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JURNAL SYNTAX IDEA p�ISSN: 2723-4339 e-ISSN: 2548-1398 |
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Vol. 5, No. 6, Juni 2023 |
ANALYZE THE EFFECT
OF WASTE MATERIAL AND MATERIAL MANAGEMENT WITH LEAN CONSTRUCTION TO IMPROVE
PROJECT COST PERFORMANCE
Lusi ma'rifah,
Budi Susetyo
Fakultas Teknik, Universitas Mercu Buana� �
Email: [email protected], [email protected],
Abstract
The purpose of
this study
is to
measure how significant
the influence of material management
owned by
the project team has
an impact
on the
implementation of project
financial performance. Research on stakeholder
interaction analysis is
designed based on
its objectives,
including explanatory research.
The results
showed that the application
of the
Lean Construction
approach in material
management can have
a significant
impact on improving
project cost performance.
Reducing material waste through the identification
and elimination
of waste
provides the potential
for significant
cost savings.
In addition,
the use
of effective
material management strategies,
such as
reliable supplier selection,
good inventory
control, and proper
coordination between project
teams, also contributes
to cost
efficiency. In conclusion,
material management has
a significant influence on
project financial performance
directly with the
lean construction
process.
Keywords: Cost; Lean Construction; Material Management; Waste Material.
INTRODUCTION
Sleman Regency has 574.82 km2. The
geographical location of Sleman Regency stretches from 110�13"00" to
�33"00" with Longitude 110 East, 34"51" and up to
00747"03" South Latitude, the population of Sleman Regency in 2020
according to BPS data is 1,232,598, and the population growth rate of Sleman
Regency is 1.02% in 2020.
This causes the growth rate in the
area to be quite high, and of course, it must be followed by the provision of
residential housing. So as not to make the formation of slum areas. The
development of a city brings various kinds of impacts to the pattern of life of
the community itself, one of which is the impact of the high flow of
urbanization (Ramlah, Tahir, & Ma�ruf, 2021).
Due to the need for housing for the
people of Sleman Regency and due to the lack of land available to be affordable
for low-income people (Rachmawati,
Budiarti, Febrita, & Sulistyani, 2017). So one solution for
local governments is to build flats, either public flats or special flats. From
data in the Special Region of Yogyakarta, there are 25 flats including special
flats managed not by the local government spread across 3 regencies and
Yogyakarta City, and the most flats are in Sleman Regency, totaling 7 units
with growth from 2012.
Until 2015 as many as 6 units and in
other regions such as Yogyakarta City only 3 units and in Bantul Regency 4
units, therefore the most growth in the Special Region of Yogyakarta in terms
of flats is in Sleman Regency. Through the construction of flats, it is expected
to be able to encourage urban development which is also a solution to improve the
quality of settlements.
The Ministry of Public Works and
Public Housing (PUPR) continues to increase residential development for the
community through the flats program (Rusun). For the
Yogyakarta region, for example, in 2020 823 units of flats were built and this
year it was continued again for 9,799 units.
With so many implementations of
apartment construction projects, it will cause waste that can have an impact on
ongoing projects. Waste is an activity that does not provide added value to
both customers and owners. One of the efforts to minimize the impact of time
waste is to minimize waste and increase value such as the principle of Lean
Construction (Susanti &
Suripto, 2021). Material management efforts in construction
projects can avoid material waste and accumulation of waste or material residue
in the project area that can affect the performance of a project (Liu, Yi, &
Wang, 2020).
In the implementation stage, the use
of materials is a very important resource element in realizing the planning
objectives of a construction project (Sobotka &
Czaja, 2015). However, it is different when viewed in reality
in the field where the use of materials is often allocated not optimally and
efficiently. This will have an impact on the amount of material waste that is
wasted, causing deviations from the plan's material budget with its actual
condition. Such conditions are often referred to as residual material (Devi, 2021).
In construction projects like today,
projects are required to be able to complete work on time, cost-efficient, and
good quality work. To face these challenges, methods are needed to increase effectiveness
and competitiveness in the construction market industry, from the back of the
service described above there are several problems as follows: (1) Lack of
coordination in the material management process that is weak to supervision.
(1) Low worker productivity causes work results to be less optimal and has an
impact on increasing costs and longer time as well as inappropriate quality.
(3) Lean construction work is needed so that the project's financial
performance does not exceed what has been targeted. (4) There is an
understanding of the character of the project that is not optimal.
Based on the description above behind this research or the problems identified, the formulation of this research problem is to find answers to the relationship between stakeholder interaction patterns on project implementation as follows: (a) Does the material management owned by the project team have an impact on the implementation of project financial performance? (b) Does the amount of project waste material have an impact on the implementation of the project's financial performance? (c) Do the project characteristics of the project team have an impact on the implementation of the project's financial performance?
The objectives of writing this research are: (1) Measuring
how significant the influence of material management owned by the project team
has an impact on the implementation of project financial performance. (2)
Measure how significant the effect of the amount of project material waste has
an impact on the implementation of project financial performance. The benefits
of this research (a) Provide information to create an ideal material management
pattern by maximizing each role based on their technical capabilities, within
the limits of their respective duties and authorities, so that synergies can be
well maintained which is expected to improve lean construction contribution to
the overall success of the project. (b) Able to place the method as one of the
influential methods, by providing appropriate treatment and roles and can
synergize well for the success of the project.
RESEARCH
METHODS
Research
on stakeholder interaction analysis is designed based on its objectives,
including explanatory research. Explanatory research according to Sudaryono (2017) is research that aims to describe
generalizations or explain the relationship between one variable and another.
When
viewed from the characteristics of the problem discussed, this study is
included in the type of comparative causal research (causal-comparative
research), which is research that shows the direction of the relationship
between independent variables and related variables, in addition to measuring
the strength of the relationship (Sudaryono, 2017).
Based
on the method and measurement and analysis of the data, this research is
classified as survey research (survey research), because it uses questionnaires
as its main source, and also as quantitative research (quantitative research),
which is research that aims to describe social phenomena or symptoms
quantitatively or analyze how social phenomena or symptoms that occur in
society are related to each other (Sudaryono,
2017).
The object is the whole object of research. The population of this research
is the construction of flats in Sleman. Sleman Regency has an area of 574.82
km2. The geographical location of Sleman Regency stretches from 110 13
"00" to 33 "00" with longitude 110 East, 34 "51",
and up to 007 47 "03" South Latitude. The population of Sleman
Regency in 2020 according to BPS data is 1,232,598, and the population growth
rate of Sleman Regency is 1.02% in 2020.
A
variable is an attribute or trait or value of people, objects, or activities
that have certain variations that are determined by researchers to be studied
and then draw conclusions (Sugiyono, 2017). The characteristics of the research variables
according to Sudaryono (2017) are to have a variety of values,
distinguish one object from another object in a population, and can be measured.
The data taken and collected for
this study are primary data and secondary data. Primary data by Sugiyono (2017) is
a data source that directly provides data to the data collector, while secondary
data is a data source that does not directly provide data to the data
collector, for example through another person or a document. Based on the data
collection technique, namely through questionnaires (questionnaires).
Primary
data was obtained by filling out questionnaires distributed to stakeholders as
research subjects. Secondary data are obtained through similar research
journals and research that supports the substance of this study, both research
journals on stakeholder analysis and research journals on social competence and
interpersonal skills.
Population by Sugiarti
(2018) is a generalization area consisting of objects or
subjects that have certain qualities and characteristics determined by
researchers to be studied and then draw conclusions. While according to Sugiyono (2015), The sample is part of the number
and characteristics possessed by that population. The population determined as
subjects in this study include infrastructure project stakeholders who have a
direct relationship and can have a direct impact on the project implementation
process, which is focused on: (1) Main Contractors. (2) Planning Consultant/Supervisor.
(3) Project Owner.
Sampling will be carried out with
proportionally stratified techniques according to the population distribution
of each stakeholder recorded using the Slovin formula
to determine the number of research samples needed, with a confidence level of
95% or a margin of error of 5%.
|
n |
= Number of Samples |
|
|
e |
= Margin of Error |
= 5 % |
|
N |
= Population |
= 99 Stakeholders
Interests |
From these
data and formulas, the number of samples is obtained as follows:
|
|
|
99 |
|
n |
= |
������������������������������������ |
|
|
|
1 + ( 99 x
(0.05)2 ) |
|
n |
= |
79.36 |
|
n |
= |
80 Sample |
The number
of samples based on the Slovin formula above, can be
tabulated in the table, as the distribution of the stakeholder population, and
the number of samples taken to be used as objects in this study.
Data collection techniques,
according to Sugiyono
(2019) can be divided into four kinds of
ways, namely by interviews, questionnaires, observations, and a combination of
the three. This study, following the data collection techniques in the theory
above, will be carried out with a questionnaire technique (questionnaire) that
will be distributed and filled in by respondents from samples taken from the
population determined in the discussion of this study (Nolte et al., 2019). Such as
the definition of questionnaires (questionnaires) submitted by Sudaryono (2017), that questionnaires or
questionnaires are a technique or method of collecting data indirectly
(researchers do not directly ask questions to respondents).
Descriptive statistics are statistics
used to analyze data by describing or describing the data that has been
collected as it is without the intention of making generalized conclusions or
generalizations (Sudaryono, 2017).
According to Dary (2017), Descriptive statistics are
statistics that provide an overview or description of data seen from the
average, standard deviation, maximum and minimum. In this study, this analysis
will describe the analysis of the results of the description of respondents as
filled in the questionnaire, which can be categorized statistically based on
the background of respondents, such as (a) Age of respondents. (b) Gender. (c)
Work experience and length of service. (d) Recent education.
RESULTS AND
DISCUSSION
This research was conducted by
submitting questionnaires to respondents directly or through email addresses
and electronic communication media. The total number of questionnaires
distributed in this study amounted to 80 copies, of which 80 questionnaires
have been filled in and re-received. Of the 80 questionnaires received, only 74
questionnaires could be processed, while the remaining 6 questionnaires could
not be processed because the filling data was invalid and/or filled in by
incompetent subjects in this study. The profile of respondents who participated
in this study can be described in the table as follows:
|
Variable |
Category |
Frequency |
|
Female�������������������������������������� 11 Gender��������������������������� ������������������������������������������������������������������������ Male������������������������������������������ 69 |
||
|
Work Position |
Under staff Staff |
40
|
|
|
||
|
Supervisor |
10 |
|
|
Variable |
Category |
Frequency |
|
|
Manager |
5 |
|
|
0�5 |
54 |
|
|
6�10 |
12 |
|
Work experience |
11�15 |
5 |
|
|
16�20 |
5 |
|
|
>20 |
3 |
Source: Data processing results (2023)
From the table above, an overview
of the distribution and categorization of respondents in each work position
studied can be obtained. The level of education and tenure of respondents who
are almost entirely educated above high school and also the general period of
service is above 5 years, greatly illustrates the capacity and qualifications
of respondents sufficient to be able to represent the entity of the object of
this study. The model of such interaction is determined as follows:
Picture 1 Model Lean Construction,
WAM, POC, and MAT against COP
Source: Data processing results
(2022)
A.
Evaluation of the outer
model
From the
equation model above, 3 sample modeling models will be used, namely all test
samples, and test samples. This evaluation will be used to measure loading
factors, validity, and reliability.
Figure
2 Outrr model of Lean Construction,
WAM, POC, and MAT to COP
Source:
Data
processing results (2022)
B.
Loading
factor
The loading
factor is used to see how much the indicator contributes to explaining its
construct variables.
Table 1 Loading Factor Values
|
VAR |
F. Loading |
F. Loading |
F. Loading |
F. Loading |
F. Loading |
|
COP 1 |
0.717 |
|
|
|
|
|
COP 2 |
0.743 |
|
|
|
|
|
COP 3 |
0.931 |
|
|
|
|
|
COP 4 |
0.869 |
|
|
|
|
|
COP 5 |
0.881 |
|
|
|
|
|
LEC1 |
|
0.887 |
|
|
|
|
LEC2 |
|
0.763 |
|
|
|
|
LEC3 |
|
0.885 |
|
|
|
|
LEC4 |
|
0.888 |
|
|
|
|
MAT 1 |
|
|
0.771 |
|
|
|
MAT2 |
|
|
0.727 |
|
|
|
MAT3 |
|
|
0.943 |
|
|
|
MAT4 |
|
|
0.941 |
|
|
|
MAT5 |
|
|
0.840 |
|
|
|
POC1 |
|
|
|
0.799 |
|
|
POC2 |
|
|
|
0.759 |
|
|
POC3 |
|
|
|
0.935 |
|
|
POC4 |
|
|
|
0.928 |
|
|
WAM 3 |
|
|
|
|
0.936 |
|
WAM 4 |
|
|
|
|
0.927 |
|
WAM1 |
|
|
|
|
0.823 |
|
WAM2 |
|
|
|
|
0.738 |
Source: Data processing results (2022)
C.
Convergent
validity
In addition
to using loading factor criteria, model validity testing also looks at the
results of convergent validity values using AVE values obtained from SmartPls outputs as in Table 2 below.
Table 2 Average Variance Extracted
(AVE) Value
|
|
Average Variance Extracted (AVE) |
|
Cost Performance |
0.693 |
|
Lean Construction |
0.735 |
|
Management Material |
0.721 |
|
Project Characteristic |
0.738 |
|
Waste Material |
0.739 |
Source: Data processing results (2022)
The results above show that all research variables in the sample area model are above 0.5, so it can be concluded that the convergent validity of all variables is good.
D.
Discriminant validity
Meanwhile, to see whether the measurement indicator does not have unidimensional properties, a discriminant validity measuring instrument is used by looking at the cross-loading value and the Fornell-Locker criterion. The estimation results in the model, show that all indicators in the three test sample areas have cross-loading values in their respective constructs that are higher than cross-loading values in other constructs, so all indicators can be concluded to have good discriminant validity values.
|
|
COP |
LESS |
MAT |
POC |
WAM |
|
Cost Performance |
0.832 |
|
|
|
|
|
Lean Construction |
0.319 |
0.857 |
|
|
|
|
Management
Material |
0.083 |
0.252 |
0.849 |
|
|
|
Project Characteristic |
0.089 |
0.266 |
0.991 |
0.859 |
|
|
Waste Material |
0.325 |
0.012 |
-0.098 |
-0.101 |
0.860 |
*) the value in the diagonal direction in bold is the AVE root value
Source: Data processing results
(2022)
The table above shows that all constructs have met good discriminant validity because each construct has an AVE root value higher than its highest correlation value.
E.
Inner Model Evaluation
The results of the analysis of this measurement model with PLS are shown in the figure below, which can explain the results of the R square value and its t-statistic.
Figure 3 Standardized Model of Measurement
for the entire test sample
Source: Data processing results
(2022)
Figure 4 Model t-value Measurement
for the entire test sample
Source: Data processing results (2022)
From the picture of the measurement
model results above, the equation obtained from measurement model 1 is as
follows: COP = 0.444 LEC + 0.534 WAM +
0.029 MAT, R2 = 0.706 LEC = 0.127 WAM + 0.667 MAT+0.788 POC, R2 = 0.801 POC =
0.427 WAM + 0.687 MATR2 = 0.963
Based on
this equation, it can be concluded that lean construction, material residue,
and material management have an influence of 70.6% on Cost Performance. While
the remaining 29.4% was influenced by other factors that were not included in
this study. The remaining material has the greatest influence according to this
equation with a coefficient of 0.534 in a positive and unidirectional
direction, meaning that the spatial and management of material waste and the
use of materials will directly affect the increase in the success of the
project's financial performance of 0.534 every increase of 1 unit. Meanwhile,
material management has a positive contribution of 0.029 and lean construction
can influence the success of financial performance by 0.444.
From the other equations it can be concluded, it can be concluded that
lean construction has an influence of 80.1%, from the management of remaining
materials, the character of the project, and materials management have an
influence. While the remaining 19.9% is influenced by other factors not
included in this study. Materials management has the greatest influence
according to this equation with a coefficient of 0.667 in a positive and
unidirectional direction, meaning that the implementation of material management
methods and the use of materials will directly affect the increase in the success
of the lean construction project by 0.667 for every increase of 1 unit.
Meanwhile, project characteristics have a positive contribution of 0.788 and
lean construction can have an impact on the success of financial performance of
0.127.
In the material management equation and the remaining material gives an
effect of 96.3%. The greatest influence is provided by material management
which contributes an influence of 0.667 in a positive direction. So that the
project characteristics are more influenced by material management than the
rest of the material which only has a positive influence of 0.127.
F.
The effect of lean
construction on material management, material residue, and project
characteristics on the implementation of project financial performance in all
sample data
Based on the results of hypothesis
testing on the interaction model for all sample data, it can be seen that the
H1 hypothesis which states a significant relationship between lean construction
and the success of project financial performance can be proven.
Similarly, the H2 hypothesis states
that there is a significant influence between material management on the
success of project financial performance. Indeed, no one has specifically
placed material management as a research variable in a lean contribution
pattern to the success of project financial performance. However, this research
approach can be used as a useful reference in placing material management
skills as one of the measuring variables of the lean construction model.
Similarly, the H2 hypothesis states
that there is a significant influence between material management on the
success of project financial performance. Indeed, no one has specifically
placed material management as a research variable in a lean contribution
pattern to the success of project financial performance. However, the research
approach can be used as a useful reference in placing material management
skills as one of the measuring variables of the lean construction model In
partial hypothesis each variable is known for hypothesis 3 material management
influences lean construction, material management influences project
characteristics, project characteristics influence lean construction, material
residual management provides Effect on project cost performance and material
residual management Effect on lean contractual.
In general, this measurement model,
assessing the influence of lean construction still has quite a strong role in
management patterns in infrastructure projects while project character does not
have a direct effect on the implementation of project financial performance.
This shows that the pattern of management and management of strong material
residues that are rooted in community life in both regions still dominates the
lean construction system to improve the value of project financial performance (Caldera, Desha, & Dawes, 2017). This
indicates that lean construction still has an impact on the implementation of
project financial performance.
G.
Research Implications
From the analysis and discussion
above, information was obtained about the results of partial, mediated, and
simultaneous hypothesis tests, which briefly, can be explained in the summary
of the analysis of the results as follows:
In the lean construction process,
material management and material residual management still contribute to
significant results of lean construction itself, which shows that lean
construction partially provides a significant
influence on the financial performance of the project. Similarly, the project
is characteristic of the success of the performance of the project.
While the character of the project
shows different symptoms in material management variables, where the character
of the project according to the sample is considered not to have a significant
influence on lean construction. However, if the characteristics of the project
are known with lean construction, it is not partially able to explain the
significant relationship to the success of the project's financial performance (Messah, Wirahadikusumah, & Abduh, 2017).
If you look at the mediation test,
in line with the partial hypothesis, where lean construction both as a
predictor and mediator can explain its significant relationship to the success
of project performance and success as its criterion. This is different from the
results in project characteristics where predictors and mediators can be
explained well in the relationship of significance to the success of project
financial performance as its criterion.
The explanation above proves that in
terms of project management, good material management status and waste material
management are much stronger in carrying out lean construction activities on
projects, in general, to make project financial performance good. Although the
influence of project character is still strong enough to affect lean
construction, material management, and waste material management are still very
significant.
However, when viewed simultaneously,
all research variables together, influence the success of the Project's financial
performance well. This proves that all variables of lean construction have a
significant role in the success of the project's financial performance. So that
the composition of management can be applied to determine lean construction
patterns to obtain better results.
By looking at the results above,
this study obtained an illustration, that in carrying out lean construction, in
addition to material management factors, it turns out that the management of
residual materials also influences the success of project financial
performance. So it is generally understood that,
although the influence of a strong project character affects the success of the
project, the material management side has grown considerably, and lean
construction is acceptable and coexists with project conditions.
From this explanation, the
implications of this research are expected to be the basis for determining
methods to find the right way to do lean construction to handle the project.
Construction actors can also use the results of this research in determining HR
development programs to have suitable and appropriate skills and competencies
following what is needed by project conditions.
In addition to being used for the
determination of appropriate human resources, this research can also be used to
determine the pattern of project completion that occurs both by carrying out
lean construction and between material management and waste material management
appropriately according to the conditions of the project pattern. So that in
dealing with project problems, the best solution can be produced that does not
have an impact on project implementation fatally.
CONCLUSION
The results of this study provide an overview of the process
of construction financial performance in multi-story building projects measured
based on material management variables, waste material management, and lean
construction of project financial performance. From all samples processed in
this study, the following conclusions can be compiled: (1) Material management
has a significant influence on project financial performance directly with the
lean construction process. (2) Management of residual materials has a
significant influence on financial performance. (3) Lean construction residue
consistently has a significant influence on the financial performance of the
project both on direct influence. (4) Material management and waste material
management together consistently have a significant influence on project
financial performance and lean construction both on direct influence.
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Lusi ma'rifah, Budi Susetyo (2023) |
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