Academy of Entrepreneurship Journal (Print ISSN: 1087-9595; Online ISSN: 1528-2686)

Research Article: 2022 Vol: 28 Issue: 4S

Bayesian Independent Samples T-Test for Analysis Factor Entrepreneurial of Vocational School

Ariyono Setiawan, Universitas Negeri Surabaya

Munoto, Universitas Negeri Surabaya

Luthfiyah Nurlaela, Universitas Negeri Surabaya

Citation Information: Setiawan, A., Munoto, & Nurlaela, L. (2022). Bayesian independent samples T-test for analysis factor entrepreneurial of vocational school. Academy of Entrepreneurship Journal, 28(S4), 1- 14.

Abstract

 Entrepreneurship debriefing is one way that schools can do today to be able to equip students from an early age with motivation, knowledge about entrepreneurship. There are several factors that can be used as desire, motivation, character, and readiness. By doing survey respondents and data analysis because it uses conditional probability as the basis. In this Bayesian analysis, it is used as a determinant of factors that can influence a student to be open or ready to do entrepreneurship by using T test analysis as a comparative test to assess the difference between the factor value and the sample population value obtained from the factors of a student's interest in entrepreneurship and ready to practice entrepreneurship. Bayesian Independent Samples T-Test For Analysis Factor Entrepreneurial Of Vocational Schools with quantitative methods. Data analysis is carried out starting with organizing the data because the nature of quantitative data is generally very much and varied. The population in this study were all cadets in the ministry of air transportation. In this study, the population was about 585, but the data sample used by the author for the time being is a sample obtained by using a random sample method from the entire population.

Keywords

Vocational School, Entrepreneurship, Bayesian Independent, T-Test, Cadet

Introduction

Vocational schools that exist today are trying to make their students from job seeker to be job creator, there are many ways that vocational schools can be independent when students graduate or complete their studies. Entrepreneurship debriefing is one way that schools can do today to be able to equip students from an early age with motivation, knowledge about entrepreneurship. There are several factors that can be used as desire, motivation, character, and readiness. These factors can be seen from the student's interest that multiplying the potential in early entrepreneurship can be recognized, and then it can be directed to training and mentoring incubator to find suitable and appropriate entrepreneurs for each student.

Overview Theory

In this study, Bayesian analysis is used, namely to analyze uncertainty or can usually be reduced from the information data collected, so that it can perform a better analysis. By doing survey respondents and data analysis because it uses conditional probability as the basis. In this Bayesian analysis, it is used as a determinant of factors that can influence a student to be open or ready to do entrepreneurship by using T test analysis as a comparative test to assess the difference between the factor value and the sample population value obtained from the factors of a student's interest in entrepreneurship and ready to practice entrepreneurship.

Data Collection

In the process of finding answers to the problem formulation and research objectives, it is necessary to collect relevant data. The data collection was carried out in various ways, including library research, filling out questionnaires with several instruments from the variables of Interest, Efficacy, Knowledge, Motivation, Character, and Readiness.

Data Analysis

In this research, Bayesian Independent Samples T-Test For Analysis Factor Entrepreneurial Of Vocational Schools with quantitative methods. Data analysis is carried out starting with organizing the data because the nature of quantitative data is generally very much and varied. Organizing the data so that the data obtained is neat, structured, systematic, and complete. In the process of organizing the right data, researchers can obtain good quality data, document the analysis carried out, store the data and analyze it for the completion of the research carried out. Data analysis that is carried out is to use . The research location is an air transportation school with Bayesian Independent Samples T-Test For Analysis Factor Entrepreneurial Of Vocational School with a population of cadets, lecturers and the general public.

Research Methodology

Population and Sample

The population in this study were all cadets in the ministry of air transportation. In this study, the population was about 585, but the data sample used by the author for the time being is a sample obtained by using a random sample method from the entire population.

Intrument Questionnaire

The sample population in this study was obtained from the air transportation school ministry of transportation.

Table 1
Statistical description sample for sex
Descriptive Statistics Sex
Female Male
Valid 198 387
Missing 0 0
Mean 7.727 7.850
Std. Deviation 2.534 2.560
Minimum 3.000 1.000
Maximum 10.000 10.000

With a sample value of 585 respondents, among them are 198 women and 387 men, resulting in the following calculation

Table 2
Statistical description sample for status
Descriptive Statistics
  Status
  Cadets General Lecturer
Valid 537 34 14
Missing 0 0 0
Mean 7.784 8.206 7.786
Std. Deviation 2.564 2.508 2.155
Minimum 1.000 1.000 4.000
Maximum 10.000 10.000 10.000

Respondents with cadet status as many as 537 respondents from the public as many as 34 respondents and from lecturers as many as 14 respondents

Table 3
Descriptive statistics variable
EFF1 INT1 MOT1 KNW1 CHA1 RED1
  Female Male Female Male Female Male Female Male Female Male Female Male
Valid 198 387 198 387 198 387 198 387 198 387 198 387
Missing 0 0 0 0 0 0 0 0 0 0 0 0
Mean 7.152 7.367 7.727 7.850 7.530 7.509 6.753 6.933 7.939 7.742 7.843 7.630
Std. Deviation 2.386 2.482 2.534 2.560 2.474 2.583 2.481 2.507 2.420 2.583 2.378 2.534
Skewness -0.573 -0.774 -0.780 -0.969 -0.775 -0.823 -0.364 -0.554 -0.910 -0.873 -0.857 -0.826
Std. Error of Skewness 0.173 0.124 0.173 0.124 0.173 0.124 0.173 0.124 0.173 0.124 0.173 0.124
Kurtosis -0.960 -0.740 -0.989 -0.575 -0.788 -0.742 -1.114 -0.949 -0.677 -0.743 -0.700 -0.748
Std. Error of Kurtosis 0.344 0.247 0.344 0.247 0.344 0.247 0.344 0.247 0.344 0.247 0.344 0.247
Minimum 2.000 1.000 3.000 1.000 1.000 1.000 1.000 1.000 3.000 1.000 3.000 1.000
Maximum 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000
25th percentile 5.000 5.000 5.000 6.000 5.250 5.000 4.000 4.000 6.000 5.000 6.000 5.000
50th percentile 8.000 8.000 9.000 9.000 8.000 9.000 7.000 8.000 9.000 9.000 9.000 9.000
75th percentile 9.000 9.000 10.000 10.000 10.000 10.000 9.000 9.000 10.000 10.000 10.000 10.000
25th percentile 5.000 5.000 5.000 6.000 5.250 5.000 4.000 4.000 6.000 5.000 6.000 5.000
50th percentile 8.000 8.000 9.000 9.000 8.000 9.000 7.000 8.000 9.000 9.000 9.000 9.000
75th percentile 9.000 9.000 10.000 10.000 10.000 10.000 9.000 9.000 10.000 10.000 10.000 10.000

Data Retrieval

In the process of finding answers to the formulation of the problem and the purpose of this research, it is very necessary to collect relevant data. These data were collected in various ways, including literature studies, filling out questionnaires with several instruments every variable.

Data analysis

This type of research is descriptive with quantitative methods. Data analysis was carried out starting with the organization of the data because the nature of quantitative data was generally very numerous and varied. Organizing the data so that the data obtained is neat, structured, systematic, and complete. In the process of organizing the right data, researchers can obtain good quality data, document the analysis carried out, store the data and analyze it for the completion of the research carried out. Data analysis that is carried out is by using Bayesian Independent Samples T-Test. The research location is an air transportation school with a population of lecturer cadets and the general public

Result and Discussion

Cluster is a collection of objects or data that have similarities with one another in the same cluster and are not similar to objects in different clusters (Jain, 2010).

Table 4
Bayesian independent samples T-test
  BF10 error %
EFF1 0.159 2.285e -4
INT1 0.113 3.296e -4
MOT1 0.098 3.840e -4
KNW1 0.135 2.710e -4
CHA1 0.143 2.549e -4
RED1 0.155 2.344e -4

By analyzing data from each variable BF10 and error %, the results are as in the table

Prior and Posterior

Figure 1 Inferential plots for prior and posterior EFF1

Figure 2 Bayes factor robustness check EFF1

Figure 3 Inferential plots for prior and posterior INT1

Figure 4 Bayes factor robustness check INT1

Figure 5 Inferential plots for prior and posterior MOT1

Figure 6 Bayes factor robustness check MOT1

Figure 7 Inferential plots for prior and posterior KNW1

Figure 8 Bayes factor robustness check KNW1

Figure 9 Inferential plots for prior and posterior CHA1

Figure 10 Bayes factor robustness check CHA1

Figure 11 Inferential plots for prior and posterior RED1

Figure 12 Bayes factor robustness check RED1

Table 5
Result with bayesian independent samples t-test
95% Credible Interval
  Group N Mean SD SE Lower Upper
EFF1 Female 198 7.152 2.386 0.170 6.817 7.486
  Male 387 7.367 2.482 0.126 7.119 7.615
INT1 Female 198 7.727 2.534 0.180 7.372 8.082
  Male 387 7.850 2.560 0.130 7.594 8.106
MOT1 Female 198 7.530 2.474 0.176 7.184 7.877
  Male 387 7.509 2.583 0.131 7.251 7.767
KNW1 Female 198 6.753 2.481 0.176 6.405 7.100
  Male 387 6.933 2.507 0.127 6.682 7.183
CHA1 Female 198 7.939 2.420 0.172 7.600 8.278
  Male 387 7.742 2.583 0.131 7.483 8.000
RED1 Female 198 7.843 2.378 0.169 7.510 8.177
  Male 387 7.630 2.534 0.129 7.377 7.884

Conclusion

This research was conducted to see if there is Bayes method can only be used for classification problems with supervised learning and categorical data from the entrepreneurial interests of each cadet. The success rate of the test using the Bayes method is very dependent on the factors where students get learning about entrepreneurship that is given so that it affects the interest and readiness of the cadets to be able to start opening a business.

Suggestion

Based on research data, then suggested for future researchers to develop research on the approach contextual through different methods or comparing several methods.

Conflicts of Interest Statement

The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

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Received: 03-Feb-2022, Manuscript No. AEJ-22-10686; Editor assigned: 05- Feb -2022, PreQC No. AEJ-22-10686 (PQ); Reviewed: 19- Feb-2022, QC No. AEJ-22-10686; Revised: 26-Feb-2022, Manuscript No. AEJ-22-10686 (R); Published: 10-Mar-2022

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