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php/RANGTEKNIKJOURNAL ANALYSIS OF HUMAN RESOURCES THAT INFLUENCE CONTRACTOR
PERFORMANCE IN BUILDING CONSTRUCTION PROJECT
IMPLEMENTATION
YOPPI NOVRIADI1.
WARDI2.
ZUHERNA MIZWAR3
Fakultas Teknik.
Univesitas Bung Hatta Email: yoppinovriadi23@gmail.
http://dx.
org/10.
31869/rtj.
Abstract: This research is to identify and determine human resource factors that influence contractor performance in building construction projects and provide solutions to improve the performance of contractor human resources in Payakumbuh City.
This research method uses a quantitative approach.
The results of data analysis obtained Determination coefficient value (R-Squar.
515 or 51.
5%, this shows that all variables competency, motivation, loyalty, compensation, discipline and work environment simultaneously influence the contractor's performance variables, while the remaining 48.
Influenced by other variables not tested in the research.
From the calculated F value, it is 17,873, while the resulting significant value is 0,000 < 0,05, it is concluded that all variables competency, motivation, loyalty, compensation, discipline and work environment simultaneously influence the contractor's performance variables.
From the results of the t test calculations, it is concluded that competence, motivation and discipline have a partial influence on contractor Based on the largest t value, the most dominant human resource factor is Motivation (X.
because it is found that t count > t table .
415 > 1.
, and the significance value is 0.
000 < 0.
Keywords: Human Resources.
Performance.
Contractors.
Projects.
Construction Introduction A construction project is a collection of interrelated activities that have a starting and ending point and a desired final result.
Most projects involve cross-functional organizations, which means they require different types of expertise/skills from different jobs.
Each project is different, and none are the same.
A project is an effort that requires resources to achieve certain goals, targets and expectations (Devina, 2.
A building project is an activity carried out over a certain period of time and involves several resources which are one aspect of project completion, consisting of human resources, costs, materials, equipment and With effective resource management, projects can be completed with cost, quality, efficiency and benefit to society.
(Jajang, 2.
The increasingly rapid pace of the Government in increasing the growth of the construction industry, especially in Payakumbuh City, which continues to carry out regional infrastructure development every year, including building construction projects became a breakthrough for the regional government of Payakumbuh City With the aim of supporting activities in the government and economic sectors in order to improve community welfare one of the success factors in implementing building construction projects is the contribution and role of contractors who have competent and experienced human resources.
However, the performance of building construction projects in Payakumbuh City shows that the role of human resources has not been carried out optimally, as can be seen from the lack of productivity of human resources, which hinders project acceleration (Gray, 2.
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php/RANGTEKNIKJOURNAL Other problems include delays in completing work according to the contract, which can result in fines, several work packages resulting in termination of the contract and being subject to blacklisting sanctions, failures and quality defects in work, which are mostly caused by the contractor's management human resources not having competence and only functioning as a complement to the administrative requirements to complete the tender According to Shah .
, another cause of work delays is the contractor's ineffectiveness in the management aspecthuman Resources and activities during project implementation, as well as changes in weather at the project location, which cause the project to be delayed or stopped.
Adequate human resources and natural resources are needed in construction project work.
As a result of implementing activities in the field, contractor companies show a lack of competence and low performance of the human resources involved.
The real fact is that the human resources involved in the project usually do not have the competence or quality because the contractor focuses on educational qualifications rather than quality.
This has an impact on the low performance of human resources both from the implementation aspect in the field and the project administration aspect (Widiasanti, 2.
The low performance human Resources in development project building construction, especially on project with size secondary until height, impact on failure implementation project, especially in terms of dimensions quality which produced (Willy, 2.
Indicator low performance human Resources contractor, like lack understanding to specification technical work Which done, result quality work Which produced No achieved, less understand method work, result solution the project does not appropriate time, less understand budget cost implementation, result cost implementation swollen or even resultloss, lack of implementation of the system management occupational safety and health resulting in work accidents (Barrie, 2.
The quality of the workforce can be influenced by two factors, namely internal factors that come from within the workforce themselves such as formal education, work experience, physical characteristics in the form of physical health, as well as personal characteristics and personality types of the workforce, while external factors influence the quality of the Work can come from the work environment and company management system (Simamora, 2.
One of reason low performance human Resources in implementation and control projectBecause caused by a number of factor like desire for increase productivity work so that finished appropriate time, without consider quality work, and lack understanding human Resources Of area related with quality work or Which shown in plan stop contract onwork (Setiawan, 2.
Based on data from PBJ & Dalbang Section of Payakumbuh City Regional Secretariat There are 75 building construction work packages in the last 5 .
which were carried out through a tender process with small qualifications.
Of the 75 work packages, 12 work packages experienced delays in work completion .
%).
In 2017 there were 19 work packages with 2 work packages experiencing delays in completing the work .
53%), in 2018 there were 7 work packages with 2 work packages experiencing delays in completing the work .
57%), in 2019 there were 19 work packages with 4 work packages experienced delays in completion .
05%), in 2020 there were 8 work packages with 2 work packages experiencing delays in work completion .
%), and in 2021 there were 22 work packages with 2 work packages experiencing delays in work completion .
, 09%)(Data from the PBJ & Dalbang Section of Payakumbuh Regional Secretariat, 2.
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php/RANGTEKNIKJOURNAL Based on an interview with the Head of the Public Works and Spatial Planning Department of Payakumbuh City, several problems that are often encountered in building construction projects in Payakumbuh City can be described as follows: .
There is a delay in completing the work according to the implementation time agreed upon in the Agreement Letter (Contrac.
resulting in the need for additional or extension of implementation time and a late fine will be imposed during the extended implementation time period.
This is due to the lack of competence and experience of site managers / field implementers in selecting and implementing building construction work implementation methods.
Some work results were found to have to be redone/repaired due to physical defects/imperfections because they did not comply with the technical specifications listed inin the Letter of Agreement or contractand there was also a shortage of work volume at the time of the first handover of the first job (PHO), so more time was needed for physical improvements and additional work volume at the time of the first handover of the first job (PHO).
This was caused by a lack of control fromsite manager / field implementer and lack of supervision from supervisory .
Termination of contracts and blacklisting sanctions for several building construction project packages due to the inability to complete all the work and not achieving 100% work weight until the end of the implementation period, thus causing the building to be abandoned and unable to be used or utilized properly.
Wrong One the cause is lack role and low performance human Resources in implementation and project control.
Because caused by a number of factor between other, desire to complete the work quickly or on time, but ignoring the quality of the work and lack of understanding by human resources about the quality of the work as stated in the work contract quality plan (Payakumbuh City PUPR Service, 2.
Methods In this research the author used a quantitative approach.
In this research, the population is several SKPD within the Regional Government of Payakumbuh City as Project Owners.
Contractors and Supervising Consultants on building construction projects that experienced delays in completing work in Payakumbuh City from 2017 to 2021 which was carried out through a tender process with little qualification.
There are several SKPDs within the Regional Government of Payakumbuh City as the Project Owner (Owne.
, including 7 .
SKPDs, including the Public Works and Spatial Planning Service.
Education Service.
Health Service.
Tourism.
Youth and Sports Service.
Dr.
RSUD.
Adnaan WD and North Payakumbuh District, contractors for 12 .
companies and supervisory consultants for 12 .
This research used 108 samples, consisting of several SKPDs within the Regional Government of Payakumbuh City as Project Owners .
, 36 Contractors, and 48 Supervisory Consultants.
The stages that will be carried out in this research are as follows:
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php/RANGTEKNIKJOURNAL Start Research purposes Data collection Objective 1 Objective 2 Objective 3 Literature Review Making Que stionna ires - Instrument Measurement - Dete rmination of Respondents Distribution of Questionnaires Ana lysis Results Objective 1 Ana lysis Results Objective 2 Data analysis Objective 1 Objective 2 Objective 3 Test KMO and Bartlet's Validity test Reliability Test Classic assumption test - Normality test - Multicollinearity Test - Heteroscedasticity Test Approach with the SWOT analysis method:
- Strength components - Component of weakness (Weaknes.
- Opportunity Components (Opportunitie.
- Challenge Component .
Multiple Linear Regression Analysis - Uji R2 - Uji F (F Tes.
- Uji T (T Tes.
Conclusions and recommendations End Fig.
1 Research Stages Results and Discussion Data Analysis Objective I Before carrying out data analysis for objective I, the instrument is first tested through validity and reliability tests to obtain a valid and reliable instrument.
Test Assumptions/KMO (Kaiser Mayer Oike.
and BartlettAos From the test results KMO (Kaiser Mayer Oike.
and BartlettAos.
The results obtained for each factor are as follows:
Table 1.
Recapitulation of KMO and Bartlett's Test Results Values KMO Test Factor Bartlett's significance value Result Competency (X.
0,700 0,000 Motivation (X.
0,669 0,000 Loyalty (X.
0,646 0,000 Compensation (X.
0,592 0,000 Discipline (X.
0,662 0,000 Work Environment 0,555 0,000 (X.
Source: Data processing results .
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php/RANGTEKNIKJOURNAL The test results shown in Table 1 found that each factor that influences the performance of contractors in the implementation of building construction projects in Payakumbuh City has met the requirements and this shows the adequacy of the number of samples and there is a correlation between the independent variables.
Validity test The results of the validity test analysis of each variable are as follows:
Table 2 Recapitulation Validity Test Variable r Table Factor r Count Information Code X1.
0,665
0,195
Valid X1.
0,583
0,195
Valid Competency (X.
X1.
0,484
0,195
Valid X1.
0,714
0,195
Valid X1.
0,669
0,195
Valid X2.
0,686
0,195
Valid X2.
0,599
0,195
Valid X2.
0,515
0,195
Valid Motivation (X.
X2.
0,613
0,195
Valid X2.
0,706
0,195
Valid X2.
0,702
0,195
Valid X3.
0,811
0,195
Valid X3.
0,346
0,195
Valid Loyalty (X.
X3.
0,284
0,195
Valid X3.
0,859
0,195
Valid X3.
0,800
0,195
Valid X4.
0,657
0,195
Valid X4.
0,708
0,195
Valid Compensation (X.
X4.
0,364
0,195
Valid X4.
0,574
0,195
Valid X5.
0,715
0,195
Valid X5.
0,721
0,195
Valid Discipline (X.
X5.
0,698
0,195
Valid X5.
0,789
0,195
Valid X6.
0,513
0,195
Valid X6.
0,646
0,195
Valid Work Environment (X.
X6.
0,646
0,195
Valid X6.
0,674
0,195
Valid X6.
0,533
0,195
Valid Y1.
0,700
0,195
Valid Contractor Performance Y2.
0,739
0,195
Valid
(Y)
Y3.
0,719
0,195
Valid Source: Data processing results .
Based on Table 2, from the results of the validity test on each variable, the analysis results show that all variables are declared valid.
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Reliability Test The results of the reliability test in this research can be seen from the following table:
Table 3.
Reliability Test Results Reliability Statistics Cronbach's Alpha N of Items Source: Data processing results .
Based on Table 3, the results of the reliability test/reliability statistics above can be said to be reliable.
Discussion of Objectives I From the results of the analysis of objective I, the KMO and Bartlett's test results were 5 and the Bartlett's significance value was 0.
This shows the adequacy of the sample size and that there is a correlation between the independent variables.
The results of the validity test on each variable showed that all variables were declared valid.
From the Reliability test, a Cronbach's Alpha value was obtained of 0.
672 Ou 0.
60, this shows that there is a strong and positive correlation between the independent variables .
ompetence, motivation, loyalty, compensation, discipline and work environmen.
and the dependent variable (Contractor Performanc.
Data Analysis Objective II Classic assumption test .
Normality Test The normality test can be carried out using the normal probability plot method in SPSS.
Table 4.
Kolmogorov Smirnov Normality Test Results One-Sample KolmogorovSmirnov Test Unstandardized Residual Normal Parametersa,b Mean Std.
Deviation Most Extreme Differences Absolute Positive Negative Kolmogorov-Smirnov Z Asymp.
Sig.
-taile.
Test distribution is Normal.
Calculated from data.
Source: Data processing results .
Based on Table 4.
Based on the Normality test resultsKolmogorov Smirnov earned valueAsymptotic Significance .
-taile.
as big as 0,622.
Because the significance is more than 0.
05, the residuals are normally distributed.
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Graph Normal P-Plot Based on Fig 2, the results of the normality test using the P-Plot above can be seen that the points are spread around the diagonal line and follow the direction of the diagonal line.
Multikolinieritas Test When carrying out a multicollinearity test in a multiple regression model, it can be done by looking at the valuestolerance andVariance Inflation Factor (VIF), if valuetolerance > 0.
1 or a VIF value < 10 means there is no multicollinearity in the multiple regression model:
Table 5.
Multikolinieritas Result Test Modle Collinearity Statistics Tolerance VIF 1 (Constan.
Dependent Variable : Y Source: Data processing results .
Based on Table 5, valuetolerance andVIF of all independent variables.
Earned valuetolerance of all the independent variables are all greater than 0.
1 and the VIF values are all smaller than 10, it can be stated that there is no multicollinearity between the independent Heteroskedastitas Test The heteroscedasticity test is carried out to determine whether the regression model has unequal variance between the residuals from one observation to another (Ghozali, 2.
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3 Graph Scatterplot Based on Fig 3 above, it can be seen that the distribution of points forms an unclear pattern and spreads above and below zero at point y.
So it is concluded that there is no heteroscedasticity in this regression model.
Multiple Linear Regression Analysis From the multiple linear regression analysis, the following analysis results were obtained:
Table 6 Coefficients (Regresi Linier Bergand.
Model Unstandardized Coefficients Standardized Coefficients Sig.
Std.
Error Beta 1 (Constan.
Dependent Variable : Kinerja Kontraktor (Y) Source: Data processing results .
From Table 6 Coefficients (Multiple Linear Regressio.
obtained Human Resources factors that have an influence on Contractor Performance, namely .
Competency factor (X.
, with a value of sig.
025 < 0.
05, .
motivation factor (X.
, with Sig.
000 < 0.
05, .
000 < 0.
05, indicating that it is significant.
Because it is 0.
000, it is the most significant .
loyalty factor (X.
, with a sig value.
108 > 0.
05, .
competency factor (X.
, with a sig value.
908 > 0.
05, .
discipline factor (X.
, with a Sig value.
007 < 0.
05, .
work environment factors (X.
, with a Sig value.
213 > 0.
Ctt .
ignificant < 0.
05, t calculated with a value of min (-) shows that it has a negative effec.
So the most dominant factor is the motivation factor (X.
because it has the highest regression coefficient (B) of Based on table B obtained from multiple linear regression analysis, the following regression equation model can be formed:
Y = 2,777 0,112 X1 0,214 X2, 0,069 X3 0,008 X4 0,157 X5-0,062 X6
This multiple linear regression equation explains that:
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The constant value .
has a positive value of 2.
The positive sign means that it shows a unidirectional influence between the independent variable and the dependent This shows that if all independent variables which include competence (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline (X.
and work environment (X.
have a value of 0 percent or have not changed, then contractor performance value (Y) is 2.
The regression coefficient value for competency (X.
has a positive value of 0.
This shows that if competency (X.
increases by 1%, then the contractor's performance (Y) will increase by 0.
112 assuming other independent variables are considered constant.
A positive sign means that it shows a unidirectional influence between the independent variable and the dependent variable.
The regression coefficient value for motivation (X.
has a positive value of 0.
This shows that if motivation (X.
increases by 1%, then the contractor's performance (Y) will increase by 0.
214 assuming the other independent variables are considered A positive sign means that it shows a unidirectional influence between the independent variable and the dependent variable The regression coefficient value for loyalty (X.
has a positive value of 0.
This shows that if loyalty (X.
increases by 1%, then contractor performance (Y) will increase by 0.
069 assuming other independent variables are considered constant.
positive sign means that it shows a unidirectional influence between the independent variable and the dependent variable The regression coefficient value for compensation (X.
has a positive value of 0.
This shows that if compensation (X.
increases by 1%, then the contractor's performance (Y) will increase by 0.
008 assuming other independent variables are considered constant.
A positive sign means that it shows a unidirectional influence between the independent variable and the dependent variable The regression coefficient value for discipline (X.
has a positive value of 0.
This shows that if discipline (X.
increases by 1%, then contractor performance (Y) will increase by 0.
157 assuming other independent variables are considered constant.
positive sign means that it shows a unidirectional influence between the independent variable and the dependent variable The regression coefficient value for the work environment variable (X.
This value shows a negative influence .
n the opposite directio.
between the work environment variable (X.
and contractor performance (Y).
This means that if the work environment variable (X.
experiences an increase of 1%, then on the other hand the contractor performance variable (Y) will experience a decrease of 0.
Assuming that other variables are held constant.
Based on the above, if the competency factor (X.
increases with the assumption that other factors remain constant, the contractor's performance will also increase, and so will the treatment for other factors, namely when the value is B for the Human Resources factor.
(X)
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php/RANGTEKNIKJOURNAL Coefficient of Determination Test (RA) This coefficient of determination is used to determine the magnitude of the influence of the independent variable on the dependent variable.
The value of the coefficient of determination is determined by value Adjusted R square.
Table 7 Model Summary Model Change Statistics Std.
Error Adjusted of the Square Sig.
R Square R Square Estimate Change Change df1 df2 Change 873 6 101 Predictors: (Constan.
X6.
X4.
X1.
X3.
X2.
X5 Source: Data processing results .
Based on Table 7, the value of the Coefficient of Determination (R-Squar.
515 or equal This shows that all independent variables, namelycompetency (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline (X.
and work environment (X.
,simultaneously .
the effect is equal to51,5% on the dependent/independent variable Contractor Performance (Y).
While the remainder is .
%-51.
5% =48,5%)
influenced by other variables not tested in the research.
Uji F (F-Tes.
The provisions of the F test (Ghozali, 2.
are as follows:
If the significant value F < 0.
05 then H0rejected and H1 accepted.
This means that all independent/free variables have a significant influence on the dependent/dependent .
If the significant value F> 0.
05 then H0 accepted and H1 This means that all independent variables do not have a significant influence on the dependent variable.
Tabel 8.
ANOVA
Model Sum of Squares Mean Square Sig.
1 Regression Residual Total Predictors: (Constan.
, work environment (X.
, compensation (X.
, competence (X.
, loyalty (X.
, motivation (X.
, discipline (X.
Dependent Variable: Contractor Performance (Y) Source: Data processing results .
Based on Table 8, it can be concluded that H0rejected and H1 accepted.
This can be seen from the calculated F value, which is 17.
Meanwhile, the resulting significance value is0,000 < 0,05.
It can be concluded that this multiple linear regression model is suitable for use and includes independent variablescompetency (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline (X.
and work environment (X.
has a simultaneous influence on the dependent variable contractor performance (Y) or the hypothesis is accepted.
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The T test was carried out to determine the level of relationship between factor .
The basis for decision making in the T test is that if the calculated T value > T table then factor X (Human Resource.
influences Y (Contractor Performanc.
Table 9.
Coefficients Source Coefisien tcount Sig.
Information Source Influential Motivation (X.
Influential Loyalty (X.
No effect Compensation (X.
No effect Discipline (X.
Influential Work Environment (X.
No effect Source: Data processing results .
Table 10.
T Test Result Source Competency (X.
Motivation (X.
Loyalty (X.
Compensation (X.
Discipline (X.
Work Environment (X.
Significant level 5% .
Source: Data processing results .
Information Influential Influential No effect No effect Influential No effect Based on Table 10, the T test results in the table above show the following:
From the table above, we get the t calculated effect of Competency (X.
on Contractor Performance (Y) of 2.
268 and a significance of 0.
025, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get t calculated > t table .
268 > 1.
and the significance value of 0.
025 is smaller than 0.
05, it can be concluded that the Competency variable (X.
has an influence on the Contractor Performance variable (Y).
From the table above, the t count of the influence of Motivation (X.
on Contractor Performance (Y) is 5.
415 and the significance is 0.
009, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get t count > t table .
415 > 1.
, and the significance value of 0.
009 is smaller than 0.
05, so it can be concluded that the Motivation variable (X.
has an influence on the Contractor Performance variable (Y).
From the table above, we get the t count of the effect of Loyalty (X.
on Contractor Performance (Y) of 1.
621 and a significance of 0.
108, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get t count < t table .
621 < 1.
, and the significance value of 0.
108 is greater than 0.
05, so it can be concluded that the Loyalty variable (X.
has no influence on the Contractor Performance variable (Y).
From the table above, we get the calculated t effect of Compensation (X.
on Contractor Performance (Y) of 0.
116 and a significance of 0.
908, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get t calculated < t table .
116 < 1.
and the significance value of 0.
908 is greater than 0.
05, so it can be concluded that the ISSN 2599-2081
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has no influence on the Contractor Performance variable (Y).
From the table above, the t count of the effect of Discipline (X.
on Contractor Performance (Y) is 2.
749 and the significance is 0.
007, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get t count > t table .
749 > 1.
, and the significance value of 0.
007 is smaller than 0.
05, so it can be concluded that the Discipline variable (X.
has no influence on the Contractor Performance variable (Y).
From the table above, we get the calculated t effect of the Work Environment (X.
on Contractor Performance (Y) of 1.
253 and a significance of 0.
213, where the t table .
k = n-k-1 = 108-6-1 = .
980, we get the t calculated < t table .
, and the significance value of 0.
213 is greater than 0.
05, it can be concluded that the Work Environment variable (X.
has an influence on the Contractor Performance variable (Y).
From the results of the T Test above, it can be concluded that competency factors (X.
, motivation factors (X.
and discipline factors (X.
have a partial influence on Contractor Performance (Y).
The dominant factor in this research is the Motivation factor (X.
because it is found that t count > t table .
415 > 1.
, and the significance value of 0.
009 is smaller 05, which consists of the variables improving work ability (X2.
, support and company guarantees for achievement (X2.
, desire to achieve work achievements (X2.
application of professional teamwork (X2.
, recognition and appreciation for work results (X2.
, work situations and relationships good (X2.
Conclusions The conclusions from this research are:
From research literature studies relevant to this research, human resource factors can be identified that influence contractor performance on building construction projects in Payakumbuh, namely the independent variables competence (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline ( X.
and work environment (X.
and the dependent variable contractor performance (Y).
The results of the multiple linear regression analysis calculations obtained are:
Y = 2.
112 X1 0.
214 X2, 0.
069 This shows that all the variables competency (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline (X.
and work environment (X.
, simultaneously have an influence of 51.
5% on the Contractor Performance variable (Y).
While the remaining 48.
5% influenced by other variables not tested in the research.
From the calculated F value, it is 17,873, while the resulting significant value is 0.
000 < 0.
It can be concluded that this multiple linear regression model is suitable for use and competence (X.
, motivation (X.
, loyalty (X.
, compensation (X.
, discipline (X.
and work environment (X.
have a simultaneous influence on contractor performance (Y ).
From the results of the t test calculations, the t value for Competency (X.
is 2,268, the t value for Motivation (X.
is 5,415, the t value for Loyalty (X.
is 1,621, the t value for Compensation (X.
116, the t value for Discipline (X.
is 2,749, and the calculated t value for the Work Environment (X.
is 1,253 while the t table value is 1,980, with the conclusion that competence (X.
, motivation (X.
and discipline (X.
have a partial influence on Contractor Performance ( Y) because it is found that t count > t tabl.
, and the ISSN 2599-2081
EISSN 2599-2090
Fakultas Teknik UM Sumatera Barat Vol.
7 No.
1 Januari 2024 Rang Teknik Journal http://jurnal.
id/index.
php/RANGTEKNIKJOURNAL significance value is smaller than 0.
Based on the largest t value, the most dominant human resource factor is Motivation (X.
because it is found that t count > t table .
415 > 1.
, and the significance value of 0.
000 is smaller than 0.
Alternative solutions that must be implemented are as follows: .
Establishing good communication between Human Resources on the project.
Improving the conditions of the workforce or Human Resources on the project.
Give awards to Human Resources who contribute good work to create stronger work motivation.
Provide clear information and training to contractor Human Resources so that teamwork can be implemented .
Provide recognition and appreciation for work results, so that a good working situation and relationship is established.
Providing allowances and salaries on time so that Human Resources motivation increases References