INTRODUCTION
Currently, humans have
begun to enter the era of industrial revolution 4.0 seen from human work which
is replaced by automatic machines in the scope of industry(Nurjani, 2018). �Industry 4.0 is then said to be a disruption
because the rise of machine automation in an industry can have an unstable
impact on job competition. With the emergence of this phenomenon, it raises a
situation that allows making humans as industrial cogs will be replaced by
smart robots later(Nurjani, 2018)
The role of the
industrial revolution 4.0 is agreed to change humans, especially in the field
of work, the impact of the industrial revolution 4.0 is agreed to change
humans, especially in the field of work, the impact of the industrial
revolution 4.0 will be felt by manual workers because later it will be replaced
by automatic machines that make workers lose their jobs(NatureAntony Hotama,
& Kuswandi, 2019)
The results show that in
industry 4.0 digitalization opens up many jobs that make digitalization
continue to spread widely to various fields depending on the complexity of
automation. Judging from the technology that is very rapidly developing today,
it does not rule out the possibility that humans will be replaced later, just a
matter of time, this happens because the competitiveness of robots will
increase.(Rajnai & Kocsis,
2017)
Not a few media say that
humans will become obsolete because of the emergence of robots in the world of
work. The results obtained from the influence of robots, especially in the
industrial field, found that robots have a significant increase in high- and
middle-level jobs. Then robots are also considered more advanced and able to
work better technologically(Aprilia & Subiyantoro, 2022; Marsudi &
Widjaja, 2019; Suwardana,
2018)
The results obtained by
Acemoglu confirmed that robots will reduce human employment. It is based on the
robotics industry which has many advancements which are then attributed to
employment in the local industry. This is interesting because it is true that
robots reduce human employment, reinforced by the results of the European
Commission through the analysis carried out. Robots are referred to as
"killers" in the world of work, but this is inversely proportional
when robots have entered the industrial world, in fact companies that use
robots get a much higher level of productivity in their manufacturing processes(Alfa, 2019; Dara et al., 2022; Haqqi
& Wijayati, 2019; Muaja,
Adolfina, & Dotulong,
2017)(Ellitan,
2020; Ghufron, 2018; Kahf,
2017; Partono, Wardhani, Setyowati, Tsalitsa, &
Princess, 2021)
There are so many studies
on job competition between humans and robots, but each study has different
characteristics related to the problem, both from what is researched to the
actors involved in the research. Acemoglu's Robots and Jobs: Evidence from Us
Labor Markets examines the influence of robots on the U.S. labor market. The
results of this study found that one robot is compared to a thousand workers.
This led to a reduction in the population of labor ratios by 0.2 percentage
points and wages by 0.42. This finding can be attributed to the author because
in the world of industry 4.0 it is very necessary to know about job competition
against robots. (Kim, 2022; Richard, Goh, &; Margery, 2018)
An article by Lena
Ellitan entitled Competing in Era of Industrial Revolution 4.0 And Society 5.0
explains that in the era of the industrial revolution 4.0 there are many
challenges that will be faced by industry players such as lack of expertise and
even skills from human resources.
METHOD
This research was conducted using a qualitative descriptive approach. With
the data used, it is obtained from questionnaires distributed to resource
persons through several criteria that must be met beforehand by respondents.
The criteria that must be met by respondents are: a) Workers in the industrial
field for reasons that are more familiar with their work environment, b)
Respondents who are willing to fill out questionnaires. Questionnaires are made
using google forms, in the form of questionnaires or closed questionnaires,
Later respondents can only answer by sharing a characteristic on the answer
choices that are thought to be very suitable and able to describe their
thoughts (Sujarweni, 2015; Usman & Akbar, 2008).
Data is collected through main information because the source of
information is given directly to the informer through questionnaires
distributed to respondents, The data that has been collected is then used for
analysis using the form of the Likert scale which serves to determine the
perception of the respondents regarding the questions asked. The use of the
Likert scale on the riser that is carried out is the deadline of 1 point and a
maximum of 5 points, the Likert scale is used because later it will clearly
know the answers sent by respondents, whether later respondents will tend to
choose to agree or disagree, so that the results will be more relevant,(deep Sugiyono, 2017; Sugiyono, 2010)
|
No
|
Answer
|
Points
|
|
1
|
Strongly Disagree (SS)
|
1
|
|
2
|
Disagree (TS)
|
2
|
|
3
|
Neutral (N)
|
3
|
|
4
|
Agree (S)
|
4
|
|
5
|
Strongly Agree (SS)
|
5
|
The data obtained from the answers of the resource persons will then be
described with the aim of explaining the choices chosen by respondents. Then in
the final stage, the results of the research conducted by the author are
obtained through conclusions drawn from the data obtained after analysis with
the aim of finding a solution and facts of a problem being studied by the
author while relating the entire research process carried out.
In this study, a qualitative approach method was used which meant that numerical data (numbers) were processed by conducting statistical methods.
Through a quantitative approach, the significance of group differences or
differences in variables under study will be obtained.(Azwar, n.d.)
RESULTS
AND DISCUSSION
The
results from table 1 show that all data items are declared valid, this
corresponds to a correlation value higher than the validity value of 0.30.
|
Variable
|
Indicators
|
Corrected Item- Total
Correlation
|
Minimum Validity Value
|
Information
|
|
|
Robot Influence (X1)
|
X1.1
|
0.716
|
0,30
|
VALID
|
|
|
X1.2
|
0.653
|
0,30
|
VALID
|
|
|
X1.3
|
0.597
|
0,30
|
VALID
|
|
|
X1.4
|
0.36
|
0,30
|
VALID
|
|
|
X1.5
|
0.492
|
0,30
|
VALID
|
|
|
X1.6
|
0.617
|
0,30
|
VALID
|
|
|
X1.7
|
0.718
|
0,30
|
VALID
|
|
|
X1.8
|
0.71
|
0,30
|
VALID
|
|
|
X1.9
|
0.728
|
0,30
|
VALID
|
|
|
X1.10
|
0.609
|
0,30
|
VALID
|
|
|
Job Competition (X2)
|
X2.1
|
0.516
|
0,30
|
VALID
|
|
|
X2.2
|
0.347
|
0,30
|
VALID
|
|
|
X2.3
|
0.415
|
0,30
|
VALID
|
|
|
X2.4
|
0.552
|
0,30
|
VALID
|
|
|
X2.5
|
0.674
|
0,30
|
VALID
|
|
|
X2.6
|
0.645
|
0,30
|
VALID
|
|
|
X2.7
|
0.576
|
0,30
|
VALID
|
|
|
X2.8
|
0.587
|
0,30
|
VALID
|
|
|
X2.9
|
0.658
|
0,30
|
VALID
|
|
|
X2.10
|
0.398
|
0,30
|
VALID
|
|
|
Future of Labour
|
Y1.1
|
0.611
|
0,30
|
VALID
|
|
|
Y1.2
|
0.68
|
0,30
|
VALID
|
|
|
Y1.3
|
0.735
|
0,30
|
VALID
|
|
|
Y1.4
|
0.675
|
0,30
|
VALID
|
|
|
Y1.5
|
0.545
|
0,30
|
VALID
|
|
Table
2. Reliability Test Results
|
No
|
Variable
|
Cronbach's Alpha
|
Information
|
|
1
|
Robot Influence(X1)
|
0.884
|
Reliable
|
|
2
|
Job Competition(X2)
|
0.835
|
Reliable
|
|
3
|
Future of Labour(Y)
|
0.843
|
Reliable
|
Source: Processed DataSPSS25,
2023
Based
on the test results, it can be seen that the three variables are considered
reliable because they have Cronbach's Alpha > 0.6
Table
3. Multicollinearity Test Results
|
Variable
|
Tolerance
|
VIF
|
Information
|
|
Robot Influence
|
0.716
|
1,397
|
No Multicollinearity
|
|
Job Competition
|
0.716
|
1,397
|
No Multicollinearity
|
Source: Processed
DataSPSS25, 2023
Based on these results, by looking at the tolerance value model and Variance Inflation Factor (VIF), the
regression model of the influence of robots and job competition on the future
of workers does not occur symptoms of multicollinearity.
Heterokedasticity Test Graph
Figure 1 Heterokedasticity Test Graph
Source: Processed DataSPSS25, 2023
Based on the
Scatterplot graph above, it was found that the heterokedasticity
test displays points that spread between 0 on the Y axis, so In the regression
model the influence of robots in job competition on the Future of Labor there
is no problem of heterokedasticity
Normality
Test Graph
Figure 2 Normality
Test Graph
Source: Processed DataSPSS25, 2023
From
the test results above, it shows that the data is distributed normally because
the data or points spread out and follow the direction of the diagonal line so
that it can proceed to regression.
Table
4. F and T Test Results
|
ANOVAa
|
|
|
Type
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
1130.793
|
2
|
565.397
|
38.092
|
.001b
|
|
Residuals
|
697.627
|
47
|
14.843
|
|
|
|
Total
|
1828.420
|
49
|
|
|
|
|
a. Dependent Variable: The Future of Labour
|
|
|
b. Predictors: (Constant), Job Competition,
Robot Influence
|
|
|
|
|
|
|
|
|
|
|
|
Source:
Processed DataSPSS25, 2023
The regression model of all variables shows Fcalculate = 42.649 with a sig
of 0.001 < 0.05 this is equal to less than 5%. With a significant usage
limit of 0.05. From these results, a GIS value smaller than 0.05 positive
coefficient was obtained, so it was concluded that the influence of robots and
job competition on the future of workers was significantly accepted.
Table 5. Test result t
(partial)
|
Coefficientsa
|
|
Type
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
|
B
|
Std. Error
|
Beta
|
|
1
|
(Constant)
|
7.681
|
3.618
|
|
2.123
|
0.039
|
|
Robot Influence
|
0.007
|
0.083
|
0.009
|
0.082
|
0.935
|
|
Job Competition
|
0.815
|
0.111
|
0.782
|
7.341
|
0.001
|
|
a. Dependent
Variable: The Future of Labour
|
Source: Processed DataSPSS25, 2023
Tests were conducted to determine whether there is an
influence of robots and job competition in the industry on the future of
workers. This test is carried out by comparing the profit of the calculation
with a significant level of 0.05 (5%) as follows:
Based on the results:
1.
The variable of the
influence of the robot, the influence of the sig for the variable of the
influence of the robot on the future of workers is 0.935 > 0.05 and the
value of t is calculated 0.082 < 2.012, so that the results are obtained
that the hypothesis stating the influence of the robot is rejected and has no
effect on Y
2.
The variable of job
competition, the influence of GIS for the variable of job competition on the
future of workers is 0.001 < 0.05 and the value of t is calculated 7.341>
2.012, so that it is found that the hypothesis that states the influence of
robots is accepted and there is an influence on Y
Results of Multiple Linear Regression Equations
Table 6. Multiple Regression
|
Coefficientsa
|
|
Type
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
|
B
|
Std. Error
|
Beta
|
|
1
|
(Constant)
|
7.681
|
3.618
|
|
2.123
|
0.039
|
|
Robot Influence
|
0.007
|
0.083
|
0.009
|
0.082
|
0.935
|
|
Job Competition
|
0.815
|
0.111
|
0.782
|
7.341
|
0.001
|
|
Source:
Processed DataSPSS25, 2023
|
Judging from the
table above, there are results from the multiple linear regression equation,
namely: Y = 7.681 + 0.007X1 + 0.815X2 from this multiple linear regression
equation, it can be concluded as follows:
1.
The constant 7.681 means
that if the Effect of Robots (X1) and also Job Competition (X2) both have not
changed or can be said to be equal to zero (0), then it can be known the
magnitude of the Future of Labor (Y) of 7.681
2.
The X1 coefficient of
0.007 means that every time there is an increase in the variable X1 (Robot
Influence) by 1%, the Future of Workers (Y) increases by 0.007, or vice versa,
every time there is a decrease in the variable X1 (Robot Influence) by 1%, the
Future of Workers (Y) decreases by 0.007
3.
The X2 coefficient of
0.815 means that every time there is an increase in the variable X2 (Job
Competition) by 1%, the Job Competition (Y) increases by 0.815 or vice versa,
every time there is a decrease in the variable X2 (Job Competition) by 1%, the
Future of Workers (Y) decreases by 0.815
Table 7.
Coefficient of Determination (R�)
|
Model Summary
|
|
Type
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.786a
|
0.618
|
0.602
|
3.853
|
|
|
|
|
|
|
a.
Predictors:
(Constant), Job Competition, Influence of Robots
Source:
Processed DataSPSS25, 2023
The results
obtained from the correlation coefficient or R of 0.786 mean that the
relationship of the Influence of Robots (X1) and also on Job Competition (x2)
on the Future of Workers (Y) has a positive relationship with a value of 78.6%.
And
The results obtained from R Square (R�) worth 0.618 can be interpreted that
the Future of Workers with variable (Y) is influenced by the variable Influence
of Robots and the variable Job Competition simultaneously on the variable
Future of Labor (Y) is 61.8%
Discussion
The Influence of Robots
on the Future of Labor
����������� ����������� The Influence of Robots on the Future of Workers through
regression testing turned out to be a positive influence between the Influence
of Robots and the Future of Workers, with this showing that there is an
influence of robots on the front mass of workers in job competition but this is
not too significant considering that jobs will be given to human workers if in
accordance with their abilities and expertise.
The Effect of Job
Competition on the Future of Workers
����������� ����������� The Effect of Job Competition on the Future of Workers
has a significant positive influence between job competition and the future of
workers, this means that the competition in question is when robots begin to
compete with workers
The Influence of Robots
and Job Competition on the Future of Workers
From the results
of the F Test Statistical Test data, it was found that the Influence of Robots
and Job Competition on the Future of Workers has the same influence on the
future of workers with a significant coefficient value. Based on the
Correlation Test, a value of 78.6% was obtained, while for the deterimination
test, 61.8% of models of the influence of robots and job competition were
found.
CONCLUSION
Based on the results of
previous analyses and reviews, it will be partially concluded that the �Influence of Robots and Job
Competition with the Future of Workers has been tested to have a significant
positive influence between the model of the influence of robots and job
competition on the future of workers. It was found that the variable that is
very dominant in influencing the future of workers is job competition which has
a coefficient value greater than the variable of influence of robots.
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Copyright holder:
Alven Qois Charisteas, Milati Auliyah, M.Sadam Al Jabbar, Ramadani, Rizki Fadilah
Ramadhan, Rama Wijaya Abdul Rozak
(2023)
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First publication right:
Journal of Social Science
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This article is licensed under:
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