Volume 2, Issue 5, August 2021 E-ISSN : 2715-4203, P-ISSN : 2715-419X
Available Online: https://dinastipub.org/DIJDBM Page 822
DOI: https://doi.org/10.31933/dijdbm.v2i5
Received: 15 August 2021, Revised: 10 September 2021, Publish: 28 September 2021
THE EFFECT OF COMPENSATION AND PERFORMANCE
ASSESSMENT ON EMPLOYEE SATISFACTION THROUGH
COMPETENCY AS A MEDIATION VARIABLE (CASE STUDY AT
PT. VINDO INTERNATIONAL)
Setiyo Purwanto
1
, Didin Hikmah Perkasa
2
1)
Universitas Dian Nusantara, Indonesia, [email protected]
2)
Universitas Dian Nusantara, Indonesia, [email protected]
Corresponding Author: First Author
Abstract: This research was conducted on the plastic manufacturing industry during the covid-19
pandemic. The purpose of this study was to examine the effect of compensation and performance
appraisal on employee job satisfaction through competence as a mediating variable. The data in the
study consisted of 150 populations and 109 samples in the study were employees of PT. Vindo
International. Data analysis in this study used quantitative methods with the SmartPLS 3.0 test tool.
Financial and non-financial compensation is part of the company's motivation to reward performance
achievements. Providing appropriate compensation can provide employee job satisfaction and can
trigger better performance. So that in the construction of this research a synergistic relationship is
built in the provision of compensation accompanied by performance appraisals based on employee
competencies, this will provide employee job satisfaction. Employee job satisfaction has an impact
on performance, loyalty and awareness. All of this will shape the organizational culture to achieve
company goals. The findings in this study are performance appraisals that are not based on employee
competence can lead to individual subjectivity, this does not provide job satisfaction.
Keywords: Compensation, Performance Appraisal, Job Satisfaction, Competence.
INTRODUCTION
During the COVID-19 pandemic since March 2020, it is a difficult time for most
industries to survive. Companies must rationalize costs by cutting various expenses (production
bonuses, attendance incentives and achievement bonuses) as well as reducing employees
significantly due to the effect of PSBB (Large-Scale Social Restrictions). This really paralyzes
the business sector from small, medium to large scale. However, in any bad condition, the
company must keep trying to survive by mobilizing various resources as well as doing a shifting
strategy to rearrange organizational resources. Based on the study of human resource
management literature according to D. Kenelak et.al (2016), explaining that, compensation given
to employees can encourage work morale, there is a perceived satisfaction so that the
performance output increases. However, the provision of compensation can not only motivate or
provide employee job satisfaction. The provision of compensation that does not meet the
principle of justice will be able to reduce motivation and job satisfaction, Aamir, Alemzeb
(2012). Maheswari's research (2017) concludes that financial compensation has an effect on
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performance, but non-financial compensation has no effect on performance. In contrast to the
results of Firmandari (2014) research which states that compensation in the form of bonuses
does not have a significant effect on performance. Based on this research, it is important to give
compensation to employees to revive morale, but there is a research gap where there must be an
appropriate way of giving compensation.
Performance appraisal is also one of the performance measurement tools to place
individual achievements at a certain grade/level as a form of corporate appreciation. This
assessment is based on established regulations, by comparing the targets (work results) with the
job description requirements, namely the work standards that have been set for a certain period,
Widodo and Sami'an (2012:1). According to Rizal et al. (2013), the results of the performance
appraisal will be a separate note in providing an assessment of each employee on the results
(output) in terms of quality and quantity achieved. Assessment of employee performance in
carrying out their duties does not always lead to job satisfaction for employees, there needs to be
an alignment of tasks and employee abilities to achieve organizational goals, Mangkunegara
(2015). Employee job satisfaction is a phenomenon that needs to be observed by organizational
leaders. Someone who is satisfied will have high motivation, commitment to the organization
and work participation, which in turn will improve his performance, Sinambela (2012).
Observing the existence of several inconsistencies in the findings of the research
above, it encourages researchers to fill the research gap with competency variables as a
mediating variable for compensation and performance appraisal on employee job satisfaction.
According to Wibowo (2012: 323) explains that the competence of human resources will
improve company performance and create organizational culture. Fiqri Surikha (2016) asserts
that a person's competence is a reflection of employee professionalism as evidenced by the
achievement of organizational performance. So that employee competencies can be used as
standardization of employee performance appraisals in an effort to get compensation that must be
given by the company.
Problem Formulation
Problems related to employee job satisfaction can be described as follows:
1. Whether compensation affect employee job satisfaction?
2. Whether Compensation affect Competence?
3. Whether Performance Appraisal affect Employee Job Satisfaction?
4. Whether Performance Assessment affect Competence?
5. Whether competency mediation affect employee job satisfaction?
6. Whether Compensation as measured through Competence affect Employee Job
Satisfaction?
7. Whether Performance Assessment as measured by Competence affect Employee Job
Satisfaction?
Research Benefits
Practical Benefits, making a positive contribution to the industry related to the effect
of compensation and performance appraisal based on competence on employee job
satisfaction so that they can further improve their performance in the future.
Theoretical benefits, add insight for academics related to Human Resource
Management and provide references for academics who will conduct similar research or as a
basis for developing research.
LITERATURE REVIEW
Compensation
Panggabean (2010) suggests that compensation is any form of award given to
employees as a reward for the contributions they make to the organization. According to
Rivai (2012), compensation is something that employees receive as a substitute for their
service contribution to the company. Furthermore, the researcher Sikula (in Mangkunegara,
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2012) explains that compensation is a gift or gift as a comparable award. Sihotang (2012),
added that compensation is an arrangement for providing remuneration, both financial and
non-financial to each entitled employee.
The dimensions of compensation according to Hasibuan (2012) are explained, among
others; Wages are usually related to the hourly rate of pay (more over time will be piad
more). While the salary generally applies to weekly, monthly or yearly rates. Incentives are
additional salaries beyond the normative salary provided by the organization. Incentive
programs are tailored to productivity, sales, benefits or cost-cutting efforts. Benefits, such as
health insurance, life insurance, company-borne holidays, pension plans and other benefits
related to employment. Facilities is a pleasure as company car, club membership, dedicated
parking.
Performance Assessment
Moeheriono (2012: 69) explains that, performance appraisal is a measure of work
performance that has been achieved by an employee. According to Widodo in Sami'an
(2012:1) it is emphasized that, performance appraisal aims to measure employee
performance based on regulations that have been set by the company. Mondy and Noe in
Sami'an (2012:2) add that a formal system is regularly used to evaluate individual
performance in carrying out their duties. Junuari (2015) revealed that performance appraisal
has a big influence on employee job satisfaction.
Competence
Competence of employees is needed in doing certain jobs. Employees who lack the
ability or have low competence will find it difficult to do a job, lowering the quality and
even hindering the completion of the work. Klarner, et al., 2013 have revealed that, it is very
necessary for human resources who have adequate competence because competence is a key
factor in improving employee performance. Yunus, 2012 and Rudlia, 2016 revealed that
employee performance is strongly influenced by competence. Competence is something that
is measurable, can be observed, predicted, and evaluated which is reflected in one's work
behavior. Competence consists of a combination of knowledge (knowledge), skills, and
attitudes. There are 5 dimensions of individual competence according to Moeheriono
(2009), including; Task-skills; Task management skills; Contingency management skills;
Job role environment skills; Transfer skills.
Job Satisfaction
Job satisfaction according to Mangkunegara (2013: 117) is a feeling that supports
individual employees related to work. In addition, Mila Badriyah (2015) argues that job
satisfaction is an employee's attitude or feeling towards pleasant or otherwise aspects of
work.
1. Relationship of Compensation to Job Satisfaction
In a study conducted by Tett and Meyer in Sutanto and Gunawan (2013) stated that the
desire to leave employees is based on an awareness of dissatisfaction with the
compensation provided, so there is a desire to find alternative jobs in other organizations.
This result is in line with previous findings by Yucel, (2012) which states that in his
research, there is a negative effect of job satisfaction on the desire to leave. This means
that if employees are satisfied with the compensation received, they are less likely to
leave work. So that compensation can be used as a way to build employee job
satisfaction. This research is reinforced by Sofyandi's theory (2013:162) that the purpose
of compensation is to provide satisfaction to employees. In addition, T. Retnoningsih,
B.S Sunuharjo, I. Ruhana, (2016) proved that non-financial compensation has a
significant effect on employee job satisfaction. Based on the construct of the
relationship, the researcher formulated hypothesis 1 as follows:
H1: Compensation Affects Job Satisfaction
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2. Relationship of Compensation to Competence
According to Septerina and Rusda Irawati (2018), financial and non-financial
compensation will improve employee work performance. Another opinion also states
that the importance of employee competence as a standardization of individual abilities
in providing appropriate compensation, Yunus (2012); Klarner, et al., (2013); Rudlia
(2016). So that researchers arrange H2 as follows:
H2: Compensation Affects Competence
3. The Relationship between Performance Assessment and Job Satisfaction
Hasibuan, (2005:88) argues that, performance appraisal is an effort used by companies to
assess employees carrying out their job duties. The results of this study strengthen the
research of January, Utami, Ruhana (2015) which argues that performance appraisal has
an effect on job satisfaction, even further explained that the better the implementation of
performance appraisal, the higher job satisfaction. Andari, Nafiudin (2019) explained
that performance appraisal has a positive effect on employee job satisfaction. Based on
the construct of the relationship, the researcher formulated hypothesis 3 as follows:
H3: Performance Assessment Affects Job Satisfaction
4. Relationship between Performance Assessment and Competence
According to Hasibuan (2011) in his research explains that, performance appraisal based
on individual competence is a measure for companies to select employees based on the
required competencies. This research supports Wibowo (2014), which suggests the role
of competence in the basis of performance appraisal because individual competence is
the ability to carry out a job that is based on skills and knowledge and is supported by a
good work attitude. Competence also describes skills and professionalism in a particular
field as an advantage in their field. These results are in line with previous research
conducted by Supatmi, Nimran, & Utami, (2013), where it has been explained that job
measurement is carried out as an effort to determine the level of employee performance
in accordance with individual competencies. Based on the construct of the relationship,
the researcher formulated hypothesis 4 as follows:
H4: Performance Assessment Affects Competence
5. The Relationship of Competence to Job Satisfaction
Measurement of individual competence value as the basis for initial compensation to be
given by the company to provide satisfaction, Mathis and Jackson (2002:81). Dessler,
(2004:70) also adds that the measurement of competence is equivalent to a person's
knowledge, expertise, skills, and ability to do work. Based on the construct of the
relationship, the researcher formulated hypothesis 5 as follows:
H5: Competence Affects Job Satisfaction.
6. Relationship of Compensation to Job Satisfaction through Competence
Dessler (2004:65) says that employee compensation is "Any form of payment or reward
given to employees for their work". Giving awards must be adjusted to their competence
to be able to motivate themselves to improve company performance, Rizwan (2014).
Previous research conducted by Rahayu and Riana (2017) also argues that compensation
given in accordance with their respective competencies has a positive and significant
effect on job satisfaction, thereby reducing the desire to leave work. In another study also
mentioned, the key to the success of a business organization is to increase the job
satisfaction of its employees. Based on the results of research by Septerina and Rusda
Irawati (2018), financial and non-financial compensation in accordance with individual
competencies will provide employee job satisfaction. The results of this study are in
accordance with research that has been carried out by several previous studies, namely:
Nazir et al. (2013); Adeoye and Fields (2014); Rood and Holdnak (2013); Salisu et al.
(2015); and Muguongo et al. (2015), who concluded that compensation in accordance
with their competence has a positive and significant effect on job satisfaction. Another
opinion is also in accordance with this study which states that the importance of
employee competence as a standardization of individual abilities in providing
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appropriate compensation, so that job satisfaction can be fulfilled, Yunus (2012);
Klarner, et al., (2013); Rudlia (2016). Based on this research, the researcher formulated
hypothesis 6 as follows:
H6: Compensation Measured Through Competence Affects Job Satisfaction
7. The Relationship between Performance Assessment and Job Satisfaction through
Competence
According to Wibowo (2014) argues that, the role of competence in underpinning
performance appraisal because individual competence is the ability to carry out a job based
on skills and knowledge and supported by a good work attitude. These results are in line
with the research of Supatmi, Nimran, & Utami, (2013) which explains that, job
measurement is carried out as an effort to determine the level of employee performance in
accordance with individual competencies as the basis for providing compensation to meet
employee job satisfaction. Based on the construct of the relationship, the researcher
formulated hypothesis 7 as follows:
H7: Performance Assessment Measured Through Competence Affects Job Satisfaction
Figure 2.1 Research Model Construct
RESEARCH METHOD
The time of the research will be carried out in October to December 2020, as for the location
of the object of research, namely: PT. Vindo International, Jl. Greater Industry III Block AD
no. 18 Bunder Village, Cikupa District, Tangerang Regency 15710 Banten-Indonesia. This
study is a descriptive study, which explains the relationship of compensation, performance
appraisal and competence to employee job satisfaction with a total population of 150
employees.
Sample
The sample is part of the population that is used as the actual data source. In other words,
the sample is part of the population. The sample is part of the number and characteristics
possessed by the population, Sugiyono (2009: 116). Determination of the sample size to be
taken in this study using the Slovin formula, Sanusi (2011:101). The Slovin formula for
determining the sample is as follows:
N
n =
1+N (e)
2
Job
Satisfaction
(Y1)
Competence
(M1)
Performance
Assessment
(X2)
Compensation
(X1)
H5
H6= X1----- M1 ----- Y1
H7= X2----- M1 ----- Y1
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Information:
n = Sample size/number of respondents
N = Population size
e = Percentage of allowance for accuracy of sampling error that can still be tolerated; e =
0.05. So the calculation of the research sample can be calculated as follows:
n = 150
1+(150(0,05)
2
)
n = 150
1,375
n = 109
Data Collection Techniques
Data collection techniques carried out by researchers by distributing questionnaires to all
employees to determine the effect of compensation and performance appraisal on employee
job satisfaction mediated by competence.
Data Analysis Method
1. Descriptive analysis.
Descriptive analysis is used to describe and describe the variables used in this study
(Sugiyono, 2017). Descriptive analysis was carried out using descriptive statistics that
produced the average, maximum, minimum and standard deviation values to describe the
research variables so that they were contextually easy to understand.
2. Partial Least Square Analysis
This model is used to determine the validity and reliability of linking indicators with
latent variables. The indicators in this study are reflective because the indicators of latent
variables affect the indicators, for this reason, 3 methods of measurement are used,
Sofyan Yamin (2009), namely:
3. Convergent Validity
Convergent Validity measures the magnitude of the correlation between the construct
and the latent variable. In evaluating convergent validity from checking individual item
reliability, it can be seen from the standardized loading factor. The standardize loading
factor describes the magnitude of the correlation between each measurement item
(indicator) and its construct. The correlation can be said to be valid if it has a value > 0.5.
4. Discriminant Validity
The next evaluation is to see and compare between discriminant validity and square root
of average variance extracted (AVE). The measurement model was assessed based on the
measurement of cross loading with the construct. If the correlation of the construct with
each indicator is greater than the size of the other constructs, then the latent construct
predicts the indicator better than the other constructs. If the AVE value is higher than the
correlation value between the constructs, then good discriminant validity is achieved.
According to Tasha Hoover (2005) in Sofyan Yamin (2011), it is highly recommended if
the AVE is greater than 0.5. Here's the formula for calculating AVE:
Σλᵢ₂
AVE =
Σλᵢ² ₊ Σ₁ ᵥₐᵣ₍ ԑᵢ₎
Where λi is the loading factor (convergent validity), and i= 1 - i2. Stating that this
measurement can be used to measure reliability and the results are more conservative
than the composite reliability value (ρс) Fornnel and Larcker in Ghozali (2014).
5. Composite Reliability
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To determine composite reliability, if the composite reliability value > 0.7 it can be said that
the construct has high reliability or reliable and > 0.6 is said to be quite reliable Chin in
Sofyan Yamin (2011). The following is the formula for calculating composite reliability:
(Σλᵢ)²
ρс =
(Σλᵢ)² + Σ₁ ᵥₐᵣ₍ ԑᵢ₎
In PLS, the reliability test is strengthened by the presence of Cronbach alpha where the
consistency of each answer is tested. Cronbach alpha is said to be good if 0.7.
3.4 Hypothesis Testing
Based on the research objectives, the hypothesis test design that can be made is a hypothesis
test design in this study which is presented based on the research objectives. The level of
confidence used is 95%, so the level of precision or the limit of inaccuracy is (α) = 5% =
0.05. And produce a t-table value of 1.96. So, if the value of t-statistics is smaller than the
value of t-table [t-statistics < 1.96], then Ho 0.5 is accepted and Ha is rejected. If the value
of t-statistics is greater than or equal to t-table [t-statistics > 1.96], then Ho is rejected and
Ha is accepted.
RESULTS AND DISCUSSION
Description of Research Object
PT. Vindo International which has been established since 2007, is a plastic manufacturing
company that has main business houseware equipment, oriented to the export and the
domestic market. As an export-oriented company and has become a member of the Europe
Sedex standardization where this standard is very concerned with employee welfare, the
company is very concerned about the rights of employees as regulated in the Labor Law to
ensure employee job satisfaction. Employees for the company are seen as very valuable
assets, because no matter how great a management system and technology that is
built/applied by the company, it will not achieve optimal performance without the important
role of reliable human resources, Wibowo (2012:323); Suharti, 2012:39). Of the total
number of questionnaires distributed and sent, namely 150 questionnaires, the total number
of questionnaires filled out and returned was 148 questionnaires.
Table 4.1 List of questionnaires
Questionnaire Quantity
Questionnaire distributed 150
Questionnaire wasn’t returned 2
Incomplete Questionnaire 39
Appropriate questionnaire used for input purposes 109
Source: primary data processed 2020
Table 4.2 Respondent Profile
Information Total Percentage
Total sample 109 100%
Gender:
Male 24 22 %
Female 85 78 %
Age:
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21 – 25 years old 29 26,6 %
26 – 30 years old 58 53,2 %
31 – 50 years old 22 20,2 %
Source: primary data processed, 2021
Based on table 4.2, it is known that the number of female respondents is more than male
respondents. This is due to the type of work in the finishing process and product packing
that requires accuracy and patience, this type of skill is mostly owned by women up to 85
people (78%) and men as many as 22 people (22%). Most of the respondents were 26-30
years old, namely 58 people (53.2%), respondents between 21-25 years old were 29 people
(26.6%), and 22 people 30-40 years old (20, 2%).
4.2 Data Analysis
The data processing technique using the Partial Least Square (PLS)-based SEM method
requires 2 stages to assess the Fit Model of a research model (Ghozali, 2006). These stages
are described as follows:
4.2.1. Descriptive statistics
Descriptive statistics is a method of collecting and presenting data so as to provide useful
information, presenting both numerically and visualizing and classifying data using
tables, in accordance with technological advances, (Ronald E. Walpole, 1993). Some
indicators of research variables are not used in hypothesis testing, so that the presentation
of descriptive statistical analysis will also not be included. Descriptive statistics are
intended to analyze data based on the results obtained from respondents' answers to each
variable measuring indicator. Descriptive statistical analysis can be seen in table 4.3.
Table 4. 3 Statistic Description
Source: Processed primary data, 2021
Based on table 4.3, it is shown that the compensation variable has a theoretical range
between 22 and 35 with an average value of 31.055 and a standard deviation of 3.885.
With an average value of 31.055 which is higher than the median value of 30, this
indicates that the Compensation variable in general has a better perception. The
Performance Appraisal variable has a theoretical range between 18 and 30 with an
average value of 26,495 and a median of 27 and a standard deviation of 3,698. It can be
seen that the average value is lower than the median, this indicates that the performance
appraisal according to the respondent's perception is less trusted to fulfill a sense of
justice (fearness) with an error rate of 3,698. The competence variable has a theoretical
range of 13 to 20 with an average value of 18.046 and a standard deviation of 2.152.
With an average value of 18.046 which is lower than the median of 19, this indicates that
according to the respondent's perception the Competence variable is less able to mediate
in fulfilling Job Satisfaction with an error rate of 2.152. Job Satisfaction variable has a
Variable
N
Minimum
Maximum
Median
Mean
Standar
Deviasi
Compensation 109 22 35
30 31,055 3,885
Performance
Assessment
109 18 30 27 26,495 3,698
Competence 109 13 20 19 18,046 2,152
Job
Satisfaction
109 23
30 28 28,027 2,850
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range between 23 to 30 with an average value of 28.027 and a standard deviation of 2.85.
With an average value of 28.027 and a median value of 28, it can be said that job
satisfaction is generally quite high. The standard deviation value indicates a deviation of
2.85 from the average value of respondents' answers to statements about 28.027.
4.2.2. Model Construct
Individual reflexive measures are said to be high if they correlate more than 0.70 with
the construct being measured. However, according Chin, 1998 (in Ghozali, 2006) for
research in the early stages of developing a scale for measuring factor loading values of
0.5 to 0.6, it is considered sufficient. In this study, a loading factor limit of 0.60 will be
used.
Figure 4.1. Research Model Fit
Source: Data processing with smartPLS, 2021
4.2.3 Evaluating Reliability and Average Variance Extracted (AVE)
Evaluation of the validity and reliability test is a statement test in the research construct to
see whether the statements compiled by the researcher are valid and have consistency to
meet the research objectives. The criteria for validity of the Average Variance Extracted
(AVE) value and reliability can be seen from the Cronbach's Alpha value in each of the
model constructs. A construct is said to have high reliability if its value is above 0.70 and
AVE is above 0.50. In table 4.5 the Composite Reliability and AVE values are presented
for all variables.
Table 4. 5 Composite Reliability and Average Variance Extracted
Cronbach’s
Alpha
Rho_A Composite
Reliability
Average Variance
Extracted (AVE)
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Job Satisfaction 0,924 0,928 0,941 0,728
Compensation 0,904 0,920 0,924 0,636
Competence 0,790 0,793 0,864 0,615
Performance
Assessment
0,894 0,895 0,919 0,655
Source: Data processing with smartPLS, 2021
Based on table 4.5 it can be concluded that all constructs that meet the criteria are valid
and reliable. This is indicated by the composite reliability value above 0.70 and AVE
above 0.60 as recommended criteria.
4.2.4 Collinearity Statistics (VIF) Testing
Multicollinearity can also be seen from the value of tolerance and Variance Inflation
Factor (VIF). A low tolerance value equals a high VIF value. The research data
requirements are normally distributed and free from multicollinearity symptoms in
smartPLS, requiring a VIF value below 5.
Table 4.7 Collinearity Statistic (VIF)
Research
Variables
Job
Satisfaction
Compensation Competence Performance
Assessment
Job Satisfaction
Compensation 3,826 1,963
Competence 4,075
Performance
Assessment
2,215 1,963
Source: Data processing with SmartPLS, 2021
Based on the results of the multicollinearity test above, all research data on each model
construct is free from multicollinearity symptoms, for this reason these results have met
the prerequisite test.
4.2.5 Structural Model Testing (Inner Model)
Testing of the inner model or structural model is carried out to see the relationship
between the construct, significance value and R-square of the research model. The
structural model was evaluated using R-square for the dependent construct of the t-test and
the significance of the coefficients of the structural path parameters. In assessing the
model with PLS, it begins by looking at the R-square for each dependent latent variable.
Table 4.7 is the result of R-square estimation using SmartPLS.
Table 4. 8 Value R-Square
R Square R Square Adjusted
Job Satisfaction 0,543 0,530
Competence 0,755 0,750
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Source: Data processing with PLS, 2021
In principle, this study uses 2 variables that are influenced by other variables, namely the
Job Satisfaction variable (Y) which is influenced by Compensation (X1) and Performance
Appraisal (X2) and the Competence variable (M) as a mediating variable which is
influenced by Compensation (X1) and Performance Assessment (X2). Table 4.8 shows the
R-square value of 0.543 showing the magnitude of the simultaneous influence of the
Compensation variable, Competency-mediated Performance Assessment on Job
Satisfaction of 54.3%. The R-square value of 0.755 on the Competence variable was
obtained indicating that the magnitude of the influence of the Compensation and
Performance Appraisal variables on the Competence mediation was 75.5%.
4.3. Hypothesis test
Hypothesis testing aims to test the relationship between variables in the research construct
whether it is accepted or rejected. The significance of the estimated parameters provides
very useful information about the relationship between the research variables. The basis
used in testing the hypothesis is the value contained in the output result Path Coefficients.
Table 4.9 provides output for structural model testing.
Table 4. 9 Direct effect between variables (Path Coefficients)
Direct effect
Original
Sample
(O)
Sample
Mean
(M)
Standard
Deviation
(STDEV)
T Statistic
(O/STDEV)
P
Value
Compensation
Job Satisfaction
0,563 0,570 0,103 5,447 0,000
Compensation
Competence
0,676 0,675 0,056 12,148 0,000
Competence
Job Satisfaction
0,538 0,532 0,194 2,712 0,006
Performance
Assessment
Job Satisfaction
0,164 0,162 0,124 1,315 0,189
Performance
Assessment
Competence
0,249 0,253 0,066 3,768 0,000
Source: Data processing with PLS, 2021
In the smartPLS test, statistically each hypothesized relationship is carried out using
simulation. To see whether or not there is an influence between the variables of the
research construct, it can be seen from the P value below 5% (< 0.005). In addition, to
assess the relationship between variables having a positive or negative relationship can be
seen from the Original Sample, if it shows a positive value the relationship between
related variables has a positive value, and vice versa. In this case, the bootstrap method is
applied to the sample. Testing with bootstrap is also intended to minimize the problem of
abnormal research data.
In the construct of the research model, the Compensation and Performance Appraisal
variables are mediated by Competence, the relationship between these variables can be
read through Table 4.10
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Table 4.10 Spesific Indirect Effects
Indirect effect
Original
Sample
(O)
Sample
Mean (M)
Standard
Deviation
(STDEV)
T Statistic
(O/STDEV)
P
Value
Compensation
Competence
Job Satisfaction
0,364 0,361 0,140 2,601 0,010
Performance
Assessment
Competence
Job Satisfaction
0,134 0,135 0,061 2,187 0,029
Source: Data processing with PLS, 2021
Based on the results of the bootstrapping test above, the relationship between variables in
the model construct can be analyzed as follows:
The direct effect between Compensation to Job Satisfaction.
Based on the results of testing the first hypothesis, it shows that the provision of
compensation has an effect on job satisfaction. This result is shown from the P value of
0.000 and the original sample of 0.563. Thus the first hypothesis (H1) is accepted. The
results of this study are in line with previous research Sofyandi (2013:162); This also
supports research from T. Retnoningsih, B.S Sunuharjo, I. Ruhana, (2016) which states
that there is a strong relationship between compensation and employee job satisfaction.
The direct effect between Compensation to Competence
Based on the results of testing the second hypothesis, it shows that the provision of
compensation has an effect on competence. This result is shown from the P value of 0.000
and the original sample of 0.676. Thus the second hypothesis (H2) is accepted. The results
of this study are in line with previous research, namely Septerina and Rusda Irawati (2018)
in addition, Yunus (2012); Klarner, et al., (2013); Rudlia (2016). which explains that the
provision of Compensation must be based on the competency criteria of employees.
The direct effect between Performance Assessment to Job Satisfaction
Based on the results of testing the third hypothesis, it shows that Performance Appraisal
has no effect on Job Satisfaction. This result is shown from the P value of 0.189 (> 0.005)
and the original sample of 0.164. Thus the third hypothesis (H3) is rejected. The results of
this study are not in line with previous research, namely January, Utami, Ruhana (2015)
which argues that performance appraisal has an effect on job satisfaction, even further
explained that the better the implementation of performance appraisal, the higher job
satisfaction. Andari, Nafiudin (2019) explained that performance appraisal has a positive
effect on employee job satisfaction.
The direct effect between Performance Assessment to Competence
Based on the results of testing the fourth hypothesis, it shows that Performance
Assessment has an effect on Competence. This result is shown from the P value of 0.000
and the original sample of 0.249. Thus the fourth hypothesis (H4) is accepted. The results
of this study are in line with previous research, namely Wibowo (2014); Supatmi, Nimran,
& Utami, (2013) who explained that there is a strong relationship between Performance
Appraisal and Employee Competence.
The direct effect between Competence to Job Satisfaction
Based on the results of testing the fourth hypothesis, it shows that competence has an
effect on job satisfaction. This result is shown from the P value of 0.000 and the original
sample of 0.538. Thus the fifth hypothesis (H5) is accepted. The results of this study are in
line with previous research, namely Mathis and Jackson (2002:81) and Dessler, (2004:70)
which explain that there is a strong correlation between Performance Appraisal and
Employee Competence.
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Indirect Effect of Competence through Competence on Job Satisfaction
Based on the results of testing the sixth hypothesis, it shows that, Compensation through
Competence has an effect on Job Satisfaction. This result is shown from the P value of
0.010 and the original sample of 0.364. Thus the sixth hypothesis (H6) is accepted. The
results of this study are in line with previous studies, namely Yunus (2012); Klarner, et al.,
(2013); Nazir et al. (2013); Rood and Holdnak (2013); Rizwan (2014); Adeoye and Fields
(2014); Salisu et al. (2015); Muguongo et al. (2015); Rudlia (2016); Rahayu and Riana
(2017); Septerina and Rusda Irawati (2018) explain that there is a significant effect of
giving compensation based on competence to fulfill employee job satisfaction.
Indirect Effect of Performance Assessment through Competence on Job Satisfaction
Based on the results of testing the seventh hypothesis, it shows that, Compensation
through Competence has an effect on Job Satisfaction. This result is shown from the P
value of 0.029 and the original sample of 0.134. Thus the seventh hypothesis (H7) is
accepted. The results of this study are in line with previous research, namely Supatmi,
Nimran, & Utami, (2013) and Wibowo (2014), which explain that there is a significant
effect of a Performance Assessment based on Competence will meet employee job
satisfaction.
CONCLUSIONS AND SUGGESTIONS
Conclusion
Based on the analysis and discussion in the previous section, the following conclusions can
be drawn:
1. A direct compensation will have a significant effect on employee job satisfaction.
Compensation can be a work motivation as the actualization of satisfaction with the
management award for the individual/employee. The compensation provided can be in
the form of facilities or non-financial compensation for the achievement of its
performance.
2. A compensation given based on consideration of individual competence is a form of
management appreciation for employee professionalism, so this attitude also triggers
motivation for other employees to further improve their individual professionalism.
3. Employee performance appraisal directly does not affect employee job satisfaction, this is
due to the existence of an element of superior subjectivity to certain individual
assessments so that it cannot fulfill a sense of justice in the eyes of employees. Based on
the results of this study, it can be used as input to make improvements to the governance
of human resource management.
4. Employee performance appraisal based on individual competence is considered more
fulfilling the sense of justice and management professionalism in managing human
resource management.
5. Employee competence is proven to have an influence in fulfilling job satisfaction.
Competence is the most basic thing in building employee professionalism.
6. Compensation given to employees based on consideration of individual competence will
provide job satisfaction. This can be measured by increasing the achievement of
employee performance. Non-financial compensation such as providing housing facilities
and work vehicles can increase work discipline and employee loyalty to the company.
Likewise, financial compensation in the form of performance bonuses is able to motivate
the achievement of targeted performance for these employees.
7. Performance appraisals based on individual competencies are considered to be able to
fulfill a sense of satisfaction at work, because the achievement of work performance is
really calculated objectively by management.
Limitations
The implementation of the research still has several limitations, namely:
1. Research variables related to employee job satisfaction can still be developed such as by
adding leadership styles, work environment and others, so it is hoped that this research
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can be developed in further research, to complement and enrich scientific discoveries in
management science that can be directly implemented directly. real in industry.
2. This research has only been conducted in the manufacturing industry and may not have
been carried out in the digital industry which measures the performance of its employees
based on public responses such as the e-commerce industry and public official agencies.
Suggestions
Based on the limitations in this study, it is expected that:
Further research can develop points from the limitations described above, both the
development of research variables and indicators and respondent sampling.
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