The Influence of Education, Training, and Individual Characteristics
on The Performance of Civil Servants in State Administrative
Institutions
Meta
Lorenta1,
Herry Krisnandi2,
Kumba Digdowiseiso3
Faculty of Economics and
Business,
Universitas National, Indonesia1,2,3
*E-mail: [email protected]1,
[email protected]2, [email protected]3
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ABSTRACT |
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Education, Training, Individual Characteristics,
Employee Performance. |
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This study aims to explore the influence of
education, training, and individual characteristics on the performance of
civil servants within state administration institutions, focusing on a sample
of 101 employees randomly selected from the population of 135 at the Jakarta
State Administration Institute. This research is included in quantitative
research, where the research instrument uses a questionnaire. Utilizing the
"Multiple Linear Regression" analysis, the findings reveal nuanced
relationships. While education positively correlates with employee
performance, the effect is not statistically significant. This
non-significant result should be interpreted with caution, emphasizing the
need for further exploration and nuanced consideration of the role of
education in enhancing performance. Conversely, training exhibits a positive
and statistically significant impact on performance, emphasizing its crucial
role in bolstering employee effectiveness. Furthermore, individual
characteristics have a positive and statistically significant influence on
performance. It is essential to convey that the positive effect of education
should not be dismissed due to its non-significant nature; rather, it prompts
a deeper examination of the intricate dynamics between education and
performance. This research underscores the importance of understanding these
factors in the context of state administration institutions, providing
valuable insights for optimizing the contributions of civil servants and
enhancing overall institutional effectiveness. |
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INTRODUCTION
The Covid-19 pandemic has inflicted considerable
challenges on the Indonesian community, particularly in Jakarta. Mandatory
self-restriction measures aimed at curbing virus spread have led to the
cessation of diverse activities, ranging from work and study to various social
engagements. Public events, including music concerts, weddings, and social
gatherings, have been cancelled, and economic sectors, such as the market, have
experienced temporary paralysis. The pandemic's impact spans various
educational levels, from higher education to elementary education, including
within the State Administration Institute (LAN). Responding to this situation,
the LAN government instituted a Work From Home (WFH) policy for employees,
including Civil Servants (PNS). This policy, aligned with health decisions and
emergencies, strives to prevent the spread of COVID-19. Moreover, it aims to
not only afford free time to civil servants but also mandates regular reporting
of work results. This measure aligns with government policies promoting Social
and Physical Distancing to combat the pandemic.
In the context of contemporary organizations, leaders
must adapt to changes and advancements across various domains to impact
performance and productivity. Human resources play a pivotal role in achieving
organizational goals, necessitating effective management, particularly in terms
of human resource development. Education and training are crucial factors in
enhancing employee performance, shaping individual characteristics, and
attaining organizational effectiveness. Focusing on education and training within
government agencies aims to enhance the knowledge and skills of employees,
providing benefits for both individuals and organizational progress. Continuous
education and training are deemed essential to cultivate high-quality civil
servants. Individual characteristics, encompassing interests, attitudes, and
needs, significantly influence employee performance. Human resource development
through education and training aims to create employees who are competent in
their duties and possess individual characteristics supporting work
effectiveness. Consequently, this study scrutinizes the impact of education,
training, and individual characteristics on the performance of Civil Servants
in State Administration Institutions, aiming to offer valuable insights and
serve as a foundation for future research in the realm of employee development
and organizational effectiveness.
METHODS
This research method uses a survey
method by collecting data through questionnaires. The object of research is
the performance of employees in the State Administration Institute, focusing on the influence
of education, training, and individual characteristics on employee performance. The research was conducted
at the State Administration Institute (LAN RI)
of DKI Jakarta Regional Provision.
The research time includes observations and surveys in September 2021, while the research
was carried out in November 2021 until completion.
The research variables consist of three
independent variables, namely education (X1), training (X2), and individual characteristics (X3), and one dependent variable,
namely employee performance (Y). The research
plan includes the preparation of proposals, proposal seminars,
data collection, data processing,
and the preparation
of the final thesis report. Data sources are divided into two types,
namely primary data obtained through questionnaires distributed to civil servants
at the State Administration Institute, and secondary data obtained from interviews
with the head of personnel,
including data on the number of
employees, qualifications, competencies, discipline, and employee performance.
The study population
was employees of the State Administration
Institute with a total of 135 people, and a sample of
101 respondents was taken using random
sampling techniques. The data collection
method uses questionnaires distributed through Google Forms. The data
were analyzed by quantitative descriptive methods and multiple
linear regression analysis.
The operational definition of research variables
includes education, training, individual characteristics,
and employee performance with measurable indicators. The validity and reliability
of the research
instruments were tested using statistical analysis such as the Pearson product moment formula and Cronbach alpha. The classical assumption test involves tests
of normality, multicollinearity, autocorrelation,
and heteroscedasticity. Multiple linear regression analysis is performed
to determine the effect of
the independent variable on the
dependent variable. The feasibility test of the model uses
the F test, the coefficient of determination (R2), and the t test
for each partially independent variable. The entire research process aims to gain a deep understanding of the factors
affecting the performance of employees in the State Administration Institution.
RESULTS
The descriptive
test results for the average
of each statement
on each variable
are shown in the following tables. The variables studied include education (X1), training (X2), and individual characteristics (X3) as independent
variables, and employee performance (Y) as dependent variables. Each variable was
measured using several question items, and data analysis was carried
out using statistical calculation methods through the SPSS 25 program. Education
(X1): The mean mean for the education
variable is 4.13. The statement with the highest mean
value was "Education programs organized by LAN aim to improve
employee intelligence"
(4.26), while the statement with the lowest mean
value was "Improved mental health and self-confidence can be achieved
through regular education programs" (3.95). Training (X2): The mean mean for the
training variable is 4.02. The statements with the highest
mean values were "Training programs in LAN can improve employee
performance productivity"
(4.11) and "Training programs organized by LAN in Human Resources develop
a better work ethic" (4.11), while the statements with the lowest
mean values were "I was able to
complete the work given by
my boss within
a predetermined time"
(3.88). Individual Characteristics (X3): The mean mean for
individual characteristic variables
is 4.24. The statement with the highest
mean value is "With the
interectual ability I have I find it
easy to understand
a job" (4.29), while the statement with
the lowest mean value is
"My assigned value in the job" (4.01).
Employee Performance (Y): The mean mean for
employee performance variables is 4.16. The statement with the highest mean
value is "I am responsible for each other's
assigned work" (4.39),
while the statement with the lowest mean
value is "My current job matches
the skills I have" (3.95). Next, a validity test is
carried out to ensure the
accuracy of the measuring instrument.
All variables, namely education (X1), training (X2),
individual characteristics (X3), and
employee performance (Y),
were declared valid based on the results
of the item-total statistics validity test. Reliability tests using the
Cronbach Alpha method showed that
the four variables had high reliability values, namely education (X1) of 0.918, training (X2) of 0.953, individual characteristics
(X3) of 0.884, and employee performance (Y) of 0.933. Finally, the normality test
using the Kolmogorov-Smirnov Test shows that the
data on all variables are normally distributed with significance values (Asymp. Sig.) above
0.05. Thus, it can be concluded
that the test model has met the conditions of data normality. With these results,
it can be
relied upon that this study has used valid, reliable, and normally distributed
measurement tools, so as to provide
accurate and reliable research results.
The multicolonearity
test can be seen from
the Variance Inflation Factor (VIF) and Tolerance, if the VIF value
is less than
10 and the Tolerance is more
than 0.1, it is stated that
multicollinearity does not occur. A good regression
model does not have a perfect or near-perfect
correlation between independent variables (Multicollinearity). Based on the results
of the Multicholinerity
Coefficient Test above, it is
known that the VIF count for
four variables < 10 VIF values and Tolerance
values of more than 0.1 which
means that the regression model does not contain multicollinearity. Autocorrelation
is useful to find out
whether in a linear regression
model there is a strong relationship both positive and
negative between data on research variables.
In autocorrelation testing, researchers
used the Durbin-Watson (DW) method. The results of autocorrelation
testing are as follows: Based
on the results
of the autocorrelation
test table 24 it is known
that the magnitude of Durbin-Watson
= 1.889 compared to the value of
Durbin-Watson table using a significance of 5% of the
number of samples 101 (n) and the number of
independent variables 4 (K
= 3), then in the Durbin-Watson table obtained dL = 1.615 and dU = 1.737. Because the Durbin-Watson
value of 1.889 is greater than
the upper bound (dU) of
1.615 and less than 4-1.737 = 2.263(4-dU). This is in accordance with the decision
criteria, namely dU < DW < 4-dU (1,737 < 1,889 < 2,263) then DW lies between
dU and 4-dU, so it can
be concluded that there is
no autocorrelation. The heteroscedasticity test using the glacier
test aims to test whether
in a regression model, there
is an inequality
of variance from the residual
from another observation. A good regression model does not occur heteroscedasticity. The results of hetroscedasticity
testing can be seen in Table 1 below:
Table 1. Gletjer
Test Results
|
Coefficient |
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Model |
Say. |
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1 |
(Constant) |
.000 |
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Education |
.669 |
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Training |
.409 |
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Karakteristik_Individu |
.400 |
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Source: SPSS 26.00 processed
data
Based on Table 1, it can
be explained the heteroscedasticity test with the
glacier method from the independent
variable and variable X showing 0.669, 0.409, and 0.400. This value obtained a significance value greater than 0.05 so that it
can be said
that the three variables above do not experience
heteroscedasticity problems.
Multiple linear regression analysis is a form
of analysis that discusses the extent of
the influence of the independent
variable (X) on the dependent variable
(Y). Where the independent variables are education (X1), training (X2),
individual characteristics (X3). While
the dependent variable is employee
performance (Y). In calculating
the regression coefficient in this study using SPSS 26.00, the calculation results are as follows:
Table 2. Multiple
Linear Regression Analysis Results
|
Unstandardized Coefficients |
Standardized Coefficients |
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Model |
B |
Std. Error |
Beta |
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1 |
(Constant) |
14.141 |
3.045 |
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Education |
.193 |
.133 |
.176 |
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Training |
.251 |
.114 |
.244 |
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Karakteristik_Individu |
.888 |
.154 |
.569 |
|
Source: SPSS 26.00 processed
data
The regression
equation provides an overview of
the relationship between independent variables, namely education, training, and individual characteristics, with variables tied to employee
performance. In the equation, a constant value (Constant) of 14.141 indicates that if the
independent variable (education, training, and individual characteristics)
has a fixed value, then the value
of the variable
tied to employee
performance will be 14.141. Furthermore, the regression coefficient for the education variable
of 0.193 illustrates that if education
increases by one unit, then employee performance will increase by
0.193, with a standard error of 0.133 when the education
variable is considered constant. Similarly, the training variable has a regression coefficient of 0.251, indicating that a one-unit increase in training will lead to
an increase in employee performance of 0.251, with a standard error of 0.114 when the
training variable is considered constant.
Finally, the
individual characteristic variable
has a regression coefficient
of 0.888, which explains that if
the individual characteristic
increases by one unit, employee performance will increase by 0.888, with a standard error of 0.154 when the training
variable is considered constant. Of the three
independent variables, namely education, training and individual characteristics have a positive influence on employee performance.
Thus, if education, training and individual characteristics increase, employee performance variables will experience the same.
The F test is used to
test the significance of the regression coefficient together, namely whether the independent variable has an influence on the
dependent variable tested at a significant
level of 0.05. In this case, the ANOVA table is used
to examine the significant effect of education,
training and individual characteristics on the performance of employees of
the State Administration Institution. In this study the significance of the value
of Sig. Fcalculate
will be compared
with 0.05.If sig. Fcalculate < 0.05 then H0 is rejected meaning
that the proposed hypothesis is acceptable. Conversely, if sig. Fcalculate > 0.05 then H0 is accepted,
meaning that the proposed hypothesis
is rejected. The results of SPSS 26.00 management show the following:
Table 3. Hasil Uji F
ANOVA
|
Model |
Sum of Squares |
Df |
Mean Square |
F |
Say. |
|
|
1 |
Regression |
2109.342 |
3 |
703.114 |
80.575 |
.000b |
|
Residual |
846.440 |
97 |
8.726 |
|
|
|
|
Total |
2955.782 |
100 |
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|
From table 3 above, it is obtained
that Sig 0.000 is smaller than
the alpha probability limit of 5% (0.05). Sig in table 3 is said to be
significant because it is below
the limit of the alpha probability
value specified 0.000 <
0.05. Then the hypothesis of no
F test is accepted based on the resulting
significance value smaller than 0.05. So it can
be concluded that in this study the model is said
to be of
significance and worthy of use
in this study based on the Sig
value obtained, that all variables
are independent because they have a significant
influence. Coefficient of determination (R2) analysis is used
to determine how much the
percentage of the dependent variable
contribution can be explained by
the independent variable. The output results are as follows:
Table 4. Results of the Coefficient
of Determination (R2)
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the
Estimate |
|
1 |
.845a |
.714 |
.705 |
2.95401 |
Based on Table 4, the coefficient of determination (R2) is 0.714, which means that
the variable level of employee performance
can be influenced
by education, training and individual characteristics 71.4%, while the remaining 28.6% is explained by
other factors outside the regression
model analyzed. T test to determine whether
education, training and individual characteristics have a positive and significant effect on employee
performance. The tester uses
a significant level of
0.05. The test results are
as follows:
Table 5. Hasil Uji t
|
Model |
t |
Say. |
|
|
1 |
(Constant) |
4.644 |
.000 |
|
Education |
.701 |
.485 |
|
|
Training |
2.210 |
.029 |
|
|
Karakteristik_Individu |
5.761 |
.000 |
|
Based on Table 5 presented, conclusions can be drawn regarding
the results of t-test testing on research variables.
First, the effect of education on
employee performance, as reflected in Table 28, shows that the
calculated value is 2.701 with a significance of 0.485 (0.015 <
0.05). Therefore, Ho was rejected and Ha was accepted, implying
that education had a positive but not significant effect on employee performance.
Second, regarding the effect of
training, Table 29 reflects that the
tcount is 2.210 with a significance of 0.029 (0.029 < 0.05). With Ho's rejection and Ha's acceptance,
it can be
concluded that training has a positive and significant influence on employee
performance. Finally, the influence of
individual characteristics, as illustrated
from Table 29, shows a calculated value of 5.761 with a significance of 0.000 (0.000 < 0.05). With Ho's refusal and
Ha's acceptance, it can be
concluded that individual characteristics have a positive and significant
influence on employee performance. The overall results of the t-test
test confirmed that education had a positive but not significant influence, while training and individual characteristics
had a positive and significant influence on employee performance.
The effect of education on employee
performance
Based
on the results
of the study, it shows that
testing the first hypothesis, namely the influence of
education on employee performance, shows that the
education variable (X1) has
a positive and significant effect on employee performance
variables (Y). In the educational variable, a calculated t value of 2.701 was obtained
with a significant value of 0.015 < 0.05, then H0 was rejected
and H1 was accepted, therefore it can be
said that in this study the educational variable had a positive and significant
effect on the performance of employees of
the State Administration Institution. Based on skunder data, it is stated
that 34% of employees have education that is not linear with the position currently
occupied. This is reinforced by
respondents' answers about the researcher's
statement in the questionnaire with redaction sounds. From there it
can be concluded
that the factors that cause
education to have a small or
low influence on employee performance,
which is 19.3%.
The purpose of employee education
is not linear with the position currently
occupied is the discrepancy of the last
education major pursued by employees
when formal education. Thus, if employees
do not have education in accordance with their work
unit will affect their performance. But on the
contrary, if employees have an even education,
it will increasingly
affect the improvement of employee performance, then it takes
someone's interest in doing work, an
attitude that can work together
with other employees in completing a job, have the
ability and competence in accordance with the position
placed, have extensive knowledge about their work,
not easily emotional in doing a job.
The effect of training on employee
performance
Based on the results of
the study, it shows that testing the second hypothesis,
namely the effect of training
on employee performance, shows that the training
variable (X2) has a positive
and significant effect on the
employee performance variable (Y). In the training variable, a calculated t value of 2.210 was obtained
with a significant value of 0.029 < 0.05, then H0 was rejected,
and H1 was accepted. Therefore it can be
said that in this study, the training variable had a positive and significant
effect on the performance of the State Administration
Institute employees. Similar research entitled "The Effect of Education and
Training on Employee Performance (Study on the Regional Civil Service Agency of Malang City)"
(Pakpahan et al., 2014). This research shows
that there is a significant influence between training and employee
performance and there is a significant
influence of education on employee
performance. This is shown by
Fcalculate = 45.222 > Ftable
= 3.195 as well as a partial
test with a t test, for the
educational variable (X1) obtained, the calculated value is greater than
table (3.298 > 2.011) and
the significant value is greater
than α = 0.05 and the training variable
(X2) obtained a calculated value of 4.593 with a significance of 0.000. The calculated value is greater
than that of table (4.593 < 2.011), and the significant value is greater
than α = 0.05. This research uses theories
related to indicators of formal and non-formal education, leadership training, functional training, and technical training. The value criteria examined in this study are by looking at
quality, quantity, and attitude/reliability towards performance.
The influence of
individual characteristics on
employee performance
Based
on the results
of the study show that testing the third hypothesis,
namely the influence of individual characteristics on employee performance, shows that individual characteristic variables
individual characteristics (X3) have
a positive and significant effect on employee performance
variables (Y). In the training variable, a calculated t value of 5.761 was obtained
with a significant value of 0.000 < 0.05, then H0 was rejected
and H1 was accepted, therefore it can be
said that in this study the training variable had a positive and significant
effect on the performance of employees of
the State Administration Institute. This statement is also
in accordance with Nopiani's opinion (2016)
Individual characteristics have
a positive and significant effect on the performance
of TVRI Lampung employees. So characteristics play an important
role in improving employee performance.
CONCLUSION
Employee
performance is 0.647, which means that
individual characteristics have
a positive and significant influence on
employee performance. From the overall
results of the study, it can
be concluded that education, training, and individual characteristics have a positive effect on the performance
of employees in the State Administration Institute. Although the influence of
education on employee performance is not significant, the role of
education still contributes positively. Job training and
individual characteristics significantly
influence
employee performance, which shows that
investment in training and attention to
individual characteristics can
improve employee performance in State Administration
Institutions. The results of this study can
be used by
the management of the State Administration
Institute to pay more attention
to aspects of education, training,
and individual characteristics
in human resource management
to improve employee performance. In addition, this research can also
be the basis for further research
and comparison with research results
in similar institutions or different contexts.
However, remember that this study has limitations, such as a limited population of State Administration Institutions, and the results may
not be directly applicable to other
organizational contexts. Therefore, conducting further research by involving more
institutions or organizations is recommended to get more general
and widely applicable results. Employees are valued at 0.888, meaning that individual characteristics have a positive and significant influence on
employee performance.
This article is a part of
joint research and publication between Faculty of Economics and
Business, National University, Jakarta and Faculty of
Business, Economics, and Social Development, Universiti
Malaysia Terengganu.
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Copyright holder: Meta Lorenta, Herry Krisnandi, Kumba Digdowiseiso (2024) |
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First publication
rights: International
Journal of Social Service and Research (IJSSR) |
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