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The Influence of Digital Technology use and Additional Employee
Income on Employee Performance Mediated by the use of the E-
Performance Application in Sub-District Offices in Pidie Regency
Nurul Husna, Zulkifli, Isthafan Najmi
Faculty of Economics and Business, Abulyatama University, Indonesia, Aceh
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000701
Received: 02 November 2025; Accepted: 10 November 2025; Published: 21 November 2025
ABSTRACT
This study aims to analyze the influence of the use of digital technology and additional employee income on
employee performance by using the E-Performance application as a mediation variable in sub-district offices
throughout Pidie Regency. The background of this research is based on the problem of low discipline and
performance of some employees, even though digital technology support and additional employee income
have been provided. This study uses a quantitative approach with a survey method. The research population
was all employees of the sub-district office in Pidie Regency, with a sample of 200 respondents selected using
the purposive sampling technique. Data analysis was carried out using Structural Equation Modeling (SEM)
based on Partial Least Square (PLS). The results of the study show that (1) the use of digital technology has a
positive and significant effect on employee performance and the use of the E-Performance application, (2)
additional employee income has a positive and significant effect on employee performance and the E-
Performance application, (3) the E-Performance application has a positive and significant effect on employee
performance, and (4) the E-Performance application mediates the influence of digital technology and
additional employee income on employee performance. This study concludes that the use of technology and
incentive policies will be more effective if supported by an objective and integrated application-based
performance appraisal system.
Keywords: Digital technology, Additional Employee Income, E-Performance Application, Employee
performance.
INTRODUCTION
In the current era of globalization, the majority of government institutions have begun to transition from
manual work to online or digital work. The emergence of applications that are easy to use by all people has
accelerated government services. Latifah explained that the implementation of electronic systems in
government aims to improve the way the bureaucracy works. Examples of this system are E-Kinerja, E-KTP,
and E-Budgeting which help simplify the information collection process and administrative registration
process.
In order to implement Presidential Regulation Number 95 of 2018 concerning Electronic-Based Government
Systems and to support the performance management of State Civil Apparatus employees in government
agencies, it is necessary to implement an integrated employee performance management information system
with the State Civil Apparatus Information System.
Additional employee income or often referred to as incentive is a means of motivation that provides
encouragement to employees to work with optimal abilities, which is intended as extra income outside the
predetermined salary. Employees who work in a company definitely need adequate and fair compensation or
rewards to increase the morale and productivity of the employees themselves.
Additional Income of State Civil Apparatus Employees, hereinafter referred to as additional employee income,
is income other than basic salary and other valid allowances in accordance with the provisions of laws and
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regulations, which are given by the Regional Government to the State Civil Apparatus which is sourced from
the Regional Revenue and Expenditure Budget.
The limitation of Human Resources in agencies has a great effect on the development and maintenance of
digital systems. So many government employees are used to conventional ways of working and are reluctant
to adapt to new technology. It can be interpreted that employee performance is closely related to the results of
a person's work in an organization, which can be related to quality, quantity, and timeliness. Employee
performance is not only influenced by their ability and expertise in work but also greatly influenced by their
work spirit.
The E-Performance Application is a web-based assessment application system that is used to analyze work
performance, unit or unit workload as the basis for calculating work performance and providing work
incentives. With the existence of the E-Performance system, the provision of Additional Employee Income
allowances becomes fairer. Employees who have the same job title will earn rewards that match their
performance. The amount of allowances provided is assessed based on the performance of employees recorded
in the E-Performance system, this system also monitors employee activities during working hours to find out
whether they are active or not. Sirait (2019) Explained that this E-Performance policy encourages employees
to increase the productivity of the State Civil Apparatus and provides opportunities for employees who were
previously less disciplined to be more diligent and increase competitiveness.
However, problems arise in the payment of additional income which is actually intended to provide additional
employee income to provide motivation for employees but does not have an impact as expected, because there
are still various problems, especially employee discipline problems, where related to attendance/attendance is
not optimal, late checks and not filling out daily work reports where each employee is required to complete
main tasks every working day
Based on the results of observations made by researchers at the sub-district office in Pidie district, there are
several problems that occur. First, there are still State Civil Apparatus employees who lack understanding of
technology or "stuttering technology", especially the elderly, which is an obstacle in filling out E-Kinerja.
Second, there are still employees of the State Civil Apparatus who are not in the office during working hours,
where the State Civil Apparatus leaves the room after being absent and sitting in the coffee shop, then does not
come on time when the State Civil Apparatus should be present on time in accordance with the regulations that
have been set. From these two problems, it will be a factor that inhibits the vision and mission of the office and
determines the amount of Employee Income Supplement.
The problem of low effectiveness in the use of digital technology and the provision of incentives in the form of
Additional Employee Income does not only occur in Pidie Regency, but is also an issue that occurs widely in
various regions in Aceh. According to data from the State Civil Service Agency and the Ministry of PAN-RB,
violations of working hours, failure to use the E-Performance application, and the low influence of additional
employee income on the motivation of the State Civil Apparatus are still quite high.
Based on the understanding of the background of the problem that has been explained earlier, the author is
interested in conducting a research entitled " The Influence Of Digital Technology Use And Additional
Employee Income On Employee Performance Mediated By The Use Of The E-Performance Application In
Sub-District Offices In Pidie Regency ".
LITERATURE REVIEW
Digital Technology
Meanwhile, according to Romney & Steinbart (2016), digital technology is defined as computers and other
electronic devices used to store, retrieve, transmit and manipulate data. In the research of Diah (2021), digital
technology is a tool whose operation no longer requires human labor and tends to be a system that can
automatically connect with all computers. Digital technology literacy also brings various conditions about
awareness of digital use, one of which is about social change, because digital technology can present a virtual
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public, as well as fast information transmission. The development of digital technology makes it easy for
people to get various information related to online payments.
Digital Tenology Indicators According to Affandi, (2018) be as follows: 1) Willingness 2) Capability 3)
Accessibility 4) Infrastructure 5) Integration 6) Innovation 7) Impact.
Employee Performance
According to Hasibuan (2017), performance is a result of work achieved by a person in carrying out the duties
of the State Civil Apparatus on skills, effort and opportunity. Meanwhile, according to Adhari (2020),
employee performance is the result produced by certain job functions or activities in certain jobs over a certain
period of time, which shows the quality and quantity of the work. Employee performance according to
(Awaluddin Anwar, 2022) is an overall level of success in a certain period to carry out the duties of the State
Civil Apparatus in accordance with the criteria and provisions that have been set together.
In measuring a performance, several indicators are needed, according to Afandi (2018) the indicators of
employee performance are as follows:
1. Quantity of work output: Any form of unit of measure that relates to the quantity of work output that can
be expressed in numerical measures or other numerical equivalents.
2. Quality of work outputs All forms of units of measurement that are related to the quality or quality of
work outputs that can be expressed in numerical measures or other numerical equivalents.
3. Initiative The ability to decide and do something right without being told, being able to find what to do
with something around you, trying to keep moving to do some things even when things feel more
difficult.
4. Efficiency in carrying out tasks Various resources wisely and how to save costs.
5. Work discipline Obey applicable laws and regulations.
6. Accuracy The level of conformity of the work measurement results whether the work has achieved what
goals it has not.
7. Leadership Process influences or sets an example by the leader to his followers in an effort to achieve the
goals of the organization.
8. Honesty is one of the human traits that is quite difficult to apply.
9. Creativity A mental process that involves the emergence of ideas or that involves the emergence of ideas
Additional Employee Income
According to Sedarmayanti (2021), additional employee income is additional income given to the State Civil
Apparatus by considering performance, competence, and work discipline. Additional Employee Income is part
of the remuneration system that aims to realize a professional, high-performance, and prosperous State Civil
Apparatus. Additional Employee Income is also expected to prevent corruption, collusion, and nepotism
practices in the government bureaucracy.
Additional Employee Income is a form of compensation given to State Civil Apparatus outside the basic
salary. Additional employee income is given with the aim of improving the welfare, motivation, and
performance of the State Civil Apparatus in carrying out their duties and functions. To measure the effect of
providing additional employee income, clear and measurable indicators. According to (Syamsi, 2022)
Indicators that can measure additional employee income include:
1. Workload
2. Work performance
3. Working conditions
4. Competence
5. Work discipline
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E-Performance Application
According to Nabilah et al (2022), E-Performance is a web-based application used by the government to
monitor and assess employee performance. E-Performance aims to improve the performance of Civil Servants
and organizations, tidy up and improve organizational structures, evaluate the performance achievements of
Civil Servants, improve the welfare and justice of Civil Servants and encourage healthy competition, improve
the qualifications and positions held by Civil Servants, and stimulate creativity and innovation in their work.
According to Mukti (2019) E-Performance is an artificial application that is specialized for monitoring and
assessing the performance of employees directly by entering daily work data into the software to get approval
from superiors. According to Bangun (2018), a job can be measured using the following five indicators:
1. Quantity of Work
2. Quality of Work
3. Timeliness
4. Presence
5. Collaborative Capabilities
RESEARCH METHODS
Types and Approaches of Research
This type of research is quantitative research with an analytical survey approach. This research is focused on
analyzing the influence of the use of digital technology and additional employee income on employee
performance mediated by the use of the E-Performance application at the Pidie Regency Sub-district Office.
Sample of 200 respondents, Types of data used primary and secondary, Data collection techniques including
observation, interviews and questionnaire distribution. Data processing used SPSS and PLS (Partial Least
Square) descriptive statistics, Descriptive statistics in this study were used to describe the characteristics of
respondents. Meanwhile, PLS (Partial Least Square) is used to analyze the influence of the use of digital
technology and additional employee income on employee performance mediated by the use of the E-
Performance application at the Pidie Regency Sub-district Office.
The data analysis technique used in this study is quantitative data analysis. The results of the research obtained
from the field were processed using statistical calculations using PLS (Partial Least Square). PLS is a
Structural Equation Modeling (SEM) equation model with an approach based on variance or component-based
structural equation modeling. According to the purpose of PLS-SEM is to develop a theory or build a theory
(prediction orientation). PLS is used to explain whether there is a relationship between latent variables
(prediction). PLS is a powerful analysis method because it does not assume flow data with a certain scale
measurement, small sample size (Hair et al, 2017)
Figure 1.Flowchart
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RESULTS AND DISCUSSION
Respondent Characteristics
The majority of respondents in this study were men, namely 125 people (60.7%), while female respondents
amounted to 81 people (39.3%). The majority of respondents were in the age group of 40–49 years (44.2%),
followed by the age group of 30–39 years (34.5%). Meanwhile, respondents aged 20–29 years were 15%, and
those over 50 years old were only 6.3%. The majority of the education category has a bachelor's education
background, which is 145 (70.4%). As many as 10.7% of respondents completed S2 education, while 7.3% had
taken Diploma III education. In addition, there are 11.2% of respondents who have reached the Diploma IV
education level. Meanwhile, in the service period category, the majority of respondents had a working period
of 9-14 years (34%), followed by a working period of 3-8 years (30.6%). Furthermore, there were 18.9% of
respondents with a working period of 15–20 years, 11.7% with a working period of less than 3 years, and only
4.9% who had worked for more than 21 years. This shows that most of the respondents have a long enough
work experience, which is more than 3 years, so it can be said that they already have a good understanding of
their work.
Evaluation of Measurement Model (Outer Model)
Measurement model testing will be conducted to show the results of validity and reliability tests. In this study,
validity testing is conducted to determine whether the construct has met the requirements to be continued as
research or not. In this validity test, there are two types of evaluations that will be conducted, namely:
Convergent Validity
Convergent Validity models measurement with items that have values based on the correlation between the
item's score and the construct value. The convergent validity index is measured by the factors of AVE,
composite reliability, R square, cronbach's alpha.
The results of the AVE index, composite reliability, R square, cronbach's alpha can be seen in Figure 1.
Table 1Average Variance Extracted
Variable
AVE
Composite
Reliability
Cronbach's Alpha
E-Performance Application (Z)
0.654
0.765
0.712
Employee Performance (Y)
0.689
0.799
0.720
Digital Technology (X1)
0.745
0.718
0.745
Additional Employee Income (X2)
0.631
0.740
0.869
The criteria for validity and reliability can also be seen from the reliability value of a variable and the value of
the Average Variance Extracted (AVE) of each variable. A variable is said to have high reliability if the
composite reliability value is above 0.7 and the AVE is above 0.5. Based on table 1, it is stated that four
variables meet the reliability of the composite because their values are above the recommended number, which
is above 0.7 which already meets the reliability criteria.
The following are the results of the outer model test that shows the value of outer loading using the Smartpls v
3.2.7 analysis tool.
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Figure 2 PLS Path Diagram Model
The results of the analysis shown in Figure 2 show that all research variables have a loading factor value
above 0.7. To see the value of the loading factor, all the construct data can be viewed in Table 2.
Table 2Loading Factor Values of All Second Constructs
Item Code
Loading Factor
AEK.1
0.748
AEK.2
1.074
AEK.3
1.062
AEK.4
1.137
AEK.5
0.925
KP.1
1.180
KP.2
1.070
KP.3
1.087
KP.4
0.958
KP.5
0.659
KP.6
0.684
TD.2
0.620
TD.3
0.551
TD.4
0.950
TD.5
1.243
TD.6
1.104
TD.7
1.144
TPP .1
0.827
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TPP.2
1.091
TPP.3
1.034
TPP.4
0.984
TPP.5
1.026
A discriminant correlation test is performed to see the relationship between one construct and another. If the
AVE value of each construct is greater than the correlation value between the construct and the other
construct, then the discriminant validity requirement is met. Here's a table that explains the value of each
variable.
Table 3 Discriminant Validity
E-Performance
Application
Employee
Performance
Digital
Technology
Additional
Employee Income
AEK.1
0.483
0.141
0.250
0.147
AEK.2
0.700
0.192
0.242
0.212
AEK.3
0.672
0.204
0.088
0.191
AEK.4
0.703
0.200
0.165
0.280
AEK.5
0.568
0.217
0.039
0.224
KP.1
0.250
0.672
0.214
0.158
KP.2
0.117
0.592
0.129
0.071
KP.3
0.227
0.601
0.063
0.157
KP.4
0.158
0.529
0.159
0.114
KP.5
0.036
0.373
0.108
0.079
KP.6
0.072
0.382
0.097
0.144
TD.2
0.081
0.136
0.377
0.135
TD.3
0.057
0.069
0.312
-0.026
TD.4
0.126
0.177
0.538
0.089
TD.5
0.131
0.184
0.709
0.131
TD.6
0.140
0.116
0.643
0.192
TD.7
0.246
0.130
0.659
0.162
TPP.1
0.179
0.123
0.081
0.506
TPP.2
0.243
0.176
0.100
0.666
TPP.3
0.167
0.084
0.162
0.624
TPP.4
0.165
0.122
0.098
0.594
TPP.5
0.241
0.165
0.219
0.620
In table 4.12, the AVE value can be seen which shows the number of each variable tested, the data is larger
than the correlation between other variables, so it can be concluded that all latent variables in the study have
good discriminative validity.
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Internal model evaluation or structural model test is used to see the direct and indirect influence between
variables. The values of R-square, F-square, and Q-square are the reference for the internal model evaluation
activities with PLS-SEM. Here are the results.
The model built has two endogenous variables, so it has one or two R2. The R2 values of the endogenous
variables are presented in table 4.15 below.
Table 4 R-square
R-square
E-Performance Application
0.148
Employee Performance
0.136
Based on table 4.8, it appears that the value of R2 (R-Square) of Y Employee Performance is 0.136 or 13.6%.
This value indicates that the Y variable of Employee Performance can be explained by all X variables by
13.4% while the rest is explained by other variables that are not included in this study. Meanwhile, the variable
value R2 (R-Square) of Z of the e-performance application can be explained by 0.148 or 14.8%. All X's in this
study can explain Z by 14.8% while the rest is explained by other variables outside of this study
Hypothesis Test Results
To assess the significance of the influence between variables, a bootstrapping procedure was carried out. The
bootstrap procedure uses the entire original sample to then be resampled. In the bootstrap resampling method,
the significance value used (two-tailed) t-value is 1.96 (significance level 5).
Table 5 Total Effect
Original
Sample (0)
Sample Mean
(M)
Standard
Deviation
(STDEV)
T Statistics
(|O/STDEV|)
P-
Values
E-Performance
Application ->
Employee Performance
0.221
0.227
0.084
2.618
0.004
Digital Technology ->
E-Performance
Applications
0.187
0.205
0.080
2.327
0.010
Digital
Technology ->
Employee
Performance
0.166
0.187
0.088
1.895
0.029
Additional Employee
Income -> E-
Performance
Application
0.298
0.314
0.065
4.559
0.000
Additional Employee
Income -> Employee
Performance
0.119
0.131
0.079
1.510
0.066
Based on the results of the total effect contained in Table 5. It shows that there are 5 paths that have
significance to their constructs with a statistical t-value greater than 1.96 and a p-value less than 0.05, meaning
that the entire path has a good significant value.
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Based on this description, to find out whether a hypothesis is accepted or rejected, it can be done by paying
attention to the significance value between constructs, t-statistics and p-values. Then measurement estimates
and standard errors are no longer calculated on statistical assumptions, but are based on empirical observations.
In the bootstrap resampling method in this study, the hypothesis is accepted that if the significance value of the
t-value is greater than 1.96 and/or the p-value is less than 0.05, then Ha is accepted and Ho is rejected and
vice versa.
Based on Table 5. The determination of the accepted or rejected hypothesis is explained as follows:
The E-Performance Application variable has a t-statistical value of 2,618 > 1.96, and a p value of 0.004 < 0.05.
Therefore, the first hypothesis that states the influence of the E-Performance Application on employee
performance is accepted and supported by research data.
The digital technology variable has a t-statistical value of 2,327 > 1.96, and a p value of 0.010 < 0.05.
Therefore, the second hypothesis that states the influence of digital technology on E-Performance
Applications is accepted and supported by research data.
The digital technology variable has a t-statistical value of 1.895 > 1.96, and a p-value of 0.029 < 0.05.
Therefore, the third hypothesis that states the influence of digital technology on employee performance is
accepted and supported by research data.
The Additional Variable of Employee Income has a t-statistical value of 4,559 > 1.96, and a p value of 0.000 <
0.05. Therefore, the fourth hypothesis that states the influence of Additional Employee Income on the E-
Performance Application is accepted and supported by research data.
The Additional Variable of Employee Income has a t-statistical value of 1,510 < 1.96, and a p value of 0.066 >
0.05. Therefore, the fifth hypothesis that states the influence of Additional Employee Income on Employee
Performance is rejected and is not supported by research data.
Simultaneous testing of the influence of exogenous variables of green human resource management, green
intellectual capital, and environmental commitment on endogenous environmental performance was
performed. In the final testing stage, the effect of exogenous variables on endogenous variables was not
significant, while the influence of mediating variables on endogenous variables was significant. Thus, the
mediating variable was shown to mediate the influence of exogenous variables on endogenous variables.
Table 6.Specific Indirect Effect
Construct
Original
Sample (0)
Sample
Mean (M)
Standard
Deviation
(STDEV)
T Statistics
(|O/STDEV|)
P-
Values
Digital Technology -> E-
Performance Applications ->
Employee Performance
0.041
0.046
0.025
1.643
0.050
Additional Employee Income-> E-
Performance Application ->
Employee Performance
0.066
0.071
0.031
2.110
0.017
In table 6, it can be seen that the influence of Digital Technology variables on E-Performance Applications and
on employee Performance variables is not significant. This means that the E-Performance Application
variable is not able to partially mediate the relationship between Digital Technology and Employee
Performance.
In table 6, it can be seen that the influence of the variable of Additional Employee Income to the E-
Performance Application and to the variable of Employee Performance is significant. This means that the E-
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Performance Application variable is able to partially mediate the relationship between Employee Income
Supplement and Employee Performance.
DISCUSSION
E-Performance Application has a significant positive effect on Employee Performance
The results of the study show that the E-Performance Application has a significant positive effect on Employee
Performance. The results of the empirical analysis show that this hypothesis is supported by data, with a
regression coefficient of 0.221 and a P-value of 0.004. These findings indicate that the direction of the
coefficient influence is positive, and the P-value is below the significance level of 0.05. Thus, it can be
concluded that the E-Performance Application has a significant positive effect on Employee Performance. This
is consistent with the hypothesis put forward earlier, so H1 is acceptable. In addition, the regression coefficient
value of 0.221 shows that every one unit increase in the E-Performance Application variable will be followed
by an increase of 0.221 units in the Employee Performance variable.
The results of the study show that the E-Performance Application has a significant positive effect on Employee
Performance, with a regression coefficient value of 0.221 and a P-value of 0.004 which is below the
significance threshold of 0.05. These findings prove that the use of the E-Performance Application can
improve the quality of employee performance because the existing system supports work processes to be more
directed, measurable, and accountable.
This result is also supported by the large number of Agree and Strongly Agree by the respondents. One
example can be seen in the results of the questionnaire, namely: Based on indicators that e-performance
applications can help increase employee productivity, the majority of respondents said they agreed with 113
people (54.9%) and strongly agreed with 70 people (34%), so that the total approval reached 88.9%.
Meanwhile, 23 respondents (11.2%) chose neutral, and no respondents (0%) voted against or strongly
disagreed. These results show that most employees consider e-performance applications to be effective in
helping to increase work productivity.
The use of Digital Technology has a significant positive effect on E-Performance Applications
The results of the study show that the use of Digital Technology has a significant positive effect on E-
Performance Applications. Based on the results of the analysis, a regression coefficient of 0.187 with a P-value
of 0.010 was obtained. This value is below the significance level of 0.05, so this hypothesis is supported by the
data. Thus, it can be concluded that digital technology has a significant positive effect on e-performance
applications, so H2 is accepted. The regression coefficient value of 0.187 indicates that every one unit increase
in digital technology will be followed by an increase of 0.187 units in the E-Performance Application.
The results of the study show that the use of Digital Technology has a significant positive effect on E-
Performance Applications. This means that the higher the level of use of digital technology by employees, the
more optimal the use of e-performance applications in supporting work processes. This shows that the
readiness and habits of employees in using technology are important factors in the successful implementation
of the E-Performance Application.
These findings are also reinforced by previous research. Uno, Upe, & Firdaus, (2024) found that literacy and
habits of using digital technology have a significant effect on the successful implementation of performance
management information systems in the public sector. In addition, research by Firdaus (2024) emphasizes that
employees' mastery of digital technology increases the effectiveness of using performance-based applications.
Thus, these findings are in line with previous theories and research, thus strengthening that the Use of Digital
Technology has a positive effect on E-Performance Applications.
The use of Digital Technology has a significant positive effect on Employee Performance
The results of the study show that the use of Digital Technology has a significant positive effect on Employee
Performance. The results of the analysis showed a regression coefficient value of 0.166 with a P-value of
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0.029, which is smaller than 0.05. This confirms that the hypothesis proposed is supported by the data, so H3 is
acceptable. With a regression coefficient of 0.166, it can be interpreted that every one unit increase in the Use
of Digital Technology will increase Employee Performance by 0.166 units.
The use of Digital Technology has been proven to have a positive effect on E-Performance Applications. This
shows that the more optimal the use of digital technology in an organization, the more effective the
implementation of electronic-based performance applications. Digital technology supports speed, accuracy,
and information openness which is an important foundation in an e-performance system (Sari et al, 2022).
This result is also supported by the large number of Agree and Strongly Agree by the respondents. One
example can be seen in the results of the questionnaire, namely: Based on indicators of the use of applications
and digital systems in supporting employee work, the majority of respondents gave positive responses, with
125 respondents (60.7%) voting in favor and 65 respondents (31.6%) strongly agreeing, so that the total
approval reached 92.23%. Meanwhile, 16 respondents (7.8%) chose neutrality and no respondents expressed
disagreement or strongly disagreed. These results show that digital applications and systems are considered
very helpful in supporting employee work.
Additional Employee Income has a significant positive effect on the E-Performance Application
The results of the study show that Additional Employee Income has a significant positive effect on the E-
Performance Application. The results of the analysis showed a regression coefficient of 0.298 with a P-value
of 0.000, which is well below the significance level of 0.05. Therefore, this hypothesis is supported by data,
and H4 is acceptable. The coefficient value of 0.298 shows that every one unit increase in Employee Income
Supplement will increase the E-Performance Application by 0.298 units.
Additional Employee Income is a form of incentive given to improve employee motivation, performance, and
discipline. Logically, employees who receive financial rewards will be more motivated to work according to
the rules and targets set. The provision of additional employee income is also a means to encourage employee
compliance in utilizing the E-Performance Application, because the application is used as a basis for assessing
performance achievements which will later be directly related to the amount of additional employee income
received. Thus, the better the employee income supplement system is implemented, the higher the seriousness
of employees in using the E-Performance Application as a form of responsibility and performance reporting.
In line with Sari (2020's research), it shows that providing incentives has a significant effect on compliance
with the use of digital-based performance systems. Another study by Putra and Lestari (2021) found that clear
financial motivation will increase employee involvement in electronic performance recording. In line with that,
Hidayat (2022) emphasized that additional employee income is not only a form of appreciation, but also an
effective control instrument in ensuring that employees report their performance accurately through the
application.
Additional Employee Income does not have a significant positive effect on Employee Performance
The results of the study show that Additional Employee Income does not have a significant positive effect on
Employee Performance. The regression coefficient value obtained was 0.119 with a P-value of 0.066, which is
greater than the significance level of 0.05. This suggests that the hypothesis is not supported by the data, so H5
is rejected. Thus, additional employee income cannot be proven to have a significant effect on Employee
Performance, even though the direction of the resulting regression coefficient remains positive.
Additional Employee Income does not have a significant positive effect on Employee Performance. This can
happen because the main motivation of employees in working is not only from financial factors, but also from
non-financial aspects such as a conducive work environment, leadership, self-development opportunities, and a
sense of responsibility. Several previous studies have also found similar results, for example studies that show
that financial incentives are not always the dominant factor in improving employee performance, but intrinsic
motivation and job satisfaction are more influential (Putra, 2019; Lestari, 2021). Thus, even if additional
employee income is given, it is not necessarily able to significantly improve employee performance.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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Page 8622
In addition, financial incentives tend to have a short-term effect. The provision of Additional Employee
Income can encourage administrative compliance, but it does not automatically improve the quality of work
such as efficiency, innovation, or public services. If Employee Income Supplement is considered a "routine
right", then its motivational value is diminished. The results of this study are consistent with Putra (2019) who
found that intrinsic motivation has more influence on performance improvement than financial incentives.
Lestari (2021) also emphasized that work environment and leadership factors have a more significant role in
improving employee performance than financial factors.
The use of Digital Technology has no effect on Employee Performance through the E-Performance
Application
Based on the results of statistical analysis in the table above, the value of the path coefficient (Original
Sample) is 0.041 with a T-statistical value of 1.643 and a P-value of 0.050. Because the P value is right at the
significance threshold (α = 0.05) and the T-statistics < 1.96, it can be concluded that the Use of Digital
Technology does not have a significant effect on Employee Performance through the E-Performance
Application. Thus, the hypothesis that states the mediation effect of the E-Performance Application is not
supported by data.
The Lack of Influence of Digital Technology on Employee Performance through the E-Performance
Application can be explained that even though digital technology has been used, its use is not always in line
with performance improvement if it is not accompanied by the readiness of individuals and organizations. The
Technology Acceptance Model theory explains that the use of technology will only be effective if it is
supported by perceived usefulness and perceived ease of use. If employees are limited to using technology
without really feeling that it increases productivity, then the effect on performance will be low.
Previous research by Siregar, & Setiyaningsih, (2025) shows that the use of digital technology does not
necessarily improve employee performance if it is not balanced with training, system adaptation, and a
supportive organizational culture. Similarly, the results of research from Harjani (2025) found that the
influence of technology on performance is stronger when there are mediating factors in the form of digital
competence and employee motivation. Therefore, it can be understood that the Use of Digital Technology
through the E-Performance Application does not have a significant effect on employee performance.
Additional Employee Income has a significant effect on Employee Performance through the E-
Performance Application
Based on the results of the analysis in the table, the value of the path coefficient (Original Sample) was 0.066
with T-statistics of 2.110 and P-value of 0.017. Because the P value < 0.05 and the T-statistics > 1.96, it can be
concluded that Additional Employee Income has a significant effect on Employee Performance through the E-
Performance Application. This means that the incentives or additional income received by employees
encourage them to make more use of e-performance applications, which ultimately improves performance.
Theoretically, this can be explained through the Expectancy Theory Vroom which states that employee
motivation is influenced by the expectation that their efforts will result in good performance, which in turn will
result in rewards or rewards. Additional income is a motivational factor that strengthens the relationship
between the use of the E-Performance Application and the improvement of employee performance. With clear
rewards, employees are more encouraged to make optimal use of e-performance applications, so that the
process of assessing and recording performance becomes more effective.
These results are also supported by previous research. Research by Sukarini (2025) found that financial
incentives play an important role in encouraging employees to use digital performance systems, which in turn
contributes to increased productivity. In addition, Astawan's research (2025) shows that the provision of
additional income is positively related to increased utilization of performance-based applications, because
employees feel that their efforts are appreciated through compensation. Thus, it can be emphasized that
Additional Employee Income through the E-Performance Application significantly affects employee
performance
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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Page 8623
CONCLUSION
Based on the results of data analysis and discussion, several conclusions can be drawn as follows:
1. The use of Digital Technology has been proven to have a significant positive effect on E-Performance
and Employee Performance Applications. This shows that the use of digital technology supports the
effectiveness of e-performance applications and increases employee productivity.
2. The E-Performance application has a significant positive effect on Employee Performance, which
indicates that this system plays an important role in facilitating performance evaluation, transparency,
and accountability.
3. Additional Employee Income has a significant positive effect on the E-Performance Application, but not
significantly on Employee Performance directly. This means that Employee Income Supplement
functions more as a motivator for the use of the E-Performance Application than a direct driver of
performance.
4. The E-Performance application acts as a significant mediator between Employee Income Supplement and
Employee Performance, but not for the Use of Digital Technology and Employee Performance. This
shows that financial incentives affect performance through the use of E-Performance Applications, while
the influence of digital technology on performance does not have to be through E-Performance
Applications.
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