance.
The entrepreneurial motivation factor turns out to have a significant positive influence on startup business results.
Therefore, startup companies and related entities should pay special attention to developing and nurturing Journal homepage http://mebis.
Jurnal MEBIS (Manajemen dan Bisni.
- Vol.
No.
Desember 2023, pp.
entrepreneurial motivation among their team members.
In addition, these findings highlight the important role of internship programs in improving startup performance through increasing entrepreneurial motivation.
This provides an incentive for startups to collaborate with interns or young professionals looking more actively for work By engaging them effectively, startups can garner passion and energy that can help them achieve success.
However, the finding that entrepreneurship training does not have a direct influence on startup performance reminds us to reflect again on the approach to training.
It may need to be upgraded or adjusted to better fit the startup's real
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