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Eduvest – Journal of Universal Studies Volume 3 Number 3, March, 2023 p- ISSN 2775-3735-
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Universitas Sam Ratulangi, Indonesia |
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ABSTRACT |
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Entering the era
of information and free trade, PT. Samudera Mulia Abadi requires a certain
advantage in order to face national and international competition. For this
reason, every company strives to provide the best service facilities for
customers through the accuracy, precision and effectiveness of information.
These things must be supported by the development of information technology
at this time. An organization that has a well-designed information system
will generally have a competitive advantage over an organization with a
weaker system. However, the facts show that the implementation of an
information system is not easy. The more departments related to the
information system, the more complex the information system will be and the
higher the risk of failure. This research takes a case study of the
effectiveness of information system implementation at PT Samudera Mulia Abadi
(SMA) and what factors influence it. The method use in this study is a survey
method by distributing questionnaires to all respondents who use an
integrated information system at PT SMA. From the research results, it was
found that several factors influence the effectiveness of information system
implementation, including : user interaction with
information systems, IT support, involvement of consultants and features of
information systems. Without the above
factors, it is very unlikely that companies that implement integrated
information systems can take maximum advantage of integrated information systems
that are applied to their companies |
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KEYWORDS |
integrated information system,
implementation |
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This work is licensed under a Creative
Commons Attribution-ShareAlike 4.0 International |
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INTRODUCTION
Companies
in various industries are competing to use integrated information systems to increase
their competitiveness, for example by using an ERP (enterprise resource
planning) system (Lotfi et al., 2013). ERP is an information system that
integrates all information in an organization. User involvement is a very
influential factor in the success or failure of the implementation of an
information system. This research will provide an overview of what
non-technical factors influence the effectiveness of information system
implementation (Oladejo et al., 2020).
IT consulting firms can create an
integrated information system that can monitor almost all company activities,
control company finances, streamline company performance and increase company
competitiveness. But in reality, information systems that have been well
designed are difficult to implement in a company (Maiga, 2012). Often the results
of the implementation of the information system are not in line with
expectations or the time for implementing the system becomes much longer than
the predetermined time (Creswell & Creswell, 2017).
The ineffective implementation of an
integrated information system greatly disrupts the performance of the
consulting firm (as the party in charge of implementing the system) and harms
the company that uses the information system (as the user who has invested time
and money). So this research needs to be done, why in the field often occur
implementation of ineffective information systems ?
The effectiveness of an information
system that will be examined here is seen from the user’s point of view (Dobusch, 2014). The system is considered effective if the
user is satisfied in using the system and its performance increases. With an
increase in user performance, the company’s performance will also increase and
usually companies that use information systems will get the maximum benefit
from the implementation of the information system (Putri, 2017).
Problem
formulation.
Based on the description of the
background of the problem above, the research problem is formulated as follows
:
1.
Does user interaction with the information
system significantly influence the effectiveness of the information system
implementation ?
2.
Will IT support significantly influence
the effectiveness of information system implementation ?
3.
Will the support of consultants from
outside the company affect the effectiveness of information system
implementation ?
4.
Will the information system supporting
features affect the effectiveness of the information system implementation ?
Implementation of
information systems
There are many examples of information
system implementation failures in the existing literature. According to (Seddon et al., 1999) which tries to explain why failures often occur
in information systems projects and how to guarantee project success.
Until now there has been no
agreement on how to measure the success of an information systems project. The factors
that lead to the success of an information system implementation project vary
widely, depending on the stakeholders’ point of view, different project
characteristic and several other point of view
(Markus & Tanis, 2020) write that success depends on several things
depending on who defines it. From the point of view of project managers and
information systems implementation consultants, they often define an
implementation as successful if it has completed the project on time and on
cost. But from the point of view of organizations using information systems,
success is defined as the use of the system to achive maximum results for ther
business, and usually they expect a smooth transition from the old system to
the new system, get improvements from their business such as reducing
inventories, or can improve accuracy in decision making.
Implement an information system to
an organization, it will affect the existing processes within the organization.
This is where the views of stakeholders and consultants making information
systems usually meet each other. Complaints that are often issued are : ‘you built what I told you, but not what I
actually wanted”
Information system
risks.
The hierarchy of risk analysis
related to the creation of a software-based information system is : Information
system risks can be classified into several categories. Where each risk has
problems such as :
· Potential costs
· Time
· Technical
/ business consequences
To achieve
success, a software-based information system must meet technical criteria and
business requirements, within predetermined time and cost limits.
The risk of determining software
projects: defining operational, organizational, and contractual software (DeLone & McLean, 2016).
The project risk is primarily the responsibility of management. The risks of
the project involve the determination of contract boundaries, external
interfaces, relationships with suppliers, relationship with vendors, support
from the organization.
Process risk : include here is
management and technical work procedures. Management procedures, for example,
are planning, staffing, tracking, quality assurance. While technical procedure
risks are mainly found in design, program and testing activities.
Product risk : Failure of an
information system product is entirely the technical responsibility of the
vendor. Failures are often fount in the required standardization stability,
design, product usability, software complexity, and testing of the software.
The more flexible a system is, the more difficult produk risk will be to
manage.
The complexity of
information systems.
Table 1
Information system complexity
|
Making information systems, possible adverse effects |
Low (0.0<P<0.4) |
Medium (0.4<P<0.7) |
High (0.7<P<1.0) |
|
Number of departments associated
information systems |
1 |
2 |
5 |
|
The total time to create a system |
5
man years |
10
man years |
20
man years |
|
Estimated project implementation time
required |
<
12 months |
13
months -- 24 months |
>24 months |
|
Estimated of changes to
organizational functions that must be
made, if the new system is implemented |
0 – 25 % |
25
– 50 % |
50
– 100 % |
|
The level of complexity of changes that
must be made if a new system is implemented |
Low |
Medium |
high |
Source : (Pressman, 2016)
Table 1
shows the level of complexity of an information system based on the number of
departments in an organization that are interrelated (Pressman, 2016). The more departments that are interrelated with
information systems, the higher the level of risk/possibility of adverse
effects. The table explains that the Company is the opportunity for possible
adverse effects to occur.
RESEARCH
METHOD
This research was conducted at PT Samudra Mulia Abadi Tbk. On jalan
Pumorrow no 88, when new to the city of Manado. This research began in March
2022 until it was completed. The research was divided into several stages,
starting with creating questionnaires, testing, questionnaires collecting data,
analyzing data and preparing reports on the results of the research.
Because research is intended to determine the effectiveness of the
implementation of information systems, especially at the level of information
system users at PT Samudera Mulia Abadi. Then the population of the study is
all people who directly use information systems to support their work. The data
collection system using Simple random samples will be carried out using a
questionnaire in several areas in Manado. Sample size will be determined based
on time, cost and access considerations. This determination is important for
statistical analysis of data
After
the data can be collected, the data will be analyzed using the SPSS
(Statistical Product and Service Solutions) program to determine the validity
and reliability of the questionnaire.
The
validity test aims to determine the extent to which an instrument can measure
what it is intended to measure, so that it relates to the accuracy of the data.
There are several approaches to testing validity (Newman, 2013):
face validity, content validity, criterion validity and construct validity. The
validity test that was carried out was limited to testing the validity of the
respondents and the way the respondents filled out the instrument.
Reliability
test is used to determine the consistency of the data. (Newman, 2013) defines there are 3 types of reliability :
Reliable through time, Reliable through sub-population and consistent results
through several different indicators. Statistical measurements according to
Cronbach’s alpha, will be processed using the SPSS program to determine the
reliability of the data collected.
Where : reliability
coefficient N :
sum of items on questionnaire S2 :
variance of total questionnaire Si2 : variance of individual item
Source : (Newman, 2013)
Will
check the validity and reliability of the data. Respondents who do not meet the
filling criteria and do not meet the filling requirements will be discarded. Data
that has passed the validity and reliability test will be collected in one
table to make it easier to analyze the data. Measurements made in descriptive
data analysis are : mean, frequency and dispersion using the standard
deviation.
The
mean is the average value of the observations. It is the sum of all the data
divided by the number of data in the group (Aczel & Sounderpandian, 2019),
the frequency shows the amount of data in the same category. This can be
collected from the questionnaire obtained. While the standard deviation is a
measurement of the spread of data
RESULT AND DISCUSSION
PT.
Samudra Mulia Abadi
PT
Samudra Mulia Abadi is a limited liability company engaged in the mining
contractor sector, which was established based on notarial deed number 47 date
19 May 2010. PT. Samudra mulia Abadi started its business activities in the
heavy equipment rental business. Beginning with the procurement of heavy
equipment for exploration activities at PT. Arafura Surya Alam (J
Resourcess-Doup Site-Kotabunan). Heavy Equipment Support at PT. Sago Prima
Pratama (PT. SPP-Site Seruyung) and mining service activities at PT. J
Resources Bolaang Mongondow Lanut site & Bakan site- North Sulawesi. PT SMA
is one of the main contractors at PT. SPP (Seruyung site) which fully supports
land clearing, exploration construction, mining and gold mining activities. In
early 2012. PT SMA joined PT. J Resources Bolaang Mongondow Lanut site and
supports mining acivities. With the support of PT SMA, production can be
achieved beyond the target. In early 2016, PT SMA started a new mining project
with Rajawali Group subsidiary : PT. MSM / PT. The TTN – Toka Tindung Gold Mine
Project is located in Likupang – North Sulawesi
Respondents
The
information system used connects several departments of the company including
the marketing department, purchasing department, inventory control department,
accounting/ finance department, HDR/payrolls
department, construction department,
Because
it connects many departments, the implementation of the information system will
be very complex (Pressman, 2016), has a high risk, involves many users and takes a
long time to complete.
Data
were obtained by distributing questionnaires to the entire population of
company employees who were directly involved in the implementation of the
information system. Of the 74 respondents who were involved in the
implementation of the information system, there were 62 respondents who filled
out the questionnaire completely and met the requirements for further data
processing.
Reliability
and validity test
The
reability test is used to determine the consistency of the research instrument.
So if the instrument is used to measure the same object, a consistent output
will be produced. While the validity test is used to measure whether all
construct indicators for a variable are consistent.
According
to (Santoso, 2017),
how to measure validity and reliability is as follows:
Validy
test :
· If the
coefficient r is positive and greater than r table (r > r table) then the variable is valid
· If the
coefficient r is negative or smaller that r table (r < r table), then the
variable is invalid
Reliability
test :
·
If r alpha is positive and greater than r
table ( r alpha > r table), then the variable is reliable
·
If alpha is negative or smaller than r
table (r alpha > r table), then the variable is not reliable.
From the test, it was
found that for a significant level of 5 % (alpha = 0.05) and n = 50, then r
table = 0.279. whereas for n = 100, then r table = 0.195. for n= 62, then r
table can be calculated through interpolation :
(62-50) : (100-50) = (r-0.279) :
(0.195-0.279)
12 : 50 = ( r – 0.279) : (- 0.084)
r = 0.258
It can be
seen the reliability and validity test for each variable :
·
User interaction with information systems.
All r corrected items – Total correlation
> r table (0.258), meaning all items are valid r alpha (0.8457) is also greater than r table
(0.258), meaning that all items are reliable.
·
IT support.
Not all r corrected items – Total
Correlation > r table (0.258), means that not all items are valid, all r
corrected items – Total Correlation > r table (0.258) means all items are
valid. r Alpha (0.8719) is also greater than r table (0.258), meaning that all
items are reliable
·
Involvement of external consultants.
All
r corrected items – Total Correlation > r table (0.258), meaning all
items are valid r Alpha (0.9099) is also greater than r table (0.258), meaning
that all items are reliable.
·
Features of the information system.
All r corrected items – Total Correlation
> r table (0.258), meaning all items are valid. r = Alpha (0.9462) is also greater than r
table (0.258), meaning that all items are reliable.
· Effective
implementation of information systems.
All
r corrected items – Total Correlation > r table (0.258) meaning all item are
valid r Alpha (0.9324) is also
greater than r table (0.258), meaning that all items are reliable.
Table 2 Summary of
Reliability Test
|
Variables
|
n
|
Alpha |
|
User
interaction with information systems |
62 |
0.8457 |
|
IT
Support |
62 |
0.8719 |
|
External
Consultant engagement |
62 |
0.9099 |
|
Features of the information system |
62 |
0.9462 |
|
Effectiveness of information system
implementation |
62 |
0.9324 |
Correlation and Regression
The
purpose of this correlation is to find out how big the relationship between
variables is. For the correlation test, it was carried out using Pearson’s
correlations on the SPSS software
Table 3
Correlation levels Based on Coefficients (Sugiyono, 2021)
|
Coefficients |
Correlation
levels |
|
0.00
- 0.199 |
Very
weak |
|
0.20
- 0.399 |
Weak
|
|
0.40
- 0.599 |
Currently
|
|
0.60
- 0.799 |
Strong
|
|
0.80
- 1.000 |
Very
strong |
Regression can be done if there is a correlation between the
two variables. In other words, if there is no correlation between the two
variables, then the regression does not need to be done (Sugiyono, 2021).
a. Correlation
It
can be seen the correlation between the dependent variable and the independent
variables, after calculating using SPSS. Based on the correlation test, the
following conclusions can be drawn :
· The correlation between the effectiveness of information
system implementation and user interaction with information systems is moderate
(0.591) and significant (0.000)
· The correlation between the effectiveness of information
system implementation and IT support is strong (0.606) and significant (0.000)
· The correlation between the effectiveness of information
system implementation and the involvement of external consultants is strong
(0.632) and significant (0.000)
· The correlation between the effectiveness of information
system implementation and the features of the information system is strong
(0.772) and significant (0.000)
Table
4 level of correlation to the effectiveness of information system
implementation
|
Pearson Correlation |
Sig (2-tailed) |
Correlation |
|
|
User interaction with
information systems |
0.591 |
0.000 |
There is |
|
IT support |
0.606 |
0.000 |
There is |
|
External consultant engagement |
0.632 |
0.000 |
There is |
|
Features of the information
system |
0.772 |
0.000 |
There is |
b. Regression
The conclusions above show that there are 4 variables that
correlate with the effectiveness of information system implementation. Then
there are 4 independent variables included in the regression, with the
dependent variable being the effectiveness
of the information system. After being recalculated with SPSS, the regression
is obtained as follows :
Y = -1.225 + 0.348 (X1) + 0.381 (X2) + 0.338 (X3) +
0.430(X4)
Where variable ;
Y = effectiveness of information systems
X1 = user interaction with the information system
X2 = IT Support
X3 = Involvement of external consultants
X4 = Feature of the information system
The significance level of the regression table above from
the ANOVA table is 0.000, so the linear regression can be used to predict Y
(information system effectiveness). With adjusted R square 0.805, which means
that the four variables (X1, X2, X3, X4) contribute 80.5 % to the effectiveness
of the information system. The remaining 19,5 % are influenced or caused by
other factors.
Discussion
From the
research.results.it can be seen that the variables that correlate with the
effectiveness of information system implementation
User
interaction (X1) IT Support (X2) Consultant from
outside the company (X3) Supporting
features of information system (X4) (X4) Effectiveness
of information system implementation (Y) Y
0.772
0.606
Figure 1
correlation between independent variable and dependent variable
The
correlation between the dependent variable the effectiveness of information
system implementation (Y) and the features of the information system (X4) is
0.772, followed by the involvement of external consultants (X3) is 0.632, IT
support (X2) is 0.606, User interaction with information systems (X1) is 0.59.
How
to explain the dependent variable the effectiveness of information system
implementation (Y) based on the independent variables (X1, X2, X3, X4) ? This
form of relationship is called regression. According to (Sugiyono,2000), a new
regression test can be done if there is a correlation between two variables. In
other words, if there is no correlation between the two variables, then
regression is not necessary.
After
carrying out a regression test on the independent variables of user interaction
(X1), IT support (X2), involvement of consultants from outside the company
(X3), supporting features of the information system (X4), it can be seen that
the regression obtained from the research is :
Y = -1.225 + 0.348 (X1) + 0.381 (X2) + 0.338 (X3) +
0.430(X4)
From
the regression equation shows that if other variables are considered constant
then an increase of 100 % of the user interaction variable (X1), will increase
the effectiveness of information system implementation (Y) by 34.8 %.
If
other variables are considered constant, an increase of 100 % of the IT support
variable (X2) will increase the effectiveness of information system
implementation (Y) by 38.1 %
If
other variables are considered constant, an increase of 100 % from the involvement
of consultants from outside the company (X3), wil increase the effectiveness of
the implementation of information systems (Y) by 33.8 %
If
other variables are considered constant, then an increase of 100 % of the information system supporting feature
variable (X4) will increase the effectiveness of information system
implementation (Y) by 43.0 %
if
all the independent variables are 100 % then the effectiveness of information
system implementation. (Y) = -1.225 + 0.348 (100%) + 0.381 (100%) + 0.338
(100%) + 0.430 (100%) = 0.272. So
according to the regression, there will be an increase of 27.2 % of the Y
variable. This also explains the facts, why failures often occur in many
companies trying to implement integrated information systems, even though these
companies have spent large amounts of money.
With a large amount of finance,
usually company management that will implement an integrated information system
will usually only choose (buy) features from sophisticated information systems
(X4), expert consultants (X3) who are usually very expensive. In addition, the
information system implementing company will also improve the existing IT
support (X2) by sending the IT division
to the information system training location that will be implemented in the
company.
However, there are other factors
that also influence the effectiveness of information system implementation (Y),
which are often overlooked. This factor is user interaction (X1). Users /direct
users of the information system will usually be passive and reject the new
system. If there is no user interaction, then the effectiveness of information
system implementation (Y) is as follows :
(Y)
= -1.225 + 0.348 (0%) + 0.381 (100%) + 0.338
(100%) + 0.430 (100%)
=
- 0.076
This means that the effectiveness of information system
implementation (Y) is reduced by 7.6 % The reduced effectiveness of the
implementation of the information system causes a decrease in user performance
within the company and a decrease in user satisfaction in using the information
system. Because according to SPSS calculation, the coreelation between user
performance and user satisfaction is strong (0.608) and significant (0.000)
CONCLUSION
Based on the research results, the following
conclusions are obtained Critical success factors that affect the effectiveness
of information system implementation are the Features of the information
system, Consultant involvement, IT support and User interaction
The factors mentioned above influence (80,5%) on
the success or failure of the effectiveness of the implementation of
information systems.
The system of giving punishments or giving gifts
to users of information systems does not significantly influence the
effectiveness of information system implementation. Because as long as the user
does no interact with the system being built, it is certain that the
information system will not provide maximum results for the company.
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