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THE INFLUENCE OF RISK FACTORS ON PROJECT COST IN
THE SIGLI-BANDA ACEH TOLL ROAD PROJECT
Mariama Badjie
Universitas Syiah Kuala, Banda Aceh, Indonesia
mariamabadjie.mb@gmail.com
ABSTRACT
Effective management of risk is critical to the success of any construction project. The importance of
risk management has grown as projects have become more complex. This study examines the influence
of risk factors on project cost in the Sigli-Banda Aceh toll road project. It identifies 47 common risk
indicators and categorises them into six risk factors, emphasize the need for improved risk management
strategies in complex construction projects. The research question of this study is to know the influence
and relationship of risk factors on project cost in the Sigli-Banda Aceh toll road project. The purpose of
this study is to determine the risk factors that influence and relate to project cost in the Sigli-Banda Aceh
toll road project. The data was analysed with statistical tools to determine the rank of factors affecting
project costs. The research method used quantitative, using hard data on Likert scale, and qualitative,
using the opinions of the respondents, with primary sources and secondary data. This research involved
the project director, site supervisors, engineers, safety environment officer, and finance manager from
PT Hutama Karya. Data collection techniques include the distribution of questionnaires. The data
analysis technique uses correlation and multiple linear regression analysis methods with the help of SPSS
software. According to the result analysis, all the factors have a moderate relationship with the project
cost, and there are four factors that have a significant relationship with the project cost, namely material
risk, equipment risk, construction method risk, contractor managerial risk, and construction safety risk.
Keywords: Influence; Risk Factors; Project Cost
INTRODUCTION
Construction is a big industry in Indonesia, as it is in other nations, and it plays a vital role
in the expansion of socioeconomic development (Khan et al., 2014). The primary criterion for
project success is meeting the project's deadlines and budget while maintaining the required level
of quality (Serrador & Turner, 2015). Although there has been significant investment in the
construction sector in Indonesia, there are still several problems with the sector, including costs
that exceed budgets, delays in finishing projects on time, construction faults, and an overreliance
on foreign labour (Menolascina et al., 2008).
The construction sector is facing a significant cost-cutting challenge as a result of the
expanding demand for building of all kinds and the limited availability of funding (Sami Ur
Rehman et al., 2022). Corporations, institutions, and the government would be in a survival race
for the remainder of the twentieth century, according to Mendelson and Greenfield (1996). The
participant in these sectors (the customer, in particular) is prepared to take on the challenge of
assuring efficient use of their resources to achieve value for money in terms of performance due
to the accompanying diminishing economic fortune of nations' economies throughout the world
(Eshofonie, 2008).
Under typical conditions, it is anticipated that the following costs will add up to the overall
cost of construction: Materials, labour, site overheads, equipment/plant, head office expense, and
profit, however in many countries, particularly in Indonesia, there are other costs that need to be
taken into account (Eshofonie, 2008).
These costs clearly have a negative impact on both the industry as a whole and the major
stakeholders in particular. High cost means additional costs to the client beyond those previously
discussed at the outset, resulting in worse returns on investment. The additional expenses are
passed on to the consumer as higher rental or leasing fees or prices. The consultants interpret this
as a failure to provide value for the money spent, which could damage their reputation and cause
clients to lose faith in them. If the contractor is at fault, it means a loss of earnings due to penalties
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for non-three-quarter completion and bad word of mouth that could jeopardise his or her prospects
of gaining more work (Eshofonie, 2008).
A project is a task carried out with constrained time and resources to accomplish preset
objectives (Sonelma & Sucita, 2022). A construction project, on the other hand, can be seen as a
collection of tasks with distinctive characteristics, constrained time, and resources, necessitating
management expertise to handle them (Simanjuntak & Simandjorang, 2019). This series of tasks
includes creating plans, creating designs, building things, and maintaining them (Dharmayanti &
Jaya, 2018)
A construction project is an activity that involves allocating certain resources in order to
achieve the intended work outcome, which is determined by the suitability of time, quality, and
cost (Mahapatni, 2019). a building is one of the works of construction that provides a space for
habitation as well as for religious, commercial, social, and cultural objectives as well as for certain
activities. Because every action requires facilities, a construction project is a construction service
that is full of various risks when it is being carried out (Rofiah et al., 2021). To plan or manage
ongoing projects, reduce risks, and achieve project goals, project management is required. Risk
management, which makes sure that project risks are minimised, is an essential part of project
management (Project Management Institute, 2017).
Infrastructure projects, including toll road projects, are inextricably related to risks. Risk is
a result of an uncertain situation, which is frequently impossible to foresee with accuracy.
Therefore, risk management is essential from the start of the construction project to minimise the
impact of potential risks (Cheng et al., 2016).
RESEARCH METHODS
The research methods and research strategy used to achieve the paper's objectives will be
covered in this chapter. In order to better understand how risk factors, affect project costs during
the construction implementation stage and how to manage them, this study employed quantitative
research methods. It focused specifically on the type of flexible pavement used in the Sigli-Banda
Aceh toll road project. Three systematic processes made up the quantitative approach: a
questionnaire survey, a risk analysis of the results of the questionnaire survey, and.
Research Object and Scope
The relationship between risk factors and project cost, as well as their influence, are the
focus of this study. This study's focus is on P.T Hutama Karya, a reputable contractor firm in
charge of the Sigli-Banda Aceh toll road project.
Data Types and Sources
Research data types that are related to data sources and the methods chosen to collect
research data. The two types of data sources used in this study are as follows:
1. Primary Data
The primary data for this study came from responses to questionnaires filled out by
knowledgeable individuals within the construction firm PT Hutama Karya. Through a
questionnaire, this is done to obtain a risk assessment of the Sigli-Banda Aceh toll road
project (Hanifah, 2019).
The primary data for this study came from responses to questionnaires filled out by
knowledgeable individuals within the construction firm PT Hutama Karya. Through a
questionnaire, this is done to obtain a risk assessment of the Sigli-Banda Aceh toll road
project (Hanifah, 2019).
2. Secondary Data
Secondary data are those that have already been statistically analysed or that have been
gathered, statistically processed, and then transferred to another party. Regardless of
whether it was made public or not, it refers to data that has previously been obtained and
used for another reason (Bagha et al., 2019).
In this study, secondary data were collected from articles and international journals reading
sources, as well as information on the evaluation of direct construction contract documents
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for construction services at PT Hutama Karya in the project of the Sigli-Banda Aceh Toll
Project. The secondary data were then processed and analysed (Hanifah, 2019).
Population and Sample
A population is a subject or an object that falls within a study topic and satisfies the
requirements for individuals to be part of the research unit or analytic unit being analysed
(individuals, groups, or organisations). To accurately reflect the population, the sample, which is
a small section of the population, is drawn using a particular procedure (Abdussamad & Sik, 2021).
1. Population
Project director, site office supervisors, engineers, Safety environment officer and
Finance Project manager from PT Hutama Karya made up the population in this study
because they are the principal decision-makers who are in charge of the initiatives and knows
about the risk in the project better, whether they are from private organisations or from
people, are included in this group (Altoryman, 2014).
Engineers, site office supervisors, project director, Safety environment officer and
Finance Project manager from PT Hutama Karya made up the population in this study.
Whether they work for private businesses or are individuals, these people are the ones who
make the important decisions that affect the initiatives (Altoryman, 2014).
The respondents were chosen by the most skilled and seasoned staff members. 30
samples from PT. Hutama Karya records were used to identify responders, including
engineers, site office managers, and project directors, under the assumption that the error
value was 10%.
2. Sample
The sample is part of the population that has certain characteristics or circumstances
that will be studied.
The goal of sampling is to provide a selection that is representative of the population
from which it was derived. A "representative" sample of the total population must be used
to generalise the research's conclusions (Altoryman, 2014).
Engineers, site office supervisors, project directors, safety environment officers, and
finance project managers from construction business PT Hutama Karya were among the
samples used in this study. A list of the building construction projects completed for the
Sigli-Banda Aceh toll road project is also provided (Ariska, 2022).
If the population is less than 100, the entire sample is taken, but if the population is
larger than 100, 10-15% or 20-25% of the entire population can be collected, according to
Arikunto (2013). The authors used 100% of the population at PT Hutama Karya, or 30
respondents, based on this research because the total population is not larger than 100
respondents.
Table 1 Sample Calculation Results
Population
Engineers
15
Site office supervisors
15
Project Director
1
Safety environment officer
4
Finance Project manager
1
Total
36
Sample
Engineers
15
Site office supervisors
15
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Project Director
1
Safety environment officer
4
Finance Project manager
1
Total
36
RESULTS AND DISCUSSION
This chapter presents the results of data processing and analysis obtained from the
questionnaires that have been distributed according to Chapter III and is given a discussion
according to the theory from the literature in Chapter II
.
Results of Data Collection
1. General Description of the Research Object
The study's purpose was the road construction project that was carried out on the Sigli-
Banda Aceh toll route. Because each activity requires infrastructure, a construction project is a
construction service that is rife with dangers during the execution stage. Based on information
collected directly from PT Hutama Karya, it was determined that the contracting company
completed construction projects on the Sigli-Banda Aceh toll road.
2. Data of Respondents
The questionnaire was distributed for one month, in December 2023. Based on the projects
that were put into action in 2022, the results of distributing the questionnaire revealed the
frequency and impact of hazards according to level. The data is then processed to provide answers
to the research's objectives. Using information from PT Hutama Karya, it will be determined
which sample was only obtained during the construction of the Sigli-Banda Aceh toll road project.
Purposive sampling is used to estimate the number of withdrawals in each area. Based on
purposive sampling, PT Hutama Karya's sample distribution in each industry is as follows: 36
respondents from different PT Hutama Karya divisions responded.
Data processing is done to provide answers to the queries that are the research's goals. The
direct distribution of questionnaires to the contractor company took place. The decision-makers
and skilled construction service providers of PT Hutama Karya were the respondents in this study.
Questionnaire A broad description of the study object is provided in Part I in the form of
respondent characteristics and company data. Position, gender, age, most recent education, job
history, company information, qualifications, prior company experience, project kind, project
value, projected length, and actual duration were the characteristics of the respondents used in
this study. Following are some details on the characteristics of respondents and firm information
gleaned from the Part I questionnaire:
3. Characteristics of Respondents
Because of the respondents' responses to the questionnaire, the characteristics of the
respondents in this study are utilized to describe the respondents' identities. Recapitulation of
survey data from respondents Table 2 displays Part I.
Table 2 Respondent Characteristics
No Characteristics of Respondents
Frequency
Percentage
1
Position
Engineer
20
55.6%
Project Director
1
2.8%
Site Office Supervisor
10
27.8%
Safety Environment Officer
1
2.8%
Finance project Manager
2
5.5%
Technician
2
5.5%
Total
Frequency
100%
2
Gender
Man
28
77.8%
Woman
8
22.2%
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Total
Frequency
100%
3
Age
21-30 Years
26
72.2%
31-40 Years
9
25%
41-50 Year
1
2.8%
Total
Frequency
100%
4
Last Education
Senior High School
6
16.7%
Undergraduate (S1)
29
80.5%
Post Graduate (S2/S3)
1
2.8%
Total
Frequency
100%
5
Work Experience
<3 Years
17
47.2%
6-8 Years
12
33.3%
>8 Years
7
19.5%
Total
Frequency
100%
According to Table 2, most respondents with positions as engineers are male and between
the ages of 21 and 30. Their most recent degree was a bachelor's degree (S1), and they have a
minimum of less than three years of work experience. The respondents can be trusted sufficiently
to answer the study questionnaire considering the findings.
Results of Data Processing
1. Research Data Test Results
a. Validity Test Results
Validity test is a measure that shows the level of validity or legitimacy of an
instrument. A valid instrument has high validity and conversely, if the level of validity is low
then the instrument is less valid. In this study, researchers used 36 respondents, so it can be
seen that the size of the r table is 0.329 which is obtained from (df= n-2 = 36-2= 34) with an
error rate of 5%. The validity test results for each question item on each variable are as
follows:
Table 3
Results of Validity Test Risk Frequency
Variable
Question
Items
Rcount
Rtabel
Information
Material Risk (X1)
X1,1
0,685
0,329
Valid
X1,2
0,764
Valid
X1,3
0,727
Valid
X1,4
0,494
Valid
X1,5
0,610
Valid
X1,6
0,630
Valid
Equipment Risk (X2)
X2.1
0,592
Valid
X2.2
0,601
Valid
X2.3
0,520
Valid
X2.4
0,801
Valid
X2.5
0,659
Valid
X2.6
0,574
Valid
X2.7
0,448
Valid
X2.8
0,536
Valid
X2.9
0,737
Valid
Construction Method Risk (X3)
X3.1
0,565
Valid
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X3.2
0,711
Valid
X3.3
0,454
Valid
X3.4
0,747
Valid
X3.5
0,753
Valid
Constractor Managerial Risk (X4)
X4.1
0,641
Valid
X4.2
0,633
Valid
X4.3
0,721
Valid
X4.4
0,714
Valid
X4.5
0,720
Valid
X4.6
0,780
Valid
X4.7
0,681
Valid
X4.8
0,651
Valid
Operational Risk (X5)
X5.1
0,477
Valid
X5.2
0,684
Valid
X5.3
0,628
Valid
X5.4
0,647
Valid
X5.5
0,539
Valid
X5.6
0,683
Valid
X5.7
0,663
Valid
X5.8
0,762
Valid
X5.9
0,452
Valid
Construction Safety Risk (X6)
X6.1
0,490
Valid
X6.2
0,713
Valid
X6.3
0,655
Valid
X6.4
0,842
Valid
X6.5
0,793
Valid
X6.6
0,690
Valid
X6.7
0,741
Valid
Project Cost (Y)
Y.1
0,719
Valid
Y.2
0,834
Valid
Y.3
0,725
Valid
Source: primary data processed with spss 20.0, 2023
Based on table 3 above, it can be seen that all question items from the variable’s material
risk, equipment risk, construction method risk, constructor managerial risk, operational risk,
construction safety risk, and project cost are declared valid. This is evident from all question
items which have calculated r values in the Corrected Item-Total Correlation which are
greater than the r table.
2. Reliability Test Results
The reliability test is a measure of a respondent's stability and consistency in
answering matters relating to the respondent's constructs which are dimensions of a variable
and are arranged in a questionnaire form. An instrument is said to be reliable if the
Cronbach's Alpha value is above 0.6 then the instrument is said to be reliable. The reliability
measurement using Cronbach's Alpha method can be seen in the table below:
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Table 4
Results of Reliability Test Risk Frequency
Variable
Alpha Cronbach
N of Items
Information
Material Risk (X1)
0,726
6
Reliable
Equipment Risk (X2)
0,785
9
Reliable
Construction Method Risk (X3)
0,662
5
Reliable
Constractor Managerial Risk (X4)
0,844
8
Reliable
Operational Risk (X5)
0,799
9
Reliable
Construction Safety Risk (X6)
0,830
7
Reliable
Project Cost (Y)
0,618
3
Reliable
Source: primary data processed with SPSS 20.0, 2023
Based on the output of table 4 above, it can be seen that all material risk, equipment risk,
construction method risk, constructor managerial risk, operational risk, construction safety risk,
and project cost variables have Cronbach's Alpha values above 0.6. This means that each question
item on each variable, including material risk, equipment risk, construction method risk,
managerial constructor risk, operational risk, construction safety risk, and project cost, is reliable.
Table 5
Correlation Test Results
No
Variable
Relationships
Spearman coefficient
Form of Relationship
1
X1 - Y
0,505
moderate
2
X2 - Y
0,594
moderate
3
X3 - Y
0,596
moderate
4
X4 - Y
0,551
moderate
5
X5 - Y
0,442
moderate
6
X6 - Y
0,452
moderate
Source: primary data processed with spss 20.0, 2023
Based on the output of table 5 above, the following interpretation can be given:
a. The relationship between material risk factors and project costs
The material risk factor has a Spearman correlation coefficient of 0.505, with a
significance value of 0.002 <0.05. This means that the material risk factor has a moderate
relationship and there is a significant relationship with project costs.
b. The relationship between equipment risk factors and project costs
The equipment risk factor has a Spearman correlation coefficient of 0.594, with a
significance value of 0.000 <0.05. This means that the equipment risk factor has a
moderate relationship and there is a significant relationship with project costs.
c. The relationship between construction method risk factors and project costs
The construction method risk factor has a Spearman correlation coefficient of 0.596, with
a significance value of 0.000 <0.05. This means that the construction method risk factor
has a moderate relationship and there is a significant relationship to project cost.
d. The relationship between contractor managerial risk factors and project costs
The contractor managerial risk factors have a Spearman correlation coefficient of 0.551,
with a significance value of 0.001 <0.05. This means that the contractor managerial risk
factors have a moderate relationship and there is a significant relationship with project
costs.
e. The relationship between operational risk factors and project costs
The operational risk factor has a Spearman correlation coefficient of 0.442, with a
significance value of 0.007 <0.05. This means that operational risk factors have a
moderate relationship and there is a significant relationship with project costs.
f. The relationship between construction safety risk factors and project costs
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The construction safety risk factor has a Spearman correlation coefficient of 0.452, with a
significance value of 0.006 <0.05. This means that operational risk factors have a moderate
relationship and there is a significant relationship with project costs.
3. Multiple Linear Regression Analysis
a. Regression Model
The multiple linear regression equation is the results of the multiple linear regression test,
among others, can be seen in the table below:
Table 6 Multiple Linear Regression Test Results
Variable
Regression
Coefficients
t test
tvalue
Sig
Constant
0,067
-0,089
0,929
Faktor Material Risk (X1)
-0,009
-0,110
0,913
Faktor Equipment Risk (X2)
0,162
2,078
0,047
Faktor Construction Method Risk (X3)
0,232
2,249
0,032
Faktor Contractor Managerial Risk (X4)
0,142
3,339
0,002
Faktor Operational Risk (X5)
-0,210
-2,603
0,014
Faktor Construction Safety Risk (X6)
0,106
1,377
0,179
Source: primary data processed with SPSS 20.0, 2023
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
.067
.749
.089
.929
Material Risk
-.009
.082
-.021
-.110
.913
Equipment Risk
.162
.078
.534
2.078
.047
Construction Method Risk
.232
.103
.388
2.249
.032
Contractor Managerial Risk
.142
.043
.466
3.339
.002
Operational Risk
-.210
.081
-.764
-2.603
.014
Construction Safety Risk
.106
.077
.328
1.377
.179
Based on the output in table 4.6 above, the regression equation can be written as follows:
𝑌𝑖=𝛽0+𝛽1𝑋1+𝛽2𝑋2+.... +𝛽6𝑋6
Y = 0,067 – 0,009 X1 + 0,162 X2 + 0,232 X3 + 0,142 X4 - 0,210 X5 + 0,106 X6
Based on the equation above, the regression coefficient in the model can be interpreted as follows:
a. The influence of material risk factors on project costs
The material risk factor has a regression coefficient of -0.009. This means that the
material risk factor has a negative influence and if it is increased, the project cost will
decrease by 0.01%.
b. The influence of equipment risk factors on project costs
The equipment risk factor has a regression coefficient of 0.162. This means that the
equipment risk factor has a positive influence and if it is increased, project costs will
increase by 16.2%.
c. The influence of construction method risk factors on project costs
The construction method risk factor has a regression coefficient of 0.232. This means that
the construction method risk factor has a positive influence and if it is increased, the
project cost will increase by 23.2%.
d. The influence of contractor managerial risk factors on project costs
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The contractor managerial risk factors factor has a regression coefficient of 0.142. This
means that the contractor managerial risk factors have a positive influence and if it is
increased, project costs will increase by 14.2%.
e. The influence of operational risk factors on project costs
The operational risk factor has a regression coefficient of -0.210. This means that the
operational risk factor has a negative influence and if it is increased, project costs will
decrease by 21%.
f. The influence of construction safety risk factors on project costs
The construction safety risk factor has a regression coefficient of 0.106. This means that
the construction safety risk factor has a positive influence and if it is increased, project
costs will increase by 10.6%.
a. T Test
The following partial test results can be seen in the following table:
Table 7 Parameter Coefficient Partial Test Multiple Linear Regression Analysis
No
Intermediate
Influence
tcount
ttable
Sig.
Sig.
Decree
Information
1
X1 - Y
-0,110
2,045
0,913
0,05
No significant effect
2
X2 - Y
2,078
0,047
Has a significant effect
3
X3 - Y
2,249
0,032
Has a significant effect
4
X4 - Y
3,339
0,002
Has a significant effect
5
X5 - Y
-2,603
0,014
Has a significant effect
6
X6 - Y
1,377
0,179
No significant effect
Source: SPSS 20 Test Results (processed data, 2023)
Based on the equation above 4.9, the t test results can be interpreted as follows:
a. The influence of material risk factors on project costs
The material risk factor obtained is a value of tcount < ttable, namely -0.110< 2.045 and
a significance value of 0.913 > 0.05, so H0 is accepted and H1 is rejected. This means
that the material risk factor has no effect and is not significant on project costs.
b. The influence of equipment risk factors on project costs
The equipment risk factor obtained a value of tcount > ttable, namely 2.078 > 2.045 and
a significance value of 0.047 < 0.05, so that H0 was rejected and H2 was accepted. This
means that the equipment risk factor has a significant effect on project costs.
c. The influence of construction method risk factors on project costs
The construction method risk factor obtained a value of tcount > ttable, namely 2.249 >
2.045 and a significance value of 0.032 < 0.05, so that H0 was rejected and H3 was
accepted. This means that the construction method risk factor has a significant effect on
project costs.
d. The influence of contractor managerial risk factors on project costs
The contractor managerial risk factor obtained a value of tcount > ttable, namely 3.339 >
2.045 and a significance value of 0.002 < 0.05, so that H0 was rejected and H4 was
accepted. This means that the contractor managerial risk factor has a significant effect on
project costs.
e. The influence of operational risk factors on project costs
For the operational risk factor, the value obtained is tcount > ttable, namely -2.063 >
2.045 and a significance value of 0.014 < 0.05, so H0 is rejected and H5 is accepted. This
means that operational risk factors have a significant effect on project costs.
f. The influence of construction safety risk factors on project costs
The construction safety risk factor obtained a value of tcount < ttable, namely 1.377 <
2.045 and a significance value of 0.179 > 0.05, so that H0 was accepted and H6 was
rejected. This means that the construction safety risk factor has no effect and is not
significant on project costs.
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Discussion
Based on the project manager's perception that data processing and data analysis have been
carried out, in this sub-chapter the researcher will provide several discussions. The discussion in
this research concerns the influence of risk factors on project cost in Sigli-Banda Aceh toll road
project, as well as the form of relationship and influence between the risk factors on the project
cost in Sigli-Banda Aceh toll road project.
The discussion can be described as follows. 4.6.1 the influence of risk factors on project
cost in Sigli-Banda Aceh toll road project
The relationship between material risk factors and project cost. The relationship between
material risk factors and project costs in Sigli-Banda Aceh toll road project has been analysed
through spearman correlation. This analysis shows that material risk factor has a moderate
relationship and there is a significant relationship with project costs., therefor there is a
relationship enough with Spearman coefficients of 0.505, with a significance value of 0.002
<0.05.
The relationship between equipment risk factors and project cost.
The relationship between equipment risk factors and project costs in Sigli-Banda Aceh toll
road project has been analysed through spearman correlation. This analysis shows that equipment
risk factors have a moderate relationship and there is a significant relationship with project costs.,
therefor there is a relationship enough with Spearman coefficients of 0.594, with a significance
value of 0.000 <0.05.
The relationship between construction method risk factors and project cost.
The relationship between construction method risk factors and project costs in Sigli-Banda
Aceh toll road project has been analysed through spearman correlation. This analysis shows that
construction method risk factors have a moderate relationship and there is a significant
relationship with project costs., therefor there is a relationship enough with Spearman coefficients
of 0.596, with a significance value of 0.000 <0.05.
The relationship between contractor managerial risk factors and project cost/
The relationship between contractor managerial risk factors and project costs in Sigli-
Banda Aceh toll road project has been analysed through spearman correlation. This analysis
shows that contractor managerial risk factors have a moderate relationship and there is a
significant relationship with project costs., therefor there is a relationship enough with Spearman
coefficients of 0.551, with a significance value of 0.001 <0.05.
The relationship between operational risk factors and project cost.
The relationship between operational risk factors and project costs in Sigli-Banda Aceh toll
road project has been analysed through spearman correlation. This analysis shows that operational
risk factors have a moderate relationship and there is a significant relationship with project costs.,
therefor there is a relationship enough with Spearman coefficients of 0.442 with a significance
value of 0.007 <0.05.
The relationship between construction safety risk factors and project cost.
The relationship between construction safety risk factors and project costs in Sigli-Banda
Aceh toll road project has been analysed through spearman correlation. This analysis shows that
construction safety risk factors have a moderate relationship and there is a significant relationship
with project costs., therefor there is a relationship enough with Spearman coefficients of 0.452,
with a significance value of 0.006 <0.05.
There are 4 factors that have a significant relationship to the project costs in Sigli-Banda
Aceh toll road project and 2 factors that have no significant relationship to the project costs in
Sigli-Banda Aceh toll road project. Significant relationships are marked on factors that have a Sig
value <0.05 (5%).
The material risk factor obtained is a value of t count < t table, namely |0.010| < 2.045 and
a significance value of 0.913 > 0.05, so H0 is accepted and H1 is rejected. This means that the
material risk factor has no significant effect and is not significant on project costs. The material
The Influence of Risk Factors on Project Cost in The Sigli-Banda Aceh Toll Road Project
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risk factor has a regression coefficient of -0.009. This means that the material risk factor has a
negative influence and if it is increased, the project cost will decrease by 0.01%.
The equipment risk factor obtained a value of tcount > ttable, namely 2.078 > 2.045 and a
significance value of 0.047 < 0.05, so that H0 was rejected and H2 was accepted. This means that
the equipment risk factor has a significant effect on project costs. The equipment risk factor has
a regression coefficient of 0.162. This means that the equipment risk factor has a positive
influence and if it is increased, project costs will increase by 16.2%. This risk often occurs during
the implementation of construction projects in Sigli-Banda Aceh toll road project. (Equipment
risk) this risk has also occurred in previous studies, which can be seen from the results of
Chattapadhyay et al., (2021), Jaber (2019) and Moi and Purnawirati (2021).
The construction method risk factor obtained a value of tcount > ttable, namely 2.249 >
2.045 and a significance value of 0.032 < 0.05, so that H0 was rejected and H3 was accepted.
This means that the construction method risk factor has a significant effect on project costs. The
construction method risk factor has a regression coefficient of 0.232. This means that the
construction method risk factor has a positive influence and if it is increased, the project cost will
increase by 23.2%. This risk often occurs during the implementation of construction projects in
Sigli-Banda Aceh toll road project. (Construction method risk) this risk has also occurred in
previous studies, which can be seen from the results of Enderzon (2020 and Suherdi dkk (2020).
The contractor managerial risk factor obtained a value of tcount > ttable, namely 3.339 >
2.045 and a significance value of 0.002 < 0.05, so that H0 was rejected and H4 was accepted.
This means that the contractor managerial risk factor has a significant effect on project costs. The
contractor managerial risk factors factor has a regression coefficient of 0.142. This means that the
contractor managerial risk factors have a positive influence and if it is increased, project costs
will increase by 14.2%. This risk often occurs during the implementation of construction projects
in Sigli-Banda Aceh toll road project. (Contractor managerial risk) this risk has also occurred in
previous studies, which can be seen from the results of Jaber (2019) and Moi and Purnawirati
(2021).
For the operational risk factor, the value obtained is t count > t table, namely |2.063| > 2.045
and a significance value of 0.014 < 0.05, so H0 is rejected and H5 is accepted. This means that
operational risk factors have no significant effect on project costs. The operational risk factor has
a regression coefficient of -0.210. This means that the operational risk factor has a negative
influence and if it is increased, project costs will decrease by 21%.
The construction safety risk factor obtained a value of tcount < ttable, namely 1.377 < 2.045
and a significance value of 0.179 > 0.05, so that H0 was accepted and H6 was rejected. This
means that the construction safety risk factor has no effect and is not significant on project costs.
The construction safety risk factor has a regression coefficient of 0.106. This means that the
construction safety risk factor has a positive influence and if it is increased, project costs will
increase by 10.6%. This risk often occurs during the implementation of construction projects in
Sigli-Banda Aceh toll road project. (Construction safety risk) this risk has also occurred in
previous studies, which can be seen from the results of Rustandi (2017) and Maulana and Santosa
(2020).
CONCLUSION
Based on the findings and discussions, it was found that the finding accepted the Influence
of risk factors is factor that affects their project cost significantly. The finding indicated that the
alternative hypothesis was accepted while the null hypothesis was rejected as the correlation
coefficient was .695, and the p-value was .000 which was less than .05 (.000 < .05). It can be
implied that there was a significant strong correlation between risk factors and project cost of the
Sigli- Banda Aceh toll road project.
The study reveals a moderate relationship between
material, equipment, construction method, contractor managerial, operational, and
construction safety risk factors and project cost, with a Spearman coefficient of 0.505,
0.594, 0.596, 0.551, 0.442, and 0.452 respectively.
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REFERENCES
Abdussamad, H. Z., & Sik, M. S. (2021). Metode penelitian kualitatif. CV. Syakir Media Press.
Altoryman, A. (2014). Identification and assessment of risk factors affecting construction projects
in the Gulf region: Kuwait and Bahrain. The University of Manchester (United Kingdom).
Google Scholar
Arikunto, S. (2013). Prosedur penelitian suatu pendekatan praktik. Google Scholar
Ariska. (2022). Identify risks in the implementation of building construction projects in Aceh
Province Dissertation. . Syiah Kuala University. Google Scholar
Bagha, L., Sehgal, S., Thakur, A., Kumar, H., & Goyal, D. (2019). Low cost joining of SS304-
SS304 through microwave hybrid heating without filler-powder. Engineering Research
Express, 1(2), 025035. https://doi.org/10.1088/2631-8695/ab551d Google Scholar
Cheng, Y. L., Lee, C. Y., Huang, Y. L., Buckner, C. A., Lafrenie, R. M., Dénommée, J. A.,
Caswell, J. M., Want, D. A., Gan, G. G., & Leong, Y. C. (2016). We are IntechOpen, the
world’s leading publisher of Open Access books Built by scientists, for scientists TOP 1%.
Intech, 11 (tourism), 13. Google Scholar
Dharmayanti, G. A. P. C., & Jaya, N. M. (2018). Analisis kinerja proyek terhadap kepuasan
Stakholder. Jurnal Spektran, 6(2). Google Scholar
Eshofonie, F. P. (2008). Factors affecting cost of construction in Nigeria. Unpublished M. Sc.
Thesis, University of Lagos, Akoka. Google Scholar
Hanifah, D. (2019). Identifikasi Risiko Pengadaan Langsung Jasa Konstruksi Menurut Perpres
Nomor 54 Tahun 2010 Komparasi Perpres Nomor 16 Tahun 2018 Menggunakan Fuzzy
Logic [Thesis, Universitas Jember]. http://repository.unej.ac.id/handle/123456789/93453
Google Scholar
Khan, R. A., Liew, M. S., & Ghazali, Z. Bin. (2014). Malaysian Construction Sector and Malaysia
Vision 2020: Developed Nation Status. Procedia - Social and Behavioral Sciences, 109,
507–513. https://doi.org/10.1016/j.sbspro.2013.12.498 Google Scholar
Mahapatni, I. A. P. (2019). Metode Perencanaan dan Pengendalian Proyek Kontruksi (Made
Novia Indriani). Unhi Press. Google Scholar
Mendelson, S., & Greenfield, H. (1996). Taking value engineering into the twenty-first century.
International Journal of Cost Estimation, Cost/Schedule Control and Project Management,
37(8). Google Scholar
Menolascina, F., Bevilacqua, V., Ciminelli, C., Armenise, M. N., & Mastronardi, G. (2008). A
multi-objective genetic algorithm based approach to the optimization of oligonucleotide
microarray production process. International Conference on Intelligent Computing, 1039–
1046. Google Scholar
Project Management Institute. (2017). A Guide to the Project Management Body of Knowledge
(PMBOK® Guide) (5th Edition). Project Management Institute, Inc. Google Scholar
Rofiah, N. H., Kawai, N., & Hayati, E. N. (2021). Key elements of disaster mitigation education
in inclusive school setting in the Indonesian context. Jàmbá - Journal of Disaster Risk
Studies, 13(1). https://doi.org/10.4102/jamba.v13i1.1159 Google Scholar
Sami Ur Rehman, M., Shafiq, M. T., & Afzal, M. (2022). Impact of COVID-19 on project
performance in the UAE construction industry. Journal of Engineering, Design and
Technology, 20(1), 245–266. https://doi.org/10.1108/JEDT-12-2020-0481 Google Scholar
Serrador, P., & Turner, R. (2015). The Relationship between Project Success and Project
Efficiency. Project Management Journal, 46(1), 30–39. https://doi.org/10.1002/pmj.21468
Google Scholar
Simanjuntak, M. Ronald. A., & Simandjorang, G. H. (2019). Kajian Faktor-Faktor Penting
Manajer Proyek dalam Proses Konstruksi Bangunan Gedung Tinggi di Jakarta Pusat.
Prosiding Seminar Nasional Teknik Sipil UMS. http://hdl.handle.net/11617/10865 Google
Scholar
The Influence of Risk Factors on Project Cost in The Sigli-Banda Aceh Toll Road Project
40
Return: Study of Management Economic and Business, Vol 3 (1), January 2024
Sonelma, N., & Sucita, I. K. (2022). Pengaruh Kompetensi Project Manager terhadap
Keberhasilan Proyek Kontruksi Gedung Apartemen X. Construction and Material Journal,
4(1), 71–81. https://doi.org/10.32722/cmj.v4i1.4483 Google Scholar