The Challenges Faced by the Information System in the Era of
Industry 4.0 and Their Impact on Information Quality
Fahmi Dwi Suhenda, Anastasya Regina Candra and Rapina Rapina
a
Department of Accounting, Maranatha Christian University, Bandung, Indonesia
Keywords: Internal Control System, Personality Characteristics, Organizational Structure, Business Process Quality.
Abstract: The importance of business process quality is widely recognized, it is a complex concept with significant
weight. When the quality of this process is poor, it has the potential to cause the information system to fail
and, as a result, contribute to a decline in the quality of information. The purpose of this research is to
investigate and assess the impact of internal control systems, personality characteristics, organizational
structure, and business process quality on the quality of the accounting information system, as well as the
impact of accounting information system quality on the overall quality of accounting information. The survey
questionnaire was filled out by 80 participants using purposeful sampling, a non-random sampling technique.
A variance-based structural equation model (SEM) was used to analyze the collected data. SEM is a statistical
method that is commonly used to analyze variable relationships and test hypotheses in complex models. The
research's primary finding contends that the effectiveness of internal control system, personality
characteristics, organizational structure, and business processes significantly and favorably influences the
effectiveness of the quality of accounting information system. The study's second key finding suggests that
the quality of the organization's information system has a significant influence on its overall information
quality.
1 INTRODUCTION
The banking sector must undergo a digital
transformation because the banking world is
undergoing multiple changes, particularly as we reach
the 4.0 era, when banks must now keep up with
technological improvements to remain competitive
(Maulidya, 2021). The digital era is closely linked to
changes in the lifestyle of the Indonesian population,
with technology increasingly facilitating banking.
The absence of real cash in today's world is a notable
difference, as all payments are made using virtual
money (Rapina, 2021).
As indicated by the new Financial Services
Authority Regulation (POJK) No. 12/POJK.03/2021
on the Implementation of Digital Banking Services,
banking services can be improved through digital
banking and capitalizing on opportunities in the
industrial revolution period. The Financial Services
Authority (OJK) has published the regulatory
framework for digital banks, with the head office
functioning as the physical branch and the rest,
a
https://orcid.org/0000-0002-0452-0201
referred to as smart branches, operating online. The
move to digital banking is a vital transformation for
all banking institutions since it requires them to adapt
to changes in human lifestyle, consequently boosting
the quality of banking performance (Maulidya, 2021).
The state-owned banks that are undergoing a digital
banking transformation, such as Mandiri, BNI, BRI,
and BTN, are still striving to enhance their information
systems to enhance integration. This allows for the
creation of clearly understandable information for
management objectives (Kurniawan, 2017).
The problems in Indonesia are characterized by
phenomena related to accounting, particularly the
implementation of accounting information systems.
Occurrence in state-owned banking occurred in 2021
at Bank Mandiri's Mampang Prapatan Branch, where
a frontline embezzled 120 billion (Simanjuntak,
2021). Lax internal controls at the Area level (one
level above the Branch), where there was little
personnel rotation or movement of supervisors and
frontline staff who had worked in the same unit for
four years, were the root cause of this occurrence,
Suhenda, F., Candra, A. and Rapina, R.
The Challenges Faced by the Information System in the Era of Industry 4.0 and Their Impact on Information Quality.
DOI: 10.5220/0012697300003798
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 2nd Maritime, Economics and Business International Conference (MEBIC 2023) - Sustainable Recovery: Green Economy Based Action, pages 195-205
ISBN: 978-989-758-704-7
Proceedings Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.
195

according to an internal audit. The organizational
culture still tolerated certain individuals sharing
passwords without focusing on security, especially in
the Branch Delivery System (BDS) software. As a
result, staff abused the Accounting Information
System (AIS), lowering its quality. Because the
incident was hushed up, the data at the Branch did not
match what was reported to the Area.
The dominance of BDS (Branch Delivery
System) in the banking sector, especially among
state-owned banks, will be in 2023. However,
because of the enormous data access, each task
performed by BDS takes a long time. For example,
updating the status of delinquent customers from
"current" to "written-off" at the end of each month
takes 5 minutes per client (if there are 50 customers x
5 minutes = 4.5 hours to execute this process). This
takes a significant amount of time and has an impact
on the quality of business processes because it is only
done at the end of the month. Furthermore, BDS
contains a flaw in the input procedure that
necessitates double entry, increasing the danger of
human mistake. This leads to poor information
system quality and inconsistencies between physical
records and BDS software entries.
The phenomenon mentioned above indicates that a
number of factors, such as internal controls (the
inability of the banking institution to implement
internal controls, which results in illicit behaviors like
the sharing of BDS passwords), can affect the quality
of the AIS (Accounting Information System).
Moreover, organizational structure (the organization
already has an adequate organizational structure, but in
the context of the phenomenon above, organizations in
branch offices or in the regions are still not fully
informed in detail regarding the authority possessed by
the board of directors at the head office); personality
characteristics (both subordinate and superior
employees do not yet have the principle that sharing
passwords is a prohibited activity so that it violates the
principle of conscientiousness or prudence); and the
quality of business.
The quality of decision-making processes can be
improved by accounting information as processed
data (Bodhar, 2014; Romney, 2018). Accounting
information is provided to organizational decision-
makers (Considine, 2012). The definition of high-
quality accounting information is that it has features
that make it more useful (O'Brien, 2014). Timeliness,
accuracy, and completeness are characteristics of
high-quality accounting information (Baltzan, 2014;
Romney, 2018).
Internal controls have an impact on the quality of
AIS (Kurniawan, 2017; Rashedi, 2019).
Organizational structure influences the quality of AIS
(Kuraesin, 2016; Wisna, 2015). The quality of business
processes influences the quality of AIS (Sari, 2015).
AIS quality is influenced by AIS quality (Al-Hiyari,
2013; Darma, 2020; Sajady, 2008). The referenced
study's extra variable is "internal controls," and the
population used comprises of all state-owned banking
companies in West Java. The previous study serves as
the main reference journal, and the unique feature is
that an additional variable of the internal control
system serves as an independent variable (Rapina,
2021). Furthermore, the researchers concentrate their
investigation on the AIS of state-owned banks, notably
the BDS or Branch Delivery System.
The researcher determines the following research
limits based on the reasoning above. The AIS in
question is the BDS software version 11.00.00, which
was upgraded on March 15, 2023. The BDS hardware
cannot be updated because of the limitations in the big
data migration process, which could result in
company losses if the data migration process is
unsuccessful. OTIs (Operational Technical
Instructions) are in effect until December 20, 2022.
Employees who run the BDS are the topic of
personality traits. Customers or borrowers are not
included in this study because it is only for personnel
who operate the BDS. The purpose of this study was
to determine how much the internal control system,
personality traits, organizational structure, and
business process quality on the quality of the
accounting information system and its impact on the
quality of accounting information. This study
contributes to factors that can affect the
implementation of accounting information systems,
resulting in quality accounting information.
Furthermore, this research is expected to help solve
problems that occur in the field of accounting for
organizations in Indonesia.
2 THEORETICAL REVIEW
2.1 Accounting Information Systems
The Industry 4.0 revolution, also known as the
"cyber-physical system," is a phenomenon that arises
when cyber technology and automation technology
collaborate. This revolution causes major changes in
a variety of industries. Many things have changed as
a result of the birth of this revolution in numerous
areas. What used to require a large personnel for
operations is now replaced by the use of technological
machines (Rashedi, 2019). The internet of things, big
data, augmented reality, cybersecurity, and artificial
MEBIC 2023 - MARITIME, ECONOMICS AND BUSINESSINTERNATIONAL CONFERENCE
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intelligence are examples of technology used in the
Industry 4.0 revolution. AIS is a component of the
Industry 4.0 revolution, and it includes big data and
cybersecurity (Rashedi, 2019).
AIS plays a critical role in providing information
that assists management in developing organizational
strategies to meet an organization's goals. The quality
of an organization's information system can be used
as a indicator of how well it meets its goals, according
to many studies.
The accounting system employed by state-owned
banks, notably the Branch Delivery System (BDS), is
the subject of the investigation. BDS is a computer-
based accounting system that allows banks to execute
financial and non-financial operations online. BDS is
the fundamental operational banking service,
consisting of menus based on transaction codes.
Banking transactions are completed using BDS with
diverse transaction types in major cities.
However, BDS utilization optimization is less
typical in smaller locations due to fewer transactions.
The BDS system is utilized by bank employees for
their daily work activities. Given that BDS is a
critically important system for banking operations,
the manner of utilizing BDS follows specific
procedures or protocols aligned with the policies of
each bank. BDS has the ability to generate accurate
information that can be used by top management for
decision-making to achieve organizational goals.
The researcher will investigate variables that can
boost the performance of BDS, which will result in
high-quality information for decision-makers
according to the above description.
The BDS workflow is comprised of three
(3)processes: (1) the morning process known as
"branch opening," in which the system is activated by
the branch manager or authorized user to allow
normal operations; (2) the daily transaction process,
in which frontliners provide services to customers
under various conditions; and (3) the end-of-day
process, also known as "branch closing," in which the
branch manager is required to physically reconcile the
cash in the vault with the n The branch closing
process can begin after the physical and non-physical
monies are in sync (Cahyaning, 2016).
2.2 Internal Control System in AIS
Quality
ICS is a collection of guidelines and practices intended
to prevent misappropriation of the company's
resources, guarantee the availability of correct
corporate accounting data, and guarantee that all staff
members have followed or implemented management
policies and laws in a proper manner. (Tresyani, 2019).
ICS is a process driven by the board of directors,
management, and employees that aims to ensure that
organizational goals are met (Rashedi, 2019).
The control environment, risk assessment,
information and communication, and monitoring are
the four fundamental components of policies and
procedures designed and implemented by
management to provide reasonable assurance that
control objectives can be met (Tresyani, 2019).
When an organization maintains a system that
generates high-quality information, its goals can be
achieved. The application system must have control
over transaction processing to ensure that internal
control components are implemented. The internal
control system is designed to guarantee the system's
completeness, including detecting input errors and
rejecting requests. It also guarantees that data
processing is in accordance with the desired criteria or
requirements and that the output is suitable for
distribution to senior management (Kurniawan, 2017).
Based on the above description, it can be
concluded that the internal control system has an
impact on the quality of AIS, similar to previous
research (Anuruddha, 2021; Kurniawan, 2017;
Rashedi, 2019).
H1: Internal Control System (ICS) influences the
Quality of AIS.
2.3 Personality Traits in AIS Quality
The behaviors of individuals in their daily activities
are characterized by personality traits that are formed
by various interconnected factors. Every employee
who works in an organization should possess these
traits as they can enhance their abilities in performing
their tasks. One of the tasks carried out in the Industry
4.0 era is the utilization of technology.
The use of technology must be comprehended as
it holds significant importance in the field of
information systems, accomplished by exploring the
role of personality: the Five Factor Model of
Personality (Openness, Agreeableness,
Conscientiousness, Extraversion, and Neuroticism).
The formation of a working team that aligns the
information system with personality types, as
outlined by Lea et al. research, is essential to achieve
optimal performance. (2019), where the Five Factor
Model of Personality can influence information
systems (Rapina, 2021).
Individuals with creativity can identify the
system's current strengths and faults (Simanullang,
2021). When a case needs to be escalated to the next
level of leadership, the system should simply align
The Challenges Faced by the Information System in the Era of Industry 4.0 and Their Impact on Information Quality
197

itself (Pramasella, 2019). Making exact decisions
requires exercising caution while operating the
system (Ernawati, 2019). The system is easy to
socialize for new users who are using it for the first
time. The system's operation should be based on
emotional experiences, developing an anticipating
mindset (Najm, 2019). Individuals must possess the
Five Factor Model of Personality as employees of any
business, particularly in this research environment of
state-owned banking, in order to operate the system
and create quality information. The researcher
restricted the personality traits explored in this study
to those that are necessary for personnel in the
banking industry.
The study conducted by Rapina (2021) explores
the influence of personality traits on the quality of
accounting information systems. Furthermore,
research examining the Five Factor Model of
Personality has been previously investigated by
(Ernawati, 2019; Pramasella, 2019; Simanullang,
2021). According to the second hypothesis of this
study, the quality of AIS is influenced by personality
traits, as described above.
H2: Personality Traits influence the Quality of
AIS.
2.4 Organizational Structure in AIS
Quality
The formal arrangement of duties, responsibilities,
and authority within an organization is called
organizational structure (McShane, 2015). The roles
and responsibilities of persons and groups associated
with the execution and supervision of interrelated
activities aimed at accomplishing organizational
goals are referred to as organizational structure
(Kuraesin, 2016). Organizational structure as having
three dimensions: span of control, centralization, and
formalization (McShane, 2015).
In organizational structure, the number of
employees can influence the system being used, but
managers in the organization must be able to control
these employees so that the system can operate as
intended (Kuraesin, 2016). The center of authority
related to the organizational system belongs to
managers (Kuraesin, 2016). The system's procedures
and rules must be consistent from the head office to
the smallest branches (Ghozali, 2018). With a well-
established organizational structure, it will result in
quality AIS (Kuraesin, 2016).
The creation of information systems requires
consideration of organizational structure as it affects
the implementation of AIS (Kuraesin, 2016). The
organization's structure can improve information
availability by spreading information to multiple
levels, giving employees at the lowest level the
opportunity to contribute to decision-making
(Bodhar, 2014).
According to the preceding definition, the third
hypothesis of this study is that organizational
structure influences the quality of AIS. (Rapina,
2021) did previous research with a random sample of
46 organizations, while (Kuraesin, 2016; McShane,
2015) conducted research revealing the influence of
organizational structure on AIS quality.
H3: Organizational Structure influences the
Quality of AIS.
2.5 Business Process Quality in AIS
Quality
Quality of business processes is the interrelated
business activities that result in products or services for
consumers. These processes can be repeated to achieve
optimal outcomes, or they can focus on maximizing a
specific process that is currently occurring (Kuraesin,
2016). The importance of business process quality is in
providing services that are convenient for employees
and don't take up customers' time. The produced
products should align with management's objectives
(Romney, 2018). Business process quality is reflected
in the waiting time for each transaction within the
organization's system. Each task has a different waiting
time based on the complexity of the performed work
(Rapina, 2021).
The information system can be influenced by the
business processes of the organization (Rapina,
2021). The quality of AIS can be enhanced through
existing business processes; a good business process
should be well-structured, and organizational
procedures should be observed based on real-life
occurrences, enabling the business process to be of
high quality.
A successful business process should have
defined objectives, inputs, outputs (within the system
being used), and resource utilization. It includes
multiple operations at various levels and can affect
more than one unit within the firm, compromising the
quality of both the business process and the AIS
(Kuraesin, 2016).
Based on the description above, the fourth
hypothesis of this study is that the quality of business
processes affects the quality of AIS, in line with
previous research (Kuraesin, 2016; Rapina, 2021).
H4: The quality of business processes has an
impact on the quality of AIS.
MEBIC 2023 - MARITIME, ECONOMICS AND BUSINESSINTERNATIONAL CONFERENCE
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2.6 Quality of AIS in Accounting
Information Quality
AIS uses a procedure to collect and turn data into
accounting information. Financial information is data
that has been processed to generate the financial AIS
process. (Darma, 2020) defines this process as the
processing of financial accounting information. For
first-time users, the system should be simple to use
(Ahmed, 2019). It should have freedom within its
constraints; a system with constraints that is escalated
to senior management due to exceptions shows
flexibility (Ahmed, 2019). The system's records
should include data that will be subject to audits, and
inputting data once should provide efficient
information, reducing human errors (Tresyani, 2019).
The output should be efficient in terms of time and
user-friendliness. To guarantee confidentiality, the
information should be maintained in a single location
(database), and it should be presented in the form of
diagrams. High-quality accounting information can
be produced by AIS that adheres to the concepts of
usability, adaptability, auditability, and security
(Darma, 2020).
The fifth hypothesis of this study is that the
quality of AIS influences the quality of accounting
information, according to (Ahmed, R., 2019,
McShane, S. G. M. Von., 2015, Rapina, 2021,
Sugiyono., 2014).
H5: The Quality of AIS Affects the Quality of
Accounting Information.
Accounting information that is timely and up to
date is available when needed (Cahyaning, E. K.,
2016). On the other hand, accurate accounting
information is free of inaccuracies and accurately
reflects current conditions (Anuruddha, S., 2021).
The quality of accounting information is a feature that
accounting information must have in order to suit the
needs of users McShane, (S. G. M. Von., 2015).
Accuracy, completeness, and timeliness are all
aspects of information quality. Accuracy,
completeness, and timeliness are all hallmarks of
high-quality information (Considine, 2012). The
quality of information is measured by its timeliness,
accuracy, and completeness (Cahyaning, E. K.,
2016). Quality information as having properties such
as correctness, timeliness, and completeness. The
quality of the information produced by the
information system determines the success of the
information system in SIA. SIA acts as a middleman
or instrument to actualize information, allowing
project managers and staff working at the company's
organizational level to make educated decisions.
The model or framework of thought is presented
in the following diagram based on the hypotheses
above. This is also a novelty of the research
conducted, because researchers have not found all
variables to be studied together.
Figure 1: Research Model or Framework.
3 RESEARCH METHOD
A data gathering strategy is to provide written
statements to respondents and ask them to answer
truthfully. Online media such as Google Forms or
physical questionnaires given directly to respondents
are utilized to distribute questionnaires. Respondents
in this survey are workers of state-owned banks,
specifically BMRI, BBNI, BBRI, and BBTN.
Because the questionnaire takes the form of
multiple-choice answers that vary (not equidistant
values from 1 to 5), the scale employed for this
research is an interval scale. The respondents were
given statements with numerical values that
corresponded to their levels (Sugiyono, 2014).
Control environment, risk assessment,
information and communication, and monitoring are
the components of the SPI variable. These criteria
were selected because a good control system needs to
have standard operating procedures and procedural
policies in order for a bank-made system to function.
Then, the dimensions of personality traits, namely
openness, agreeableness, conscientiousness,
extraversion, and neuroticism, were selected because
these five personalities are related to one another,
making it very appropriate for employees who
operate the system to form these five personality
traits. Then the dimensions of the organizational
structure are span of control, centralization and
formalization, the reason for choosing these
dimensions is because banking is a company that has
clear responsibilities and authorities so that clear
tasks will result from the company's organizational
structure. Then the dimension of the business process
quality variable is the length of time waiting, the
reason for choosing this dimension is because a
The Challenges Faced by the Information System in the Era of Industry 4.0 and Their Impact on Information Quality
199

system that runs work programs properly is a system
that minimizes waiting time. Then the reason the
researcher chose the flexibility dimension in the SIA
quality variable is because the BDS system can be
escalated to the leadership to determine policies, and
timeliness, data accuracy and data completeness as
one of the principles of information to facilitate
decision makers.
Table 1: Operationalization of Variables.
Variable
Dimension
Indicator
Internal Control
System
Meilani (2017)
Control Environment
Management Control
Division of taks
Authority
Responsibility
Risk Assesment
Procedure Policy
Information &
Communication
Standard Operating
Procediure
Monitoring
Review
Personality Traits
Barnet et al. (2015)
Openness
Openness to New
Experience
Agreeableness
Avoid Conflict
Conscientiousness
Caution in carrying
out an action
Extraversion
Interaction with
others
Neuroticism
Negative Emotional
Expérience
Organizational
Structure
Mc Shane, et al.
(2015)
Control Range
Controllable
Centralization
Centralized
Organizational
Activities
Formalization
Development Process
Notice
Business Process
Quality
Romney & Steinbart
(2018)
Long Waiting Time
No long waits
Just one time input
Work just got easier
Minimizing human
error
AIS Quality
Romney & Steinbart
(2018)
Utility
Processing
Information
Output
Optimizing Resouces
Improve the
Performance
Ease of Use
It is useful
Flexsibility
Flexsibility
Auditability
Auditability
Security
Hardware
Accounting
Information Quality
Baltzan (2014)
On Time
Real Time
Accurate
Tested
Complete
Output
SEM PLS is a data analysis method that the author
uses to analyze the relationship between variables
(Sugiyono, 2014). The outer model consists of a
validity test using convergent validity > 0.7, it is said
to be high, as well as the average variance extracted
(AVE) value and communality value > 0.5 (Ghozali,
2018), then discriminant validity can be seen from the
measurement of the cross loading factor with the
construct and comparison of average variance
extracted (AVE) roots with latent variable correlations
(Ghozali, 2018). After that, the reliability test used
Cronbach's alpha > 0.6 (Ghozali, 2018). The
relationship between the independent and dependent
variables is examined using a t test (hypothesis testing)
that is carried out both partially by Suiyono (2014).
4 RESEARCH FINDINGS
There are 30 manifest variables with 6 latent variables
including Internal Control Systems, Personality
Characteristics, Organizational Structure, and
Business Process Quality (X); AIS Quality (Y) and
Accounting Information Quality (Z), with the help of
smartPLS 3 with the following model.
Figure 2: Research Model.
The PLS Algorithm menu in the image below is
then used to provide the calculation results for the
whole bootstrapped model.
Figure 3: Complete PLS Algorithm Research Model.
Additionally, two validity tests must be
performed: convergent validity and discriminant
validity.
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4.1 Convergent Validity
Table 2: Loading Factor.
Manifest
Variable
Loading
Factor
Standard Value
Conclusion
SPI_1
0.981
0.700
Valid
SPI_2
0.976
0.700
Valid
SPI_.3
0.759
0.700
Valid
SPI_4
0.942
0.700
Valid
SPI_.5
0.921
0.700
Valid
SPI_6
0.777
0.700
Valid
SPI_.7
0.820
0.700
Valid
KK_1
0.878
0.700
Valid
KK_2
0.946
0.700
Valid
KK_3
0.794
0.700
Valid
KK_4
0.857
0.700
Valid
KK_5
0.773
0.700
Valid
SO_1
0.975
0.700
Valid
SO_2
0.981
0.700
Valid
SO_3
0.925
0.700
Valid
KPB_1
0.865
0.700
Valid
KPB_2
0.880
0.700
Valid
KPB_3
0.899
0.700
Valid
KPB_4
0.797
0.700
Valid
KPB_5
0.907
0.700
Valid
KPB_6
0.917
0.700
Valid
KSIA_1
0.723
0.700
Valid
KSIA_2
0.882
0.700
Valid
KSIA_3
0.881
0.700
Valid
KSIA_4
0.893
0.700
Valid
KSIA_5
0.767
0.700
Valid
KSIA_6
0.906
0.700
Valid
KSI_1
0.818
0.700
Valid
KSI_2
0.883
0.700
Valid
KSI_3
0.721
0.700
Valid
According to the chart above, all 30 manifest
variables are determined to have good validity
because the loading factor value is higher than the
standard value (Sugiyono, 2014).
All variables are deemed to be legitimate because
the AVE value and composite reliability of the 6 (six)
latent variables are both > 0.5 (Ghozali, 2018).
Table 3: Average Variance Extracted and Composite
Reliability.
Latent Variable
AVE
CR
Standard
Value
Conclusion
Internal Control
System
0.786
0.962
0.500
Valid
Personality
Characteristics
0.726
0.929
0.500
Valid
Struktur Organisasi
0.923
0.973
0.500
Valid
Business Process
Quality
0.772
0.953
0.500
Valid
AIS Quality
0.714
0.937
0.500
Valid
Accounting
Information Quality
0.658
0.852
0.500
Valid
4.2 Discriminant Validity
Table 4: Croos Loading Factor.
Items
SPI
KK
SO
KPB
KSIA
KIA
SPI_1
0.981
0.040
0.016
0.123
0.061
-0.087
SPI_2
0.976
0.058
0.052
0.149
0.099
-0.058
SPI_3
0.759
0.011
-0.015
0.079
-0.026
-0.103
SPI_4
0.942
0.121
0.070
0.165
0.056
-0.133
SPI_5
0.921
-0.014
0.038
0.060
0.029
-0.203
SPI_6
0.777
-0.027
-0.001
0.122
0.004
-0.067
SPI_7
0.820
-0.013
0.016
0.093
0.017
-0.025
KK_1
-0.087
0.878
0.363
0.062
0.155
0.323
KK_2
-0.058
0.946
0.264
0.060
0.313
0.181
KK_3
-0.103
0.794
0.182
-0.023
0.197
0.089
KK_4
-0.133
0.857
0.394
0.029
0.115
0.285
KK_5
-0.203
0.773
0.231
0.036
0.123
0.208
SO_1
-0.067
0.061
0.975
-0.118
-0.034
0.080
SO_2
-0.025
0.099
0.981
-0.065
-0.034
0.047
SO_3
0.323
-0.026
0.925
-0.125
-0.014
0.064
KPB_1
0.181
0.056
0.123
0.865
0.061
0.084
KPB_2
0.089
0.029
0.149
0.880
0.116
0.074
KPB_3
0.285
0.004
0.079
0.899
0.073
0.084
KPB_4
0.208
0.017
0.165
0.797
0.214
0.074
KPB_5
0.080
0.155
0.060
0.907
0.184
0.148
KPB_6
0.047
0.313
0.122
0.917
0.184
0.084
KSIA_1
0.064
0.197
0.093
0.016
0.723
0.043
KSIA_2
0.084
0.115
0.062
0.052
0.882
0.264
KSIA_3
0.074
0.123
0.060
-0.015
0.881
0.148
KSIA_4
0.084
-0.034
-0.023
0.070
0.893
0.084
KSIA_5
0.074
-0.034
0.029
0.038
0.767
0.043
KSIA_6
0.148
-0.014
0.036
-0.001
0.906
0.264
KSI_1
0.084
0.061
-0.118
0.016
0.214
0.818
KSI_2
0.043
0.116
-0.065
0.363
0.184
0.883
KSI_3
0.264
0.073
-0.125
0.264
0.184
0.724
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201

It may be deduced that the indicators used to measure
latent variables have complied with the requirements
since the CLF value of the manifest variable is higher
than the CLF values of the other manifest variables,
or in other words, the numbers in the yellow shading
are greater than the numbers in the blue shading.
Additionally, the test that needs to be run is a
reliability test called Cronbach's alpha.
The Cronbach's alpha value of the 6 (six) variables
is greater than 0.7, meaning that all latent variables
are reliable. Since the ke-6 (six) variation's nilai
cronbach's alpha is more than 0.7, all previous
variations are now reliable.
Criterion I:
H
0
: SPI / KK / SO / KPB does not affect AISQ or
AISQ does not affect AIQ
H
1
: SPI / KK / SO / KPB affect AISQ or AISQ affects
AIQ
Criterion II:
Reject H
0
: P Values are smaller than the significance
level of 0.05 (5%).
Criterion III:
Reject H
0
: t stat. greater than t table.
The value of the t table is 1.989, and the t statistics
and P values can be used to assess if the factors under
research have an influence or have the opposite effect.
As a result, the hypothesis testing's conclusion is as
follows.
a. Internal Control System's t Statistics value for AIS
Quality is 6.532 > 1.989, and the p value is 0.000
< 0.05 (5%). The conclusion that the Internal
Control System can affect AIS Quality follows
from the rejection of H
0
.
b. Personality Characteristics' t Statistics value in
relation to AIS Quality is 2.717 > 1.989, and the
p-value is 0.007 < 0.05. H
0
is therefore rejected,
proving that personality traits can affect AIS
quality.
c. The organizational structure's t statistics value for
AIS quality is 6.605 > 1.989, and the p value is
0.000 < 0.05. Inferring that Organizational
Structure can affect AIS Quality, H
0
is therefore
rejected.
d. The Business Process Quality t Statistics value for
SIA Quality is 6.873 > 1.989, and the p values are
0.000 < 0.05. Thus, H
0
is refuted, confirming the
conclusion that Business Process Quality can
affect AIS Quality.
e. The p value is 0.002 < 0.05 and the t Statistics value
of the AIS Quality towards Information System
Quality is 3.043 > 1.989. In light of H
0
's rejection,
it may be concluded that AIS Quality can affect
Information System Quality.
Table 5: CA.
Latent
Variable
CA
Standard
Value
Conclusion
Internal Control System
0.969
Must be
greater than
0.700
Reliable
Personality Characteristics
0.907
Reliable
Organizational Structure
0.961
Reliable
Business Process Quality
0.945
Reliable
AIS Quality
0.921
Reliable
Accounting Information
Quality
0.756
Reliable
Table 6: t-Test.
Information
t
Statistics
t Tabel
Results
P Values
Results
SPI →
KSIA
6.532
1.989
H
0
is
rejected
0.000 <
0.05
Sig.
KK →
KSIA
2.717
1.989
H
0
is
rejected
0.007 <
0.05
Sig.
SO →
KSIA
6.605
1.989
H
0
is
rejected
0.000 <
0.05
Sig.
KPB →
SIA
6.873
1.989
H
0
is
rejected
0.000 <
0.05
Sig.
KSIA
→ KIA
3.043
1.989
H
0
is
rejected
0.002 <
0.05
Sig.
5 DISCUSSION
5.1 Internal Control System Towards
AID Quality
Based on the data processing results above, H
0
is
rejected because the obtained p values are greater
than the calculated t value (6.532 > 1.989), indicating
that the Internal Control System (ICS) influences AIS
quality, which is consistent with previous research by
(Anuruddha, 2021; Kurniawan, 2017; Rashedi, 2019;
Tresyani, 2019). The goals of the organization can be
achieved when high-quality information is produced
by upholding a system that was put in place by the
organization to make sure that internal control
components are integrated into the application
system. As a result, control over transaction
processing is required. Internal control systems are
designed to guarantee the system's completeness by
preventing or detecting input errors, which can result
in the system rejecting such requests. Furthermore,
they ensure that data processing was carried out in
accordance with the desired criteria or requirements,
and that the outputs are suitable for distribution to top
management (Kurniawan, 2017).
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5.2 Personality Characteristics
Towards AID Quality
Based on the data processing results above, H
0
is
rejected since the acquired p values are more than the
calculated t value (2.717 > 1.989), showing that AIS
Quality influences Personality Characteristics. This is
consistent with prior studies which found that
personality traits measured using the Five-Factor
Model of personality (OACEN) can influence AIS
quality (Ernawati, 2019; Najm, 2019; Pramasella,
2019; Simanullang, 2021). The Five-Factor Model of
personality can be utilized to create a quality
accounting information system. The task of reviewing
all aspects of employment is not fully accommodated
by the banking company's accounting information
system (AIS) application. The reason for this
situation is that only the person responsible for
examining input results from other departments is
conducting the re-examination. The work outcomes
are only authorized by a supervisor when a customer,
for example, opens a new account through customer
service or transfers money through a teller.
Individuals in positions higher than the supervisor,
such as branch managers, do not participate in
approving the operations of customer service or teller,
despite the fact that they all perform the same duty as
users of the accounting information system.
Furthermore, the installed accounting information
system (AIS) does not adequately accommodate to
the strong and diligent desire to understand the
accounting information system. Customer service and
tellers, for example, should have a strong and
conscientious motivation to master the application of
accounting information systems. It has been found
that the accounting information system used by the
vast majority of commercial banks is frequently
updated in other areas, like the consumer card
division, necessitating constant adjustment on the part
of users. The workflow is hampered by these updates,
which frequently make users tired of learning. Based
on the description given, it can be inferred that the
higher the quality of the accounting information
system is, the more personality traits it can
accommodate.
5.3 Organizational Structure Towards
AID Quality
Based on the data processing results above, H
0
is
rejected since the acquired p values are more than the
calculated t value (6.605 > 1.989), showing that
Organizational Structure impacts AIS Quality. This is
congruent with the findings that organizational
structure is an important factor to consider when
creating information systems (Sari, 2015; Yanti,
2022). The adoption of AIS is influenced by
organizational structure because it improves
information availability by dispersing it across
multiple levels within an organization. This allows
employees at lower levels to participate in decision-
making. The accounting information system (AIS)
has not been able to fully incorporate job
specialization into the organizational framework.
Using an accounting information system requires
breaking down procedures into a list of necessary
actions. The bulk of commercial banks clearly divide
work across separate departments. The functions of a
customer support agent and a teller are distinct, and
they cannot switch roles. There is a physical barrier
between the customer service area and the teller area,
and the programs they use have different passwords
depending on whether they are a teller or a customer
care representative. Furthermore, it is well recognized
that the accounting information system (AIS)
application has not accommodated employees'
relevant responsibilities based on their
specializations. The reason for this is that most
commercial banks still use distinct programs for
branch offices, retail risk divisions, commercial
divisions, and consumer card divisions. As a result,
the accounting information system has been unable to
provide the essential data automatically when
generating reports. Manually combining data from
several accounting information system programs
used across various divisions is still necessary for
some reports to be created.
5.4 Business Process Quality Towards
AIS Quality
Based on the data processing results above, H
0
is
rejected since the acquired p values are more than the
calculated t value (6.873 > 1.989), showing that
process quality can influence AIS quality. The
findings that business procedures can influence
information systems (Rapina, 2021) are similar to this
one. The quality of AIS can be enhanced by the
existing business processes, which should be well-
structured and monitored based on real-world events
to ensure the quality of business processes. The
appropriate processing time is reflected in the AIS
application. This is due to data retrieval delays from
the AIS application, as they compete for processing
time with the Central and Eastern Indonesia regions.
Longer processing durations result from the
increasing amount of data extracted. The processing
timeframes of the accounting information system
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203

application support other actions, like inter-branch
fund transfers. There are two transfer options: LLG
(Lalu Lintas Giro) and RTGS (Real Time Gross
Settlement), and both forms of transfers arrive at the
target bank on the same day, though at a different
charge. Waiting times also fluctuate between
commercial banks, depending on their rules. For
example, the needed waiting time in the accounting
information system application for opening new
client accounts ranges from 5 minutes to up to 20
minutes. This is dependent on how the accounting
information system application handles client data
entry, especially when consumers are asked
confirmation questions ranging from simple to
sophisticated queries.
5.5 AIS Quality Towards Accounting
Information Quality
Based on the data processing results above, H
0
is
rejected since the acquired p values are more than the
calculated t value (3.043 > 1.989), indicating that
accounting information quality is influenced by AIS
quality. This is consistent with previous study who
found a link between AIS quality and accounting
information quality (Abidin, 2021; Darma, 2020;
Rapina, 2021; Sari, 2015; Tresyani, 2019). An AIS
that adheres to criteria such as usability, adaptability,
auditability, and security can generate high-quality
accounting data. In other words, AIS quality can
influence accounting information quality based on
these characteristics.
The accounting information system (AIS)
application has not been fully developed due to the
challenges in commercial banks in obtaining
information from multiple functional areas.
Integration, for example, has not been realized in the
credit card and loan divisions. For example, if a
customer has a business loan for billions of rupiah and
then wishes to apply for a credit card, they must do so
as a new customer because their identity cannot be
traced inside the credit card section. In other words,
the accounting information system applications that
are now in use in banking have not been integrated
nicely with other departments.
6 CONCLUSION
Based on the theory that has been described, the
research hypothesis, and the results of the study, it is
known that:
1. The effectiveness of accounting information
systems is significantly impacted by internal
control systems. The phenomenon that
exemplifies this has been reported by
(Simanjuntak, 2021), involving the
misappropriation of 120 million dollars in client
funds by frontline. A high-quality AIS can be
attained when the internal control system is built
to ensure the completeness that is inherent in the
system itself, for example, by protecting against
or identifying input errors and refusing such
requests. Additionally, it guarantees that data
processing adheres to the necessary standards or
criteria and that the output is appropriate for
presenting to upper management.
2. Personality characteristics have a big impact on
how well accounting information systems work.
(Simanjuntak, 2021) describes a phenomenon in
which some people continue to share passwords
without thinking about security, particularly
when it comes to the Branch Delivery System
(BDS) software. Employee misuse of the
Accounting Information System (AIS) therefore
reduced the system's quality. The information at
the Branch did not match what was reported to
the Area since the incident was kept quiet. The
Five-element Model of Personality (OACEN),
which each element has a distinct function that
can enhance the quality of AIS, is something
that banks should teach their employees in.
3. Although the company already has a suitable
organizational structure, branch offices and
regional organizations are still mostly unaware
of the exact authority that the head office's board
of directors possesses in light of the
aforementioned situation. Additionally, the
establishment of a distinct organizational
structure in banking will lead to identical
policies and guidelines throughout the entire
system, from the main office to the tiniest
branches.
4. The quality of during business operations has a
big influence on the caliber of accounting
information systems. on the quality of business
processes (the lengthy write-off procedure,
which can only be finished at the end of the
month, suggesting that BDS is already
overworked) (this proves that business
processes in banking are inadequate). This study
also demonstrates that process quality is one
factor affecting AIS quality. A system that
completes tasks as soon as it is practical is
considered efficient, based on process quality
metrics such as waiting time for the system.
5. The quality of accounting information is
significantly impacted by the quality of the
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204

accounting information system. Accordingly,
this data must meet the AI quality standards for
accuracy, timeliness, and completeness.
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