Syntax Literate: Jurnal Ilmiah Indonesia p–ISSN: 2541-0849 e-ISSN: 2548-1398
Vol. 9, No. 1, Januari 2024
OPTIMIZING THE PERFORMANCE OF EDUCATION
PERSONNEL: A REVIEW OF PERFORMANCE ALLOWANCE AND MOTIVATION FACTORS AT
MARANATHA CHRISTIAN UNIVERSITY
Bintang Fajarsyah, Lina Anatan
Faculty of Business, Universitas Kristen Maranatha, Indonesia
Email: [email protected], [email protected]
Abstract
This study aims to examine how performance
allowances and motivation affect Maranatha Christian University education
staff's performance. The study population consisted of all 292 educational
staff at Maranatha Christian University. The sample size was established using
the Slovin method, yielding a sample of 75
respondents. Using Full Model Regression, a multiple linear regression equation
was obtained: Y = 12.051 + -001 X1 + 0.072 X2. From this equation, it can be
deduced that the coefficient of determination (r2) is 0.466, meaning that the
X1-X2 variables may account for 46.6% of the model's variance while the
remaining variance (53.4%), which is not accounted for by this regression
model, is explained by other variables. The calculated F value was 33,249, with
a significant F of 0.000 < 5%. This supports the hypothesis that Ho: b1= b2
≠ 0, meaning that both factors (X) have an impact on Y.
Keywords: employee performance;
motivation; performance allowance
Introduction
For a business, improving
employee performance is a very important aspect. This individual performance
has a significant impact on the overall productivity and expansion potential of
the company. In this regard, understanding the concept of "motive" in
the context of work is highly relevant. Motives, in this case, refer to the
underlying reasons that drive individuals to work. Basic individual needs, such
as the need for recognition, rewards or financial security, are often the
source of motivation in the workplace. However, it is important to remember
that individual desires can vary significantly, and what motivates one person
may be different to another. Humans are the main element in every organization,
they are not only task performers, but also planners and prime movers who
influence the achievement of organizational goals (Mamminanga et
al., 2023). Therefore, companies need to pay attention
to elements such as performance benefits and motivational programs to better
understand individual motives and improve overall employee performance.
Performance allowances play an important role as an incentive for employees to achieve better performance by providing additional cash rewards (Najoan et al., 2018). These performance allowances can vary according to individual performance, creating intrinsic motivation for employees to achieve better results. In an organizational context, performance allowances can be considered an effective method of rewarding employees who have achieved or exceeded their work targets (Wati et al., 2021). As such, it creates a strong bond between performance rewards and employee motivation, which in turn can result in improved morale and overall performance within the organization.
For employees to have good work enthusiasm, they need to be motivated as well. Meanwhile, in the realm of human behavior, motivation serves as a catalyst, conduit, and pillar that incites individuals to exert diligent and fervent efforts to attain the most favorable outcomes (Junaedi & Fitriansyah, 2021). Performance according to Saputra is the extent to which workers successfully complete their tasks within a certain time frame in accordance with established or mutually agreed standards, targets or work criteria (Saputra et al., 2023). Meanwhile, Fahmi's opinion says work motivation is a set of spirit and encouragement that can make someone to be able to do work well (Kartini & Kristiawan, 2019). Employee performance may also improve with the offer of performance bonuses and job motivation. Thus, employee performance is related with each employee's achievements in line with the organization's regulations or expectations (Fuertes et al., 2020). In his study, Kasmir (2020) highlights a range of variables that have been found to exert an influence on employee performance. These variables encompass knowledge, personality, skill and competence, work discipline, work environment, work motivation, leadership, organizational culture, loyalty, and job satisfaction (Hustia, 2020).
Maranatha Christian University demonstrates a commendable commitment to its valued employees as evidenced by its provision of performance allowances and motivation. Nevertheless, it is worth noting that there remains a notable deficiency in the discipline exhibited by certain individuals in the education sector when it comes to fulfilling their professional responsibilities. Based on the supplementary data provided by Maranatha Christian University's Directorate of Human Resources in 2022, it has come to our attention that there have been instances of attendance violations among educational staff. These violations primarily involve tardiness in reporting to work. According to the data presented, it is evident that on a monthly basis, a notable number of individuals consistently surpassed the predetermined threshold for tardiness, exceeding 10 individuals. Furthermore, it is worth noting that in the year 2022, a total of 32 education personnel were subjected to reprimands or warnings as a consequence of their committed violations.
In addition to the secondary data that has been submitted, researchers also conduct preliminary studies by conducting pre-survey research as supporting material to have a better grasp of the effects of performance bonuses and motivation on productivity. This pre-research survey was conducted with 30 education personnel at Maranatha Christian University, with a total of 22 statements. There is a statement stating that I enter and leave work according to the company regulations. From this statement, of the 30 educational staff respondents studied, it turned out that there were 6 educational staff respondents (20.0%) who answered disagree. 11 educational staff respondents (36.7%) agreed, while 12 educational staff respondents (40.0%) strongly agreed. This indicates that most of the education personnel strongly agreed that I came to work and went home according to company regulations. From the responses of education personnel regarding the effect of work allowances and motivation on the performance of education personnel that have been submitted, there are differences between secondary data and primary data related to coming to work and going home according to company regulations. while secondary data record violations related to late entry to work. Researchers are thus looking at how much performance bonuses and motivation affect the educational personnel at Maranatha Christian University.
Hanifah (2017) used path analysis to examine
data from a research study on the impacts of performance bonusses on work
discipline, work motivation, and employee performance in river basin
management centers in East Java. The study included a sample of 83 employees
from BPDAS. The findings showed that: (1) performance allowances had no effect
on work motivation; (2) performance allowances had no effect on work
discipline; (3) performance allowances had a significant negative impact on
employee performance; and (4) motivation and discipline had no impact on
employee performance. The performance allowance system in BPDAS East Java
Province was found to be ineffective in improving employee motivation,
discipline, and performance, and requires improvement.
Employee
performance has also been researched in terms of compensation and motivation. (Asriani et al., 2020). The effectiveness of a company's workforce affects its
success. The performance of the workforce will be enhanced, making it simpler
to accomplish the business objectives. Pay and motivation are two elements that
might enhance employee performance. The purpose of this study was to identify
and evaluate how salary and workplace motivation affect employee performance.
The sampling technique used is called purposive sampling. Through the use
of surveys, literature studies, and observations, data were acquired.
Techniques for concurrently and partially testing the hypotheses while
analyzing basic linear regression data. As a result, both motivation and
remuneration have a big impact on how well employees work, employee
performance, motivation, and remuneration.
According to Agusra et al. (2021), both employee compensation and motivation have an effect on employee performance. A study was conducted at PT Adicitra Mulyatama in Pekanbaru, Riau, Indonesia, to investigate the influence that incentives and compensation have on employee performance. The investigation utilized a representative sample of forty people from the census. Compensation affects how well employees do their jobs, according to this study. According to the findings of the study, factors other than compensation and motivation only account for 19.6% of the total influence on employee performance.
Subroto et al., (2022) investigated the impact of job motivation and performance incentives on the performance of MAN 1 personnel in Serang City. The goal of this research is to find out: 1. the influence of work motivation on the performance of MAN 1 Kota Serang employees; 2. the impact of work allowances on the performance of MAN 1 Kota Serang employees; and 3. the impact of work motivation variables and work allowances on the performance of MAN 1 Kota Serang employees. The method used is quantitative research. Data collection and analysis are quantitative/statistical in nature, with the goal of testing predetermined hypotheses. The sample used is a population sample where the entire population is sampled, totaling 35 employees of MAN 1 Kota Serang. Product moment correlation analysis was performed to analyze the data, at a significance threshold of 5% multiple regression analysis. The results showed that: 1. There is a positive and significant influence between Work Motivation, on the Performance of Employees of MAN 1 Kota Serang, where t-count 4, 405 t-table 1,692. 2.There is a positive and significant influence between the Work Allowance of Employees of MAN 1 Kota Serang where the t-count of 4.504> t-table 692. 3.There is a positive and significant Work Motivation and Work Allowance variables on the Performance of Employees of MAN 1 Kota Serang, where f-count of 10.933> f-table 3.28 or impression round of 0.00 <0.05.
Additional research is required to investigate the role of performance allowances and motivation in the performance of educational staff at Maranatha Christian University. This investigation will produce hypotheses to predict the results of the investigation and assess the concepts that are relevant to the research issue. This study's hypotheses are as follows:
H1 : Performance allowances affect the performance of education personnel at Maranatha Christian University.
H2 : Motivation impacts the performance of education personnel at Maranatha Christian University.
H3 : Performance allowances and motivation affect the performance of education personnel at Maranatha Christian University.
Research Methods
This study’s population were all education
personnel of Maranatha Christian University with a total of 292 education
personnel. This study uses primary data sources which are carried out using
questionnaire data collection techniques. Then sampling was carried out using
simple random sampling techniques. The method employed for determining the
sample size involves the utilization of the Slovin
formula, incorporating a 10% margin of error. Consequently, the confidence
level of the sample is set at 90%. Given a population size (n) of 292 education
personnel and a margin of error (e) of 10%, the minimum required sample
size was calculated to be 74.49 responders. However, to get ease in processing
data, it is rounded up to 75 respondents.
The
questionnaire's validity was assessed by the utilization of statistical
measures, namely the product-moment correlation coefficient and a t-table with
a significance level set at 0.05. The sample size, denoted as n, was employed
in conjunction with a significance level of 0.05. A significance value less
than or equal to the predetermined alpha (α) was utilized to compare the
computed value with the corresponding value in the table. If the computed value
of r was equal to or greater than the critical value from the table, the item
was deemed to be valid. If the computed value was smaller than the value in the
table, the item was deemed to be invalid. Cronbach's alpha was employed to
assess the reliability of the questionnaire, while the Kolmogorov-Smirnov test
was utilized to confirm the normality of the data. The VIF value had to be less
than 10.00 and the tolerance value had to be less than 0.10 in the absence of
multicollinearity. The F test was used to determine whether or not signs of
multicollinearity existed at a significance level of 0.05. Each independent
variable's effect on the dependent variable was evaluated using a significance
test. The null hypothesis (H0) was accepted and the alternative hypothesis (Ha)
was rejected if the p-value of the t-test was greater than 0.05. This suggests
that the independent factors did not have a statistically significant impact on
the dependent variable. On the other hand, in the event that the p-value was
found to be below 0.05, the null hypothesis (H₀) was rejected, hence accepting
the alternative hypothesis (Ha). This outcome suggests the presence of a
statistically significant relationship between the independent variable and the
dependent variable.
The
variables performance allowance (X1) and incentive (X2) are in this study
considered to be independent variables, while the variable employee performance
(Y) is considered to be the dependent variable.
Table 1.
Variables and indicators
|
Variable |
Definition |
Indicator |
Measurement Scale |
|
Performance Allowance (X1) |
The
performance allowance itself is a reward provided to workers for their
performance with the intention of boosting morale (Najoan,
2018). |
1.
In my opinion, so far
the performance allowance provided is in accordance with my workload. 2.
I think that so far
the performance allowance provided is more or
less the same as employees who work in other
agencies for the same job. 3.
So far, the performance
allowance provided is in accordance with my work
performance and the risks of
the work I do. 4.
I receive a performance allowance based on my
hard work. 5.
The performance
allowance that I receive is in accordance with existing regulations. 6.
The performance
allowance I receive is sufficient to fulfil the
needs of my family. 7.
The performance
allowance supplied in addition to basic
wage meets my needs in accordance
with the allowance's goal of improving employee wellbeing. |
Ordinal |
|
Motivation (X2) |
Motivation is a driving force
that propels human behavior, directs it towards a
specific goal, and sustains the effort required to achieve optimal results (Hasibuan, 2017). |
1. Rewards for me at work can
motivate me to work. 2. I try my best to be
the best at work. 3. I enjoy working
with others more than working
alone. 4. I understand work
systems & procedures based on knowledge
& expertise. 5. I am co-operative,
cooperation supports goal achievement. 6. I am confident
that with my abilities, I can work well
in the company. 7. I prioritise tasks
over personal interests. |
Ordinal |
|
Employee Performance (Y) |
Employee
performance is related with each employee's accomplishments in line with the
organization's standards or expectations. (Fuertes et al., 2020). |
1.
I am
able to complete work that is better
than standard. 2.
I can
complete every job carefully and neatly. 3.
The work
I generate is in agreement with the company's goals. 4.
I can
complete my work in a timely manner. 5.
I always
try to get more work
done. 6.
I always
arrive earlier than office hours. 7.
I arrive
and leave work according to company regulations. 8.
I always
obey the rules in terms of work discipline. |
Ordinal |
Source: (Darminto, 2017; Pandari,
2021)
Multiple linear regression is used
for analysis, where multiple regression is defined by (Indrawan
and Yuniawati, 2017) as a dependent metric variable predicted by
multiple independent metric variables.
Results
and Discussion
Results
The characteristics of the education
personnel respondents at Maranatha Christian University were categorized based
on their gender, employment status, and length of service. There were 44 male
respondents ( 59% of the total) and 31 female
respondents ( 41% of the total). After that, job status determined respondents'
characteristics. There were 64 permanent administrative staff (85%), and 11
housekeeping employees (15%). The characteristics gathered data on 1-5 years of
service from as many as 14 respondents (19%), 6-10 years of service from as
many as 17 respondents (23%), and >10 years of service from as many as 44
respondents (59%).
Validity
Test
Table 2. The results of the validity test indicate
that variables X and Y demonstrate a significant correlation between each
statement item and the overall score of each variable, as evidenced by a r
count value greater than 0.2272. Upon careful analysis, it can be inferred that
all elements of the statements provided are indeed valid.
Table 2. The
results of the validity test of variables X and Y
|
Variable |
Item |
rcount |
r table |
Description |
|
Performance Allowance |
Statement 1 |
0,555 |
0,2272 |
Valid |
|
Statement 2 |
0,470 |
0,2272 |
Valid |
|
|
Statement 3 |
0,541 |
0,2272 |
Valid |
|
|
Statement 4 |
0,674 |
0,2272 |
Valid |
|
|
Statement 5 |
0,520 |
0,2272 |
Valid |
|
|
Statement 6 |
0,509 |
0,2272 |
Valid |
|
|
Statement 7 |
0,472 |
0,2272 |
Valid |
|
|
Motivation |
Statement 8 |
0,424 |
0,2272 |
Valid |
|
Statement 9 |
0,493 |
0,2272 |
Valid |
|
|
Statement 10 |
0,445 |
0,2272 |
Valid |
|
|
Statement 11 |
0,566 |
0,2272 |
Valid |
|
|
Statement 12 |
0,544 |
0,2272 |
Valid |
|
|
Statement 13 |
0,494 |
0,2272 |
Valid |
|
|
Statement 14 |
0,466 |
0,2272 |
Valid |
|
|
Education Personnel Performance |
Statement 15 |
0,626 |
0,2272 |
Valid |
|
Statement 16 |
0,522 |
0,2272 |
Valid |
|
|
Statement 17 |
0,483 |
0,2272 |
Valid |
|
|
Statement 18 |
0,572 |
0,2272 |
Valid |
|
|
Statement 19 |
0,460 |
0,2272 |
Valid |
|
|
Statement 20 |
0,403 |
0,2272 |
Valid |
|
|
Statement 21 |
0,434 |
0,2272 |
Valid |
|
|
Statement 22 |
0,479 |
0,2272 |
Valid |
Source:
Data processed using SPSS 26 (2023)
Reliability
Test
Table 3. The Cronbach's alpha score for the reliability test of
variable x1 was 0.901. The Cronbach's alpha result for the x2 variable
reliability test was 0.754. Variable y's reliability test yielded a Cronbach's
alpha score of 0.809. Because the Cronbach alpha value for all three variables
is more than 0.6, it is possible to conclude that the questionnaire was
reliable or trustworthy.
Table 3. Reliability test results
|
Variable |
Cronbach’s
Alpha |
N of
Items |
Keterangan |
|
Performance Allowance (X1) |
901 |
7 |
Reliable |
|
Motivation (X2) |
754 |
7 |
Reliable |
|
Education Personnel Performance
(Y) |
809 |
8 |
Reliable |
Source:
Data processed using SPSS 26 (2023)
Classical assumption test
Multicollinearity test
Table 4. The performance allowance
variable (X1) and motivation (X2) multicollinearity test results have an
acceptable value of 0.982> 0.10. Performance allowance (X1) and motivation
(X2) have a VIF value of 1.018 <10.00. If both variables are more than 0.10,
it is determined that there is no multicollinearity between the independent
variables in this study, and the regression can be proceeded.
Table 4.
Multicollinearity test results
|
Coefficientsa |
|||
|
No |
Variable |
Collinearity Statistics |
|
|
Tolerance |
VIF |
||
|
1 |
Performance Allowance (X1) |
0,982 |
1,018 |
|
2 |
Motivation
( X2 ) |
0,982 |
1,018 |
Source:
Data processed using SPSS 26 (2023)
Normality test one-sample
kolmogorov - smirnov test
Table
5. The one-sample Kolmogorov-Smirnov
Test normalcy test results reveal
that the Asym. Sig. (2-tailed) of 0.200> 0.05. Furthermore, the data can be
inferred to be regularly distributed
using the Kolmogorov-Smirnov normality test decision criteria.
As a result, the normality assumption and the regression
model criteria are met.
Table 5.
Normality test results one-sample kolmogorov - smirnov Test
|
One-Sample Kolmogorov-Smirnov Test |
||
|
|
|
Unstandardized Residual |
|
N |
|
75 |
|
Normal Parametersa,b |
Mean |
0,0000000 |
|
|
Std.
Deviation |
3,18743128 |
|
Most Extreme Differences |
Absolute |
0,075 |
|
|
Positive |
0,053 |
|
|
Negative |
-0,075 |
|
Test Statistic |
|
0,075 |
|
Asymp. Sig. (2-tailed) |
|
.200c,d |
Source:
Data processed using SPSS 26 (2023)
Multiple linear regression analysis
Table 6. The multiple linear
regression equation based on calculations using the SPSS 26 programme using
full model regression is: Y = 12.051 + -001 X1 + 0.072 X2 From the table
presented, it can be seen that the coefficient of determination (r2) is 0.466.
This means that the X1-X2 variables are able to explain 46.6% of the model, and
the rest (53.4%) can be explained by other variables that are not in this
regression model. The regression analysis then shows the calculated F value of
33.249 with a significant F of 0.000 <5%. This proves Ho: b1 = b2 ≠ 0. This
means that the two factors as independent variables (X) together have a
positive influence on the dependent variable (Y).
Table 6. Results of coefficients a multiple linear
regression analysis
|
Coefficientsa multiple linear regression analysis |
||||||
|
Model |
Unstandardized
Coefficients |
Standardized
Coefficients |
t |
Sig. |
||
|
B |
Std.
Error |
Beta |
||||
|
1 |
(Constant) |
12.051 |
4.082 |
|
2.952 |
.004 |
|
Performance Allowance (X1) |
-.001 |
.006 |
-.008 |
-.097 |
.923 |
|
|
Motivation (X2) |
.072 |
.009 |
.694 |
8.095 |
.000 |
|
|
a. Dependent Variable: Education Personnel Performance (Y) |
||||||
Source: Data processed using SPSS 26 (2023)
Dependent variable : Education Personnel
Performance ( Y )
F count : 33.249
Alpha : 0.05
Adjusted R Square ( R2 ) : 0.466
Sign. F : 0.000
Hypothesis testing
The
f-test
Table 7. The results of anova f
test using SPSS 26 obtained F count data of 33,249 and a significance value of
0.000. Then from the F table α = 0.05 obtained a value of 2.732. F count =
33.249> F table = 2.732 and significance 0.000 <0.05 then Ho is rejected.
This means that X1 = Performance allowance, X2 = Motivation together affect the
performance of educational staff at Maranatha Christian University.
Table 7. Result of anovaa
The f-test
|
ANOVAa The f-test |
||||||
|
Model |
|
Sum
of Squares |
df |
Mean
Square |
F |
Sig. |
|
1 |
Regression |
694,368 |
2 |
347,184 |
33,249 |
.000b |
|
|
Residual |
751,819 |
72 |
10,442 |
|
|
|
|
Total |
1446,187 |
74 |
|
|
|
|
a. Dependent Variable:
Education Personnel Performance (Y) |
||||||
|
b. Predictors:
(Constant), Motivation (X2), Performance Allowance (X1) |
||||||
Source: Data processed using SPSS 26 (2023)
Partial Test (t-test)
Table 8. The results of the hypothesis testing, specifically
the t-test, indicate that the performance allowance variable exhibits a
significance value of 0.923, which is greater than the predetermined threshold
of 0.05. The findings of this study suggest that the performance allowance
variable does not appear to have a significant impact on the performance of
educational staff. The motivation variable has a significant value of 0.000,
which is less than the predetermined threshold of 0.05, according to the
findings of the hypothesis testing (t-test). The aforementioned finding
emphasizes how important a role motivation plays in determining how well
education staff members perform.
Table 8. The
outcome of coefficientsa partial
test (t-test)
|
|
Coefficientsa Partial Test ( t-test ) |
|||||
|
Variable |
t count |
df |
t
table |
Sig |
Description |
Conclusion |
|
Performance Allowance (X1) |
-0.097 |
72 |
1.666 |
0.923 |
H0 rejected |
Not significant |
|
Motivation (X2) |
8.095 |
0.000 |
H0 accepted |
Significant |
||
|
a.
Dependent Variable: Educational Personnel Performance (Y) |
||||||
Source: Data processed using SPSS 26 (2023)
Discussion
The impact of performance allowance on
educational personnel performance
Performance allowance is a form of additional income given to employees as a reward for their exceptional performance, with the aim of boosting employee morale, as suggested by Najoan et al. (2018). The results of hypothesis testing show that the performance allowance has a significance value of 0.923, which is greater than 0.05. This suggests that the performance allowance variable has a partial effect on the performance of Maranatha Christian University education personnel, but it is not statistically significant. This is because Maranatha's organisational culture has a different approach in determining the main components in providing performance allowances. In this culture, performance allowances are not only based on individual achievements, but are more likely to be shared achievements, where performance allowance assessments are assessed based on, university performance, work unit performance and individual performance. This shows that the Maranatha organisation highly values teamwork and collaboration between members in achieving common goals, in this case, there is no discrimination through subjective individual assessments, but fairness is the basis for determining allowances. This means that every team member has an equal opportunity to be given performance allowances based on their contribution to the achievement of common goals. However, older employees with more than six years of service who have had a work contribution allowance since September 2013 are given the option to choose to follow the new performance allowance rules or choose a transitional allowance where the amount of the transitional allowance will be fixed. This is what makes the performance allowance not significantly influential, or it can be said that the performance allowance has only a small effect on the performance of Maranatha Christian University education personnel. Based on the results of this study, there is an inverse relationship between the findings of (Agusra et al., 2021) on the impact of compensation on employee performance at PT Adicitra Mulyatama in Pekanbaru and our findings. Specifically, in their study, partial testing revealed that the compensation variable (X1) has a significant effect on performance (Y), which is demonstrated by a t-count value of less than 2.024 with an influence value of 4.859, which is less than the critical value of 2.024. This finding implies that the relationship between remuneration and employee performance may not be statistically significant in the specific scenario under investigation.
The effect
of motivation on the performance of education personnel
The results of the hypothesis test, known as a T-test, are
displayed in the table that can be found above. These results suggest that the
significance level of the motivation variable is 0.000, which is lower than the
threshold value of 0.05 that was determined beforehand. This suggests that the
variable of motivation has a significant impact on the performance of educational
staff members. This observation is consistent with the findings of (Agusra et al., 2021), who demonstrated that motivation has
a significant impact on both employee performance and compensation. This
observation aligns with the findings of (Agusra et
al., 2021). According to the findings of their study, employee motivation is
responsible for 80.4% of the variation in performance, while the remaining
19.6% of the variance in performance can be attributed to unexplored variables
in their study.
The effect of
performance allowances and motivation on the performance of education personnel
According to the results
obtained from the statistical software SPSS 26, the F-count is determined to be
33,249, while the significance value is reported as 0.000. Based on the
F-table, a significance level of α = 0.05 is utilized, and a calculated value
of 2.732 is achieved. The null hypothesis (Ho) is rejected based on the
statistical analysis, since the calculated F-value (33.249) exceeds the
critical F-value (2.732) at a significance level of 0.05. Additionally, the
p-value (0.000) is less than the predetermined significance level. This data
indicates that the performance of education professionals at Maranatha
Christian University is influenced by both performance allowances and
motivation, aligning with the results reported by (Asriani
et al., 2020). The researchers observed a concurrent influence of
compensation (X1) and incentive (X2) on performance (Y) in their study. The
F-value (f-count) obtained in this study was 24.786, with a corresponding
significant level of sig = 0.000.
Conclusion
According
to the findings of the study that the researchers carried out at Maranatha
Christian University on the topic of the impact of performance allowances and
motivation on the performance of education personnel, researchers discovered
that performance allowances have only a modest effect on the performance of the
mentioned personnel. On the other hand, one could argue that performance
allowances at Maranatha Christian University have no discernible impact on the
performance of the education personnel who work there.
The
researchers also believe that factors relating to the educational personnel'
motivation also play an important role in the improvement of the staff' overall
performance at work at Maranatha Christian University. Although performance
allowances have a limited effect on performance, the performance of educational
employees can remain at optimal levels if they are strongly motivated. This is
because educational employees have a lot of autonomy in their jobs. Therefore,
efforts should be made to increase the motivation of the educational staff
at Maranatha Christian University in order to improve the quality of the
performance of the educational staff.
The
research revealed that motivation has a crucial role in influencing the
performance of the education employees at Maranataha
Christian University. The enhancement of employee performance may be achieved
via the provision of suitable motivation. The regression analysis produced the
subsequent equation. The equation can be written as Y = 12.051 + 0.001X1 +
0.072X2. The coefficient of determination (r2) was determined to be 0.466,
indicating that the variables X1-X2 have the ability to account for 46.6% of
the variability seen in the model. The remaining 53.4% of the variability is
attributed to additional variables that were not included in the model. At a
significance level less than 5%, the calculation's F value of 33,249 was
determined to be statistically significant. The analysis' findings corroborate
the theory that the coefficients X1 and X2 do not equal zero, indicating that
the independent variables X have an effect on the dependent variable Y that is
favorable.
The study's conclusions show that performance bonuses do not always have a positive effect on workers' productivity. Hence, it is important for management to meticulously deliberate on the development of performance allowance policies, including the cautious selection of pertinent elements and the establishment of attainable performance objectives. The implementation of inappropriate rules can have detrimental impacts on the performance of employees. It is imperative for management to engage in frequent evaluation and modification of their performance benefit programs, drawing upon the findings of current studies and research. The assessment process may include employee input, performance data analysis, and benchmarking against industry or organizational best practices. Continuous assessments allow management to improve performance benefits programs and satisfy employee expectations.
Employee feedback, performance data analysis, and benchmarking against industry or organizational best practices may be part of the assessment process. Management may improve performance benefits programs and meet employee expectations by implementing regular assessments.
Future studies must consider many factors. First and foremost, a rigorous methodology for assessing and analyzing the benefits of improving employee performance and effectiveness is essential. Work environment, management support, job satisfaction, and mediator influence may need to be considered. This analysis can help Maranatha Christian University create more effective policies that support its faculty. Universities can improve quality and productivity by considering performance allowances and motivation. Understanding how performance allowances and incentives affect performance can help colleges redesign staff development programs and offer incentives. Providing enough education staff rewards. The researcher admitted that lack of competence and experience limited their investigation.
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