p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 4 April 2024 http://jist.publikasiindonesia.id/
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1508
The Effect of Job Resources on Work Engagement through
Job Crafting and Burnout in Public High School Teachers in
West Kotawaringin
Yenni Lawrensia
1*
, Tuty Lindawati
2
Universitas Katolik Widya Mandala Surabaya, Indonesia
Email: [email protected]
1*
, [email protected]
2
*Correspondence
ABSTRACT
Keywords:
Job Resources, Work
Engagement, Job
Crafting, Burnout.
This study aims to determine the effect of job resources on
work engagement through job crafting and burnout in public
high school teachers in West Kotawaringin. This study is a
causal study. The data collection tool used is an online
questionnaire in the form of a google form. Questionnaires
are distributed by snowball sampling, where some subjects
will be selected to represent the school and then distribute
the questionnaire to others. The population in this study is
public high school teachers in West Kotawaringin. The
sample in this study was 166 respondents with the criteria of
having worked as teachers for one year. Data analysis
techniques in this study use SEM (Structural Equation
Model) using the lisrel program. The results showed that
there is a positive and significant influence between job
resources on work engagement, there is a positive and
significant influence between job resources on job crafting,
there is a negative influence between job resources on
burnout, there is no positive and significant influence
between job crafting on work engagement, there is a
negative influence between burnout on work engagement,
there is a positive and significant influence between job
resources on work engagement through job crafting, and
there is a positive and significant influence between job
resources on work engagement through burnout.
Introduction
Human resources (HR) are the most valuable assets for an organization (Rifa’i,
Ananda, & Fadhli, 2018). Successful HR is seen from how it performs against the
organization. Therefore, high employee performance is needed by companies, especially
to face the era of globalization in order to survive and win the competition. According to
(Aldrin & Merdiaty, 2019), employee performance is indispensable to improve
organizational performance in any country. Capital, machines and methods that become
company resources can no longer provide optimal results if they are not supported by
human resources who have optimal performance. Today, however, the success of any
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1509
business is not only determined by employee performance but also by employee loyalty
associated with a concept i.e. the concept of attachment. Engagement will result in
positive things in the organization such as superior workplace performance. Based on a
survey conducted by (De Beer, Tims, & Bakker, 2016), companies with a high level of
employee engagement increase productivity by 20% and profits increase by 21% so that
this engagement is proven to increase the development of an organization.
(De Beer et al., 2016) determines the current percentage of employee engagement
as follows: 21% of employees are engaged employees, 54% of employees are not engaged
employees and 19% of employees are actively disengaged. From these results, it can be
concluded that there are still few workers who feel engaged in their work and employees
who are not engaged in their work will have a negative impact, namely the target where
employees work will not be achieved because there is no enthusiasm from within
employees. (Jiménez, Bregenzer, Kallus, Fruhwirth, & Wagner-Hartl, 2017) define work
engagement as the psychological state of employees who have the desire to contribute to
the success of the company where the employee works and the desire of employees to
continue to be part of the company where they work. Job resources are physical, social,
psychological, or organizational aspects of work that are able to reduce job demands in
relation to psychological sacrifice, provide a positive influence to achieve goals easily
and encourage employees to be able to develop themselves.
In addition, the thing that can affect work engagement is burnout. Burnout is a
term used to express a deterioration in mental or physical exertion. (Jiménez, Winkler, &
Dunkl, 2017) define burnout as a form of fatigue caused by someone working intensely,
dedicatedly and committedly, working full and very long and viewing their needs and
wants as secondary. The causes of burnout come from two factors, namely: (1) external
factors such as working conditions, lack of opportunities for self-development, lack of
social support from leadership, excessive task demands and boring tasks and (2) internal
factors including age, gender, honor, level of education, length of work and personality
characteristics. Fatigue caused by burnout will affect low enthusiasm, dedication, and
appreciation, which then gives the impression of low work engagement of a worker.
Researchers agree that the most important factor in determining student
performance is teacher quality. Teachers play such a valuable role in shaping student
growth, academically and socially. The role of the teacher has evolved from the traditional
role of teaching, which used to be just teaching, to include administrative work. In
addition, teachers are also responsible for disciplining and providing counseling to their
students. School teachers are also considered as the backbone of a country's development
as teachers play an important role in strengthening unity and building national identity as
well as developing human resources to face the challenges of globalization. All this
contributes to the view that education is a pillar of a country's success, while school
teachers are a pillar of educational success.
Engagement is important for a teacher because engagement is a condition that
shows when teachers can be the most influential part of students' lives, teachers who have
high enthusiasm when teaching, teachers who care deeply about the success of students
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1510
even beyond existing standards, teachers who understand subjects well but are not afraid
to admit that they still need to learn more, Teachers who take pride in their work can
transmit their confidence and optimism. The level of teacher engagement decreases at the
next level. Therefore, this study will refer to the highest level of school, namely Senior
High School (SMA) to test whether the indication of engagement is proven to be less the
higher the school level or the results obtained will be different.
Job resources will be a research variable that tests how big this variable is in
increasing a teacher's work attachment. As explained by Schaufeli (2017) that job
resources are used to monitor the workplace which aims to increase work engagement.
Job resources impose a psychological motivation process that motivates teachers to
engage in tasks and roles, leading to job enjoyment and attachment. Therefore, teachers
will experience high job attachment if their job resources such as job control, access to
information, and supervisory support are available because job resources help them to do
their jobs.
Based on a survey conducted by Gallup (2022) shows that K-12 workers
(elementary to secondary teachers) have the highest level of burnout compared to other
industries. The results are based on Gallup's Panel Workforce Study, conducted Feb. 3-
14, 2022, with 12,319 full-time employees in the United States, including 1,263 K-12
workers. In the United States, 44% of teachers in K-12 education say they often or always
feel burnout, while for college or university workers, the figure is as high as 35%. These
are the top two jobs among the 14 listed in the 2022 Gallup Poll on burnout. Student
performance can be negatively affected by teacher stress. In the first meta-analysis of
teacher burnout research, a systematic literature review of 14 studies of 5,311 teachers
and their 50,616 students showed evidence that teacher burnout is associated with poorer
student academic achievement and lower quality student motivation. The findings repeat
the need for more detailed studies but provide preliminary evidence that teacher burnout
can affect the students they teach.
This study aims to find the impact of job demand and job resources on work
engagement. The population in this study is employees of private companies in Korea.
The study sample consisted of 198 participants. Data was collected directly from
respondents by distributing questionnaires. The results of this study first show that job
resources (job autonomy and performance feedback) have a positive and significant effect
on work engagement. Second, it shows that job demands (technology demands) have a
significant effect on job stress. Third, it shows that job resources (job autonomy) have a
positive and significant effect on job crafting. Fourth, it shows that job demands (work
overload and emotional demand) positively and significantly affect job crafting. Fifth,
show job crafting has a significant effect on work engagement. Sixth, it shows that job
crafting has a significant effect on job stress. Seventh, shows that job crafting mediates
the relationship between job resources and engagement.
The second previous research that became a reference in this study was a study
conducted by (Jimenez & Dunkl, 2017) in Malaysia with the title "Job Demands &; Job
Resources: Predicting Burnout and Work Engagement Among Teachers". The purpose of
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1511
this study is to understand how to increase teacher engagement adapted from cases that
have continued to evolve over the past few years. The population in this study is primary
and secondary school teachers in Malaysia. The study sample consisted of 600
respondents. The results of this study first show that there is a positive relationship
between job demands and burnout. Second, it shows that there is a negative relationship
between job resources and burnout. Third, it shows that there is a positive relationship
between job resources and work engagement. Fourth, this study shows that burnout
mediates the relationship between job resources and work engagement. The third previous
research that became a reference in this study was a study conducted by (Ivanovic,
Ivancevic, & Maricic, 2020) in Serbia entitled "The Relationship between Recruiter
Burnout, Work Engagement and Turnover Intention: Evidence from Serbia". The aim of
this study was to identify, understand and examine the relationship between burnout,
engagement, and turnover intention of job recruiters in Serbia. Data was collected using
an online questionnaire in a sample of 100 recruiters in Serbia. The results showed that
work engagement negatively affected burnout and burnout had a positive impact on
turnoverintention, while the relationship between work engagement and turnover
intention was not proven.
Based on the formulation of the problem, the purpose of this study is to analyze the
influence of:
1. Job resources for work engagement in public high school teachers in West
Kotawaringin
2. Job resources on job crafting for public high school teachers in West Kotawaringin
3. Job resources against burnout in public high school teachers in West Kotawaringin
4. Job crafting on work engagement for public high school teachers in West
Kotawaringin
5. Burnout of work engagement among public high school teachers in West
Kotawaringin
6. Job resources for work engagement through job crafting for public high school
teachers in West Kotawaringin
7. Job resources on work engagement through burnout of public high school teachers in
West Kotawaringin
Research Methods
Research Design
This study uses a type of causal research that aims to analyze the existence of causal
relationships between variables. (Moleong & Edisi, 2004) stated that causal research is
research conducted to determine the causal relationship between the variables being
studied. The method used in the research was a survey, namely by distributing
questionnaires to public high school teachers in West Kotawaringin.
Data Types and Sources
1. Data Type
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1512
This study uses quantitative data in the form of numerical numbers and analysis
using statistics. According to Martono in (Sudaryono & Surbakti, 2017), quantitative
research aims to describe social phenomena or symptoms quantitatively or analyze how
social phenomena or symptoms that occur in society are interconnected with one another.
2. Data Sources
A data source is anything that can provide information regarding data. Based on the
source, the data is divided into two, namely primary data and secondary data. The data
source used in this study is the primary data source. Explained that primary data is a data
source that directly provides data to data collectors. Primary data is also referred to as
original data that has an up to date nature. Techniques that can be used to collect primary
data are observation, interviews, and questionnaire distribution. The primary data used in
this study was collected directly from public high school teachers in West Kotawaringin
as respondents who will be distributed questionnaires on job resources, work engagement,
job crafting, and burnout.
3. Data Collection Methods
The tool used to collect data is a questionnaire. The questionnaire was distributed
directly to public high school teachers in West Kotawaringin who were willing to become
respondents. The questionnaire is a data collection tool carried out by giving respondents
a set of questions or written statements to answer. The questionnaire is distributed by
snowball sampling, where several subjects will be selected to represent the school and
then distributed the questionnaire to other teachers. Use the method of directly
distributing questionnaires to respondents in the following ways:
a. Questionnaires are distributed in the form of a google form
b. Respondents fill out questionnaires according to the instructions provided.
c. The completed questionnaire is collected and processed.
Population, Sample, and Sampling Techniques
1. Populasi
According to Sugiyono (2016: 80), population is a generalized area consisting of
objects/subjects with certain qualities and characteristics determined to be studied and
then conclusions are drawn. The population in this study is public high school teachers in
West Kotawaringin.
2. Sample
According to (Imperatori, 2017) samples are part of the number and characteristics
possessed by the population. According to (Hair Jr, Sarstedt, Hopkins, & Kuppelwieser,
2014), when using structural equation model (SEM) analysis, the minimum sample size
is 100 to 200. In this study, the sample size used was 166 people obtained from a total of
7 public high schools in West Kotawaringin.
Sampling Techniques
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1513
The sampling method in this study is non-random sampling with purposive
sampling techniques, which are sampling techniques that do not provide equal
opportunities for population members to be selected as samples based on certain
considerations. The sample criteria in this study are public high school teachers in West
Kotawaringin who have worked for at least one year.
Data Analysis
The data analysis technique used in this study is the Structural Equation Model
(SEM) with lisrel software. SEM is a statistical technique that can directly analyze the
pattern of relationships between latent constructs and indicators, latent constructs with
one another, and measurement errors.
1. Data Normality Test
According to Ghozali (2013: 110) the normality test aims to find out whether each
variable is normally distributed or not. Yamin and Kurniawan (2009: 29) said that data
normality consists of two types of output, namely:
2. Univariate normality
In univariate normality, data is said to be normally distributed if the p-values of chi-
square skewness and kurtosis are at least 0.05. Conversely, if the data is not normally
distributed, it is marked with a value of chi-square, Skewness, and Kurtosis less than 0.05.
3. Multivariate normality
In multivariate normality, data is said to be normally distributed if the p-values of
chi-square skewness and kurtosis are at least 0.05. Conversely, if the p-values of chi
square skewness and kurtosis are less than 0.05, then it can be said that the whole variable
is not normally distributed.
4. Validity Test
(Yamin & Kurniawan, 2009) said that validity aims to prove whether an indicator
can measure the latent variables used in research. In other words, the validity test is used
to measure the validity or validity of a questionnaire. The validity of the construct can be
measured through the statistical t-test approach of factor load provided that an indicator
is said to be valid if the t value of the factor charge is > 1.96.
5. Reliability Test
(Yamin & Kurniawan, 2009) said that reliability is used to obtain evidence that the
information or data used is reliable and able to reveal information in accordance with
reality. Reliability tests are performed with the Cronbach Alpha test. Cronbach's Alpha
formula is as follows:
Construct Reliability = (∑𝜆𝒾)2 (∑𝜆𝒾)2+𝛴ℯ 𝒾
According to (Yamin & Kurniawan, 2009), if the alpha value > 0.7, it means that
reliability is sufficient, while if alpha is >0.80, it suggests all reliable items and all tests
consistently internally because it has strong reliability.
6. Model Overall Fit Test
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1514
The overall fit test is used to test the research model used with data collected from
respondents. According to (Yamin & Kurniawan, 2009), several indicators can be used
to measure model testing, namely:
a. GFI (Goodness of Fit Index)
GFI is used to measure the ability of a model to explain data diversity. If the GFI
value is greater than or equal to 0.90, then it can be explained that the model has a good
fit feasibility.
b. AGFI (Adjusted Goodness of Fit Index)
AGFI is a modification of GFI by accommodating comparisons between free degree
models with other models. With test criteria: if the AGFI value is greater than or equal to
0.90 is good fit, while if the value is 0.80 ≤ AGFI < 0.90 is marginal fit.
c. NFI (Normed Fit Index)
NFI is the magnitude of the mismatch between the target and base models. With
test criteria: if the NFI value is greater than or equal to 0.90 is good fit, while if the value
is 0.80 ≤ NFI < 0.90 is marginal fit.
d. IFI (Incremental Fit Index)
The provision of value in IFI if IFI ≥ 0.9 is said to be a good fit, while if 0.8 ≤ IFI
< 0.9, then it is said to be a marginal fit.
e. CFI (Comparative Fit Index)
The test criteria: if the CFI value is greater than or equal to 0.90 is a good fit, while
if the value is 0.80 ≤ CFI < 0.90 is a marginal fit.
f. RFI (Relative Fit Index)
Its value ranges between 0 and 1. An RFI value of ≥ 0.9 is a good fit, while an RFI
value of 0.8 ≤ < 0.9 is a marginal fit.
g. RMSEA (Root Mean Square Error of Approximation)
RMSEA is used to measure the average difference per degree of freedom expected
in a population. With test criteria: if the RMSEA value is less than 0.08 is a good fit,
while if the RMSEA value is smaller than 0.05 is a close fit.
Structural Model Conformity Test
The structural model fit test is used to test the relationship between hypothesized
variables, that is, to find out whether the relationship coefficients between those variables
are statistically significant or insignificant. The test commonly used is a two-way test,
which uses a statistical t-value limit of 1.96. The coefficient of determination (R²)
explains how much the hypothesized exogenous variable in the equation can explain the
endogenous variable. A large R² value indicates that the exogenous variable can explain
the endogenous variable well.
Uji Hypoplant
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1515
This test is necessary to determine the significance of the results of Structural
Equation Modelling. The cut-off of a data is said to be significant if the test criterion is
1.96. According to (De Beer et al., 2016), if each parameter estimate has a t value greater
than 1.96, the relationship between variables is declared significant.
Results and Discussion
Normality Test
Normality testing uses two tests, namely univariate normality and multivariate
normality. Univariate normality is a normality test for each indicator and multivariate
normality is a normality test for all indicators that make up the research model. The
results of univariate normality testing are shown in the following table:
Table 1
Univariate Normality Table
No.
Variable
Skewness and Kurtosis
Information
Chi-Square
1.
JR1
42.451
Abnormal
2.
JR2
34.801
Abnormal
3.
JR3
39.013
Abnormal
4.
JR4
48.653
Normal
5.
JR5
19.014
Normal
6.
JR6
21.243
Normal
7.
JR7
33.843
Normal
8.
JC1
17.985
Normal
9.
JC2
23.196
Normal
10.
JC3
30.069
Abnormal
11.
JC4
62.399
Abnormal
12.
JC5
57.763
Normal
13.
JC6
50.224
Abnormal
14.
JC7
62.623
Normal
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1516
15.
JC8
14.461
Abnormal
16.
JC9
37.626
Abnormal
17.
JC10
45.611
Abnormal
18.
BO1
38.453
Normal
19.
BO2
42.394
Abnormal
20.
BO3
29.251
Abnormal
21.
BO4
18.002
Abnormal
22.
BO5
20.976
Abnormal
23.
BO6
41.913
Abnormal
24.
BO7
39.050
Abnormal
25.
BO8
18.012
Abnormal
26.
WE1
23.244
Normal
27.
WE2
22.727
Normal
28.
WE3
27.607
Abnormal
29.
WE4
21.849
Normal
30.
WE5
55.882
Normal
31.
WE6
34.957
Normal
32.
WE7
56.749
Normal
33.
WE8
63.659
Abnormal
34.
WE9
56.125
Normal
35.
WE10
39.849
Normal
36.
WE11
23.633
Normal
Source: Appendix 5, processed
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1517
Based on Table 1, it can be seen that univariately, the normality assumption in some
indicators is not fulfilled because the p-value is less than the set cut-off of 0.05. However,
half the indicators of the existing amount are already met because the p-value is more
than the cut off. Furthermore, to see the overall data declared normal or not, a multivariate
normality test can be used as a reference for normality.
Table 2
Multivariate Normality Table
Skewness
Kurtosis
Skewness and
Kurtosis
Value
Z-
Score
P-
Value
Value
Z-
Score
P-
Value
Chi-
Square
P-
Value
400.550
18.553
0.000
1469.737
9.252
0.000
429.815
0.000
Table 2 shows that the data are abnormally multivariate because the P-value of
skewness and kurtosis is less than 0.05, which is 0.000, but the analysis can still be
continued.
Validity Test
Validity Test is the level of reliability and validity of the tools used. The following
are the results of validity testing in this study:
Table 3
Validity Testing Results
Variable
Indicator
Factor
Loading
(T-Value)
Cut Off
Conclusion
Job
Resources
JR1
-
-
JR2
7,73
>1,96
Valid
JR3
7,87
>1,96
Valid
JR4
6,87
>1,96
Valid
JR5
7,08
>1,96
Valid
JR6
7,00
>1,96
Valid
JR7
6,14
>1,96
Valid
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1518
Job Crafting
JC1
-
-
JC2
6,64
>1,96
Valid
JC3
4,28
>1,96
Valid
JC4
8,54
>1,96
Valid
JC5
7,35
>1,96
Valid
JC6
8,82
>1,96
Valid
JC7
8,95
>1,96
Valid
JC8
6,18
>1,96
Valid
JC9
4,34
>1,96
Valid
JC10
5,00
>1,96
Valid
Burnout
BO1
-
-
BO2
16,18
>1,96
Valid
BO3
15,74
>1,96
Valid
BO4
15,57
>1,96
Valid
BO5
17,61
>1,96
Valid
BO6
16,55
>1,96
Valid
BO7
18,55
>1,96
Valid
BO8
15,35
>1,96
Valid
Work
Engagement
WE1
-
-
WE2
7,72
>1,96
Valid
WE3
11,76
>1,96
Valid
WE4
7,35
>1,96
Valid
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1519
WE5
6,56
>1,96
Valid
WE6
6,20
>1,96
Valid
WE7
7,97
>1,96
Valid
WE8
7,04
>1,96
Valid
WE9
6,93
>1,96
Valid
WE10
5,86
>1,96
Valid
WE11
7,13
>1,96
Valid
Based on Table 3 it can be seen that the data is valid because all indicators have a
loading factor greater than 1.96.
Reliability Test
Reliability tests are measured using the construct reliability formula as follows:
Construct reliability can be said to be reliable if the results exceed 0.7. The results
of the construct reliability calculation of each variable are shown in the following table:
Construct Reliability Variabel Job Resources (JR)
Table 4
Hasil Perhitungan Uji Construct Reliability Job Resources
Indikator
2
(1-2)
(Ʃ )2 +
Ʃ (1-2)
CR
Ket
JR1
0,74
0,5476
0,4524
JR2
0,68
0,4624
0,5376
JR3
0,61
0,3721
0,6279
JR4
0,68
0,4624
0,5376
JR5
0,65
0,4225
0,5775
JR6
0,72
0,5184
0,4816
JR7
0,68
0,4624
0,5376
JR
4,76
3,7522
3,7522
26,4098
0,857924
Reliabel
( JR)2
22,6576
Source: Appendix 7
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1520
From the calculation of construct realibility job resources in Table 4, it can be
concluded that the job resources variable is reliable because the reliability value shown is
0.85 where the value exceeds the cut off of >0.7.
Construct Reliability Variabel Job Crafting (JC)
Table 5
Job Crafting Construct Reliability Test Calculation Results
Indikator
2
(1-2)
(Ʃ )2 +
Ʃ (1-2)
CR
Ket
JC1
0,67
0,4489
0,5511
JC2
0,64
0,4096
0,5904
JC3
0,61
0,3721
0,6279
JC4
0,75
0,5625
0,4375
JC5
0,69
0,4761
0,5239
JC6
0,74
0,5476
0,4524
JC7
0,76
0,5776
0,4224
JC8
0,63
0,3969
0,6031
JC9
0,66
0,4356
0,5644
JC10
0,62
0,3844
0,6156
JC
6,77
5,3887
51,2216
0,894796
Reliabel
( JC)2
45,8329
From the calculation of construct realibility job crafting in Table 5 it can be
concluded that the job crafting variable is reliable because the reliability value shown is
0.89 where the value exceeds the cut off which is >0.7.
Construct Reliability Variabel Burnout (BO)
Table 6
Construct Reliability Burnout Test Calculation Results
Indikator
2
(1-2)
(Ʃ )2 +
Ʃ (1-2)
CR
Ket
BO1
0,85
0,7225
0,2775
BO2
0,86
0,7396
0,2604
BO3
0,91
0,8281
0,1719
BO4
0,89
0,7921
0,2079
BO5
0,89
0,7921
0,2079
BO6
0,89
0,7921
0,2079
BO7
0,88
0,7744
0,2256
BO8
0,89
0,7921
0,2079
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1521
BO
7,06
1,767
51.6106
0,965763
Realiabel
( BO)2
49,8436
From the calculation of construct realibility burnout in Table 6, it can be concluded
that the burnout variable is reliable because the reliability value shown is 0.96 where the
value exceeds the cut off of >0.7.
Construct Reliability Variabel Work Engagement (WE)
Table 7
Work Engagement Construct Reliability Test Calculation Results
Indikator
2
(1-2)
(Ʃ )2 +
Ʃ (1-2)
CR
Ket
WE1
0,79
0,6241
0,3759
WE2
0,68
0,4624
0,5376
WE3
0,76
0,5776
0,4224
WE4
0,63
0,3969
0,6031
WE5
0,71
0,5041
0,4959
WE6
0,73
0,5329
0,4671
WE7
0,76
0,5776
0,4224
WE8
0,77
0,5929
0,4071
WE9
0,75
0,5625
0,4375
WE10
0,73
0,5329
0,4671
WE11
0,63
0,3969
0,6031
WE
7,94
5,2392
68.2828
0,923272
Reliabel
( WE)2
63,0436
From the calculation of construct realibility work engagement in Table 7, it can be
concluded that the burnout variable is reliable because the reliability value shown is 0.93
where the value exceeds the cut-off of >0.7.
Uji Model
A model-wide fit test is a test performed to analyze a model's fit to data. The
following are the results of the fit test of the entire model in this study.
Table 8
Model Conformity Test
Goodness Of Fit
Index
Cut Off Value
Result
Information
Chi Square
867,46
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1522
Significance
Probability
≥ 0,05
0,000
Not Fit
RMSEA
≤ 0,08
0,054
Good Fit
NFI
≥ 0,90
0,95
Good Fit
SMOKE
≥ 0,90
0,98
Good Fit
RFI
≥ 0,90
0,95
Good Fit
CMIN/DF
≤ 2,83
1,87
Good Fit
CFI
≥ 0,95
0,98
Good Fit
Judging from table 8 above, it can be concluded that the model used in this study
as a whole can be said to be suitable because the value of the model fit test indicator is
met, there are only three indicators that are not met.
Uji Hypoplant
Table 9
Research Hypothesis Test Results
Hipotesis
Variable
T-Value
Cut Off
Information
H1
Job Resources → Work
Engagement
7,80
>1.96
Significant
H2
Job Resources → Job
Crafting
8,85
>1.96
Significant
H3
Job Resources →
Burnout
-3,74
>1.96
Significant
H4
Job Crafting → Work
Engagement
1,06
>1.96
Insignificant
H5
Burnout → Work
Engagement
-2,30
>1.96
Significant
H6
Job Resources → Job
Crafting → Work
Engagement
7,79
>1.96
Significant
H7
Job Resources →
Burnout
→ Work Engagement
2,49
>1.96
Significant
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1523
The significance test criterion with the T-Table was 1.96. The positive direction if
the T-Value > 1.96 then significant and the negative direction if - T Value < -1.96 then
significant. Based on Table 4.17, the results of hypothesis testing can be explained as
follows:
1. Job Resources (JR) have a positive and significant effect on Work Engagement (WE).
This influence is evidenced by a t-value of 7.80 (t-value > 1.96).
2. Job Resources (JR) has a positive and significant effect on Job Crafting (JC). This
influence is evidenced by a t-value of 8.85 (t-value > 1.96).
3. Job Resources (JR) negatively and significantly affect Burnout (BO). This influence
is evidenced by a t-value of -3.74 (t-value < -1.96).
4. Job Crafting (JC) has a positive effect on Work Engagement (WE). This effect is not
significant, as evidenced by a t-value of 1.06 (t-value < 1.96).
5. Burnout (BO) has a negative and significant effect on Work Engagement (WE). This
effect is evidenced by a t-value of -2.30 (t-value < -1.96).
6. Job Resources (JR) has a positive and significant effect on Work Engagement (WE)
through Job Crafting (JC). This influence is evidenced by a t-value of 7.79 (t-value
>1.96).
7. Job Resources (JR) have a positive and significant effect on Work Engagement (WE)
through Burnout (BO). This influence is evidenced by a t-value of 2.49 (t-value >
1.96).
The Effect of Job Resources on Work Engagement
Judging from the statistical results, it is stated that the effect of job resources on
work engagement is positive. Test the hypothesis that job resources have a positive effect
on work engagement in State High School teachers in West Kotawaringin is proven by a
t-value of 7.80 (more than the cut off of 1.96). This proves the influence of job resources
on work engagement.
Based on respondents' answers obtained from public high school teachers in West
Kotawaringin, it can be seen through descriptive statistics that the job resources variable
has an average value of 4.19. The average value proves that respondents agree on the job
resources variable which has seven indicators. The most widely agreed indicator is about
how to receive sufficient information about the goals and results of the work of the
respondents. While the indicator that is less agreed is how respondents have freedom in
carrying out their work activities. The average value of the work engagement variable is
4.15. The average value also proves that respondents agree with the measurement of work
engagement variables which have 11 indicators.
It can be concluded that when the dimensions in job resources are fulfilled in a
worker, it will increase the work engagement of the worker. The fulfillment of factors in
job resources such as freedom in doing work, feedback that is always given to employees,
getting clear information about their work and the existence of a good relationship
between employees and superiors will make employees more attached to their company
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1524
because they feel positive in their work and do not feel burdensome about their work. The
better or more fulfilled job resources in employees, the higher their attachment to the
organization or company.
The results of this study are supported by research conducted by (Kotze, 2018)
which proves that job resources affect work engagement in employees of private
companies in Korea. Another study conducted by Kunte & Rungruang (2018) on
employees of various industries in Thailand also confirmed that job resources have a
positive influence on work engagement. Studies say that job resources such as perceived
organizational and social support, autonomy, and good relationships with management
have also been shown to increase job engagement
The Effect of Job Resources on Job Crafting
Judging from the statistical results, it is stated that the influence of job resources on
job crafting is positive. Test the hypothesis that job resources have a positive effect on
job crafting in State High School teachers in West Kotawaringin is proven by a t-value of
8.85 (greater than the cut off of 1.96). This proves the influence of job resources on job
crafting.
Based on respondents' answers obtained from public high school teachers in West
Kotawaringin, it can be seen through descriptive statistics that the job crafting variable
has an average value of 4.16. The average value proves that respondents agree on the job
crafting variable which has ten indicators. Of the 10 existing indicators, there are several
indicators with the highest agreed value. It can be concluded that teachers feel they can
improve themselves about the importance of their work for the success of organizations
and communities, teachers can prioritize work that matches their respective skills or
interests and teachers think about how their work positively impacts their lives. Based on
answers on job resources variables, respondents answered in agreement on each indicator.
However, the indicator with the lowest level of approval in the job resources variable is
how respondents have freedom in carrying out their work activities. This means that there
is not much freedom that teachers can do in their work.
The results of this study are supported by research conducted by (Kotze, 2018) on
employees of private companies in Korea proving that job resources have a positive and
significant effect on job crafting. Job autonomy is one dimension in job resources where
each indicator discusses how a worker has freedom in doing his job and can decide for
himself how his work is carried out.
The Effect of Job Resources on Burnout
Judging from the statistical results, it is stated that the effect of job resources on
burnout is negative. The hypothesis test stating that job resources negatively affect
burnout in State High School teachers in West Kotawaringin is proven by a t-value of -
3.74 (less than the cut-off of -1.96). This proves the negative influence of job resources
on burnout.
Based on respondents' answers to the burnout variable, respondents answered
disagree on each indicator. The indicator that had the highest level of disapproval was
that teachers felt emotionally drained because of their work. Judging from respondents'
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1525
answers to the job resources variable, respondents on average answered in agreement on
each indicator. Based on questionnaires on job resources variables, each teacher feels they
have freedom in doing work activities, each teacher has an influence in planning activities
and work speed, each teacher can decide for himself the content of his work activities,
each teacher receives enough information about the goals and results of their work, each
teacher feels that their work gives direct feedback on how well they do their job, Every
teacher feels that their boss tells them how good they are at doing and every teacher has
colleagues telling them about how good they are at doing their job. What the teachers feel
proves that the job resources in the teachers have been fulfilled, so that the teachers do
not feel fatigue in themselves. Teachers don't feel emotionally drained from work, don't
feel physical fatigue at the end of the workday, don't feel lethargic when they wake up in
the morning because they have another day at work, don't feel pressured when working
with people all day and don't feel tired and frustrated because of work.
The Effect of Job Crafting on Work Engagement
Based on respondents' research obtained on job crafting in public high school
teachers in West Kotawaringin, it can be seen that the average respondent answered in
agreement on the job crafting variable which has 10 indicators. The most widely agreed
indicator is that respondents prioritize jobs that match their skills or interests and they
think about how their work can have a positive impact on their lives. The indicator with
the lowest level of approval was about how respondents could change the scope or type
of tasks they completed at work. This means that respondents cannot easily change how
they work or the types of tasks they perform, such as changes in the way they teach, which
is basically teaching in the classroom.
Judging from the statistical results, it is stated that the effect of job crafting on
work engagement is positive. The hypothesis test stating that job crafting has a positive
effect on work engagement in State High School teachers in West Kotawaringin is not
proven with a t-value of 1.06 (less than the cut off of 1.96). This proves the absence of
the influence of job crafting on work engagement.
When viewed from the results of respondents' answers in this study, from the three
dimensions in job crafting, namely task crafting, relational crafting, and cognitive
crafting, then in this study the respondents felt that what they could do in job crafting was
how they could change their perspective or their perspective on their work, Judging from
the value of the most widely agreed indicator, they are able to think that their work can
have a positive impact on their lives. If teachers can only change the way they view work,
but cannot change in detail how their work matches what they expect, for them it has not
been able to increase their engagement in accordance with the results of respondents'
answers the indicator with the lowest level of approval is about how teachers can change
the scope or type of their tasks. When viewed at the level, high school teachers may not
have many ways to teach their students because students will also understand the simple
learning process. Unlike if the research is conducted at the elementary school (SD) level,
teachers can be required to be more creative in teaching because elementary students will
more easily understand the lesson in certain ways. Teachers already have standards in the
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1526
teaching and learning process, only the way of delivering the material can vary. If teachers
can be more free to express themselves in the delivery of learning materials, it will be
easier to increase work engagement.
How Burnout Affects Work Engagement
Based on respondents' answers obtained from public high school teachers in West
Kotawaringin, it can be seen through descriptive statistics that the burnout variable has
an average value of 2.51. The average value proves respondents disagree on the burnout
variable, with 8 indicators. The indicator with the highest disapproval level was that
teachers felt emotionally drained because of their work. The indicator with the lowest
level of disapproval was related to how they felt others at work blamed them for the
problem.
Negative influence means that when a worker or teacher has a low burnout rate,
their engagement will be higher. But on the contrary, if teachers feel very high burnout in
their work, their engagement will be lower. Judging from the respondents' answers in this
study, it can be concluded that teachers feel low burnout. This can be seen from the
answers of respondents who disagreed on all indicators in the burnout variable. Teachers
do not feel high emotions in their work; teachers do not feel excessive physical fatigue
when work hours are over, teachers do not feel lethargic when they have to get up early
and have a new day again to work; teachers do not feel pressure to work with people
around them, teachers do not feel frustrated because of their work, teachers do not feel
that their lives and careers will not change and teachers do not think that people in their
workplaces blame them when things go wrong.
The Effect of Job Resources on Work Engagement through Job Crafting
Judging from the statistical results, it is stated that the influence of job resources
on work engagement through job crafting is positive. Test the hypothesis that job
resources positively affect work engagement through job crafting in State High School
teachers in West Kotawaringin is proven by a t-value of 7.79 (more than the cut-off of
1.96). This demonstrates the influence of job resources on work engagement through job
crafting.
Judging from the respondents' answers to the variable of job resources who agreed
there is freedom in carrying out work activities and can decide the content of work
activities, teachers can do job crafting in doing their work. So, when the freedom to
change the scope is allowed, it will increase teachers' work engagement. Although in the
variable of job crafting, the teachers agree that they can only change the way they view
the work rather than have the freedom to change the scope of work, the teachers still agree
that there is an opportunity for them to change the scope of work.
The Effect of Job Resources on Work Engagement through Burnout
Judging from the statistical results, it is stated that the effect of job resources on
work engagement through burnout is positive. Test the hypothesis that job resources
positively impact work engagement through burnout in State High School teachers in
West Kotawaringin is proven by a t-value of 2.49 (more than the cut off of 1.96). This
demonstrates the influence of job resources on work engagement through burnout.
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1527
The results of this study are supported by research conducted (Jimenez & Dunkl,
2017), proving that burnout mediates the relationship between job resources and work
engagement. The results of research conducted by (Barkhowa, 2020) on manufacturing
industry employees in Salatiga also prove that job resources affect work engagement
through burnout as an intervening variable. (Barkhowa, 2020) wrote in the results of his
research that in the variable of job resources, research respondents felt that they had the
opportunity to develop careers in the company, had good communication between
colleagues in the company, felt that all the information needed by employees in helping
complete responsibility tasks was always in the company, getting support from superiors,
having groups in the work environment positively; All employees always participate in
decision making, and the type of work done by employees in the company is very varied.
If this is fulfilled by employees, it can affect burnout because respondents feel always
excited at work and they feel not tired when doing work. When employees are enthusiastic
in doing their work, it will increase work engagement because employees have high
energy while working, feel excited and enthusiastic when doing their work, where all
feelings of enthusiasm arise when what is needed in job resources has been obtained by
employees in their work.
Conclusion
Based on the analysis and discussion, it can be concluded that Job Resources (JR)
has a positive and significant effect on Work Engagement (WE), Job Crafting (JC), and
a negative impact on Burnout (BO) in public high school teachers in West Kotawaringin.
However, Job Crafting (JC) does not positively affect Work Engagement (WE) and
Burnout (BO) negatively affects Work Engagement (WE). In addition, Job Resources
(JR) also positively affects Work Engagement (WE) through Job Crafting (JC) and
through Burnout (BO).
Yenni Lawrensia, Tuty Lindawati
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1528
Bibliography
Aldrin, Neil, & Merdiaty, Netty. (2019). Effect of job crafting on work engagement with
mindfulness as a mediator. Cogent Psychology, 6(1), 1684421.
https://doi.org/10.1080/23311908.2019.1684421
Barkhowa, Mokhammad Khukaim. (2020). Pengaruh Job Resources Terhadap Work
Engagement Melalui Burnout Karyawan Industri Manufaktur di Salatiga. Fokus
Ekonomi: Jurnal Ilmiah Ekonomi, 15(1), 241–261.
https://doi.org/10.34152/fe.15.1.241-261
De Beer, Leon T., Tims, Maria, & Bakker, Arnold B. (2016). Job crafting and its impact
on work engagement and job satisfaction in mining and manufacturing. South
African Journal of Economic and Management Sciences, 19(3), 400–412.
Hair Jr, Joe F., Sarstedt, Marko, Hopkins, Lucas, & Kuppelwieser, Volker G. (2014).
Partial least squares structural equation modeling (PLS-SEM): An emerging tool in
business research. European Business Review, 26(2), 106–121.
Imperatori, Barbara. (2017). Engagement and disengagement at work: Drivers and
organizational practices to sustain employee passion and performance. Springer.
Ivanovic, Tatjana, Ivancevic, Sonja, & Maricic, Milica. (2020). The relationship between
recruiter burnout, work engagement and turnover intention: Evidence from Serbia.
Engineering Economics, 31(2), 197–210.
Jiménez, Paul, Bregenzer, Anita, Kallus, K. Wolfgang, Fruhwirth, Bianca, & Wagner-
Hartl, Verena. (2017). Enhancing resources at the workplace with health-promoting
leadership. International Journal of Environmental Research and Public Health,
14(10), 1264.
Jimenez, Paul, & Dunkl, Anita. (2017). The buffering effect of workplace resources on
the relationship between the areas of worklife and burnout. Frontiers in Psychology,
8, 234160.
Jiménez, Paul, Winkler, Bianca, & Dunkl, Anita. (2017). Creating a healthy working
environment with leadership: the concept of health-promoting leadership. The
International Journal of Human Resource Management, 28(17), 2430–2448.
Kotze, Martina. (2018). How job resources and personal resources influence work
engagement and burnout. African Journal of Economic and Management Studies,
9(2), 148–164.
Moleong, Lexi J., & Edisi, PRRB. (2004). Metodelogi penelitian. Bandung: Penerbit
Remaja Rosdakarya, 3(01).
Rifa’i, Muhammad, Ananda, Rusydi, & Fadhli, Muhammad. (2018). Manajemen peserta
didik (Pengelolaan peserta didik untuk efektivitas pembelajaran).
The Effect of Job Resources on Work Engagement through Job Crafting and Burnout in Public
High School Teachers in West Kotawaringin
Indonesian Journal of Social Technology, Vol. 5, No. 4, April, 2024 1529
Sudaryono, Sudaryono, & Surbakti, Natangsa. (2017). Hukum Pidana Dasar-Dasar
Hukum Pidana Berdasarkan KUHP dan RUU KUHP.
Yamin, Sofyan, & Kurniawan, Heri. (2009). SPSS complete: Teknik analisis statistik
terlengkap dengan software SPSS. Jakarta: Salemba Infotek, 328.