Abstract: - Entrepreneurship education is to be a solution to the unemployment problem. Entrepreneurial

character is for someone to act as an entrepreneur. The purpose of this study is to evaluate the instrument of

entrepreneurship character among students from various universities in Indonesia who adopt entrepreneurship

education in the curriculum. The research focused on the operational process of entrepreneurial characteristics

of 23 dimensions. The subjects of this study were 357 undergraduate students attending entrepreneurship

education. Psychometry is the research method, and SPSS and AMOS-assisted factor analysis to analyze the

results. The results showed that there was one indicator (Kbtp 10) that dropped in the factor analysis because it

did not meet the requirements (0.486 < 0.5). For EFA calculation, two (2) dimensions dropped because they

were accommodated in other dimensions/indicators and did not meet the calculation requirements. In the end,

The problem of unemployment is part of the world's

attention that affects the achievement of sustainable

development as stated in the Sustainable

Development Goals (SDGs) as aspired by the

United Nations in 2030. Unemployment has the

potential to hinder 17 (seventeen) issues that are the

main goals of the SDGs, and at least 6 (six) issues

are directly related. The six problems include

relevant in Indonesian universities.

graduates to work outside the scientific field is quite

open. Therefore, entrepreneurship education is

needed, the process needs to maximize, and its

success is measured appropriately [1], [2]. Several

unemployment rate reaching 12.49% [7], [8].

needs are still rare. For this purpose, this research

was conducted. Currently, measuring the success of

entrepreneurship education in Indonesian

universities has not been able to evaluate the success

achieved by students. The measuring success of

entrepreneurship education that is carried out places

more emphasis on book-smart and street-smart.

With a pattern like this, the efforts to encourage the

main factor that determines entrepreneurial success

[9]. Measurement pattern causes the reactionary

entrepreneurship lecture in an in-depth study, so,

naturally, university graduates contribute to a

significant unemployment rate. Entrepreneurship

lectures are on studies. The formation of

entrepreneurial character is not measured correctly.

However, in Indonesian universities, the instrument

of entrepreneurial qualities has not yet been

developed as one of the formations. Thus, the study

1.1 Identification of Problems

To measure the success of entrepreneurship is to get

student entrepreneurship. Several relevant studies on

instruments for measuring the success of

entrepreneurship learning have developed. Based on

these various literature studies, researchers are

interested in developing the instrument's

entrepreneurial character. This instrument is unique

because it measures the success of entrepreneurship

education through an evaluation of the

and religion [11]-[13].

weaknesses in measuring the success of

entrepreneurship learning in Indonesian universities.

First, the scope of the area in developing the

measurement of entrepreneurial character is still too

individual productivity to increase personal income

[26]. Therefore, entrepreneurship education

generates human capital. Human capital says that

the higher education a person has, the more

opportunity and may generate higher income [27].

So, entrepreneurial education must concern with

human capital. Human capital needs an

entrepreneurial character too.

education [28]. Therefore, entrepreneurship

[37], [40],[43], [44].

3.1 Participants

This research is descriptive, using the psychometric

method. Data using questionnaires were distributed

electronically with Google Forms with non-random

snowballs. This procedure was active for two

in this study is 357 students spread across western,

central, and eastern parts of Indonesia. The

questionnaire used so far was tested

psychometrically by factor testing using SPSS V.23

software and for the exploratory factor analysis test

using Amos V.23.

component analysis. It is also used to identify a

relatively small number of factors that can be used

to explain a large number of interrelated variables.

use varimax methods to transform to rotate the

of the original variables to have a high correlation

with certain factors only so that each will be easier

to interpret.

to explain the variability between observed variables

(manifest variables) or variables correlated with

variables called factors. EFA is used when research

is looking for a structure of a variable, or it is called

a data reduction method. EFA can trace correlations

based more on actual data than on theory. The

purpose of EFA is to reduce the number of variables

and detect the relationship between variables, to

classify variables.

3.2 Instruments

The questionnaire evaluates the 23 dimensions

The first step of this test is based on the Kaiser-

Meyer-Olkin (KMO) test, the following output is

the results presented in Table 2.

Source: Data results, 2022

analysis can be continued.

proceed with the second eligibility prerequisite test

for the entrepreneurial character variable by looking

at the Measures of Sampling Adequacy (MSA)

value on the anti-image correlation matrices. Based

on the SPSS output in Table 2, the letter code (a) is

the sign for MSA. The table above shows the MSA

value for all the variables studied is > 0.50. It

fulfilled the second requirement for proceeds to

output in the table above, there is one indicator that

is not able to explain the entrepreneurial character

variable, namely the dimension "need for

achievement" indicators "desire to compete with

others" (Kbtp 10) because it has an extraction value

of 0.486 < 0.5. So based on this, the indicator "the

desire to compete with others" (Kbtp 10) is dropped

in this study.

component in the variable, the Total Variance

described in Table 6:

Source: Data Analysis, 2022.

indicators, components 2 - 10 indicators,

components 3 - 9 indicators, components 4 - 10

indicators, components 5 - 10 indicators,

obtained is getting closer to 1 (either -1 or +1),

which indicates the stronger. Components correlate

0.00-0.30 in the moderate, 0.31-0.70 in the good,

and 0.71-1.00 in the very good without seeing the

plus or minus sign.

4.2 Exploration Factor Analysis with AMOS

4.2.1 Goodness of Fit (GOF)

Data analysis follows standard educational and

Adaption = 0.751, and Entrepreneurial Flexibility =

0.743.

4.2.3 Discriminant Validity

Discriminant validity by looking at the ratio of the

between-trait correlation to the within-trait

correlations [51]. If the HTMT value is < 0.9 then

discriminant validity is achieved (Henseler, Ringle,

& Sarstedt, 2015). In this study, discriminant

validity was achieved in all cases both

Entrepreneurial Intelligence - Entrepreneurial

Adaption (0.86), Entrepreneurial Intelligence -

Entrepreneurial Flexibility (0.83), Actualization -

Entrepreneurial Adaption (0.90), Actualization -

Entrepreneurial Flexibility (0.85), and

Entrepreneurial Adaption - Entrepreneurial

Flexibility (0.79).

4.3 Discussion

In the last few decades, entrepreneurship has

developed to achieve higher education in Indonesia.

evaluate entrepreneurship in universities in

Indonesia. This study evaluates the process of

entrepreneurial characteristics [10], [15]-[18] of 23

dimensions to collect evidence about the

repositioning instruments and the entrepreneurial

character in Indonesian universities.

RQ1: Has a repositioning of dimensions on the

entrepreneurial character instrument after the

revaluation?

(8) components based on the Eigenvalues.

closely related to entrepreneurial adaptation [60],

[61]. Therefore, entrepreneurial adaptation becomes

self-resilience.

(EFA) with AMOS show that the Maximum-

Likelihood Estimation matrix extraction method and

the fit model are considered adequate for all

self-development and resilience are not part of the