osInternational Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 04, April 2019, pp. 1854-1862, Article ID: IJCIET_10_04_194
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=04
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication
Scopus Indexed
EFFECT OF BUILDING MAINTENANCE
VARIABLES IN ISLAMIC JUNIOR HIGH
SCHOOL
Agung Sedayu and Harida Samudro
Department of Architecture, Faculty of Science and Technology, State Islamic University of
Malang, Malang, Indonesia
ABSTRACT
Some educational facilities support Islamic Junior High School as educational
institutions. School building as a physical facility has a vital role in supporting learning
activities. Many buildings of educational institutions are built but not supported by
good maintenance management so that there is damage to the components of the
building. This research aims to determine the influence level of variable maintenance
of Islamic Junior High School building. This research uses a method to know the
influence level by using a mathematical model that is Structural Equation Modeling
(SEM). The mathematical equation used is the recursive path model. The location
research is building a class in Islamic Junior High School Al-Rifaie Malang Regency.
The analysis of influence level considers the user perception include teachers and
students. The research variables include facility and utility as an exogenous manifest
variable, maintenance quality as a moderator variable, and building performance as
an endogenous manifest variable. The result of the analysis describes that facility and
utility variable have a positive influence on maintaining quality. The three variables of
facility, utility, and maintenance quality have a positive influence on building
performance. The building maintenance considers the improvement priority based on
the most significant among the variables that influence the maintenance quality and
building performance.
Keywords: Influence Level, Variable, Maintenance, Building, Islamic Junior High
School
Cite this Article: Agung Sedayu and Harida Samudro, Effect of Building
Maintenance Variables in Islamic Junior High School. International Journal of Civil
Engineering and Technology, 10(04), 2019, pp. 1854-1862
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Agung Sedayu and Harida Samudro
1. INTRODUCTION
Islamic Junior High School as educational institutions are supported by some educational
facilities. School building as a physical facility has a vital role in supporting learning activities.
Many buildings of educational institutions are built but not supported by good maintenance
management so that there is damage to the components of the building. This research aims to
determine the influence level of variable maintenance of Islamic Junior High School building.
The location research is building a class in Islamic Junior High School Al-Rifaie Malang
Regency. This research has a novelty compared to the previous researches that this research
considers user perceptions of the performance of building facilities and utilities that are made
technically and knows the level of influence between the performance variables of the building.
Some of the previous researches that have become references and comparisons are research
conducted by Sedayu (2018) which aims to determine the priority of maintaining the reliability
of sustainable construction at the Ampel Mosque Surabaya. This study obtains ten variables
that affect the maintenance quality includes workability, serviceability, durability, security and
safety, architectural aesthetic system and construction material, comfort and regularity, and
maintainability. The other research that had conducted by Sedayu (2018) about service quality
modelling for housing procurement project by green building principles. Variables that
reviewed include assurance, responsibility and reliability, performance, aesthetics, easiness,
durability, architectural design, and eco-friendly. Sedayu also had researched in 2018 about
creating a model of performance optimisation of Hamid Rusdi green terminal in Malang
Indonesia. This research obtained variables contains security, safety and health, building utility,
responsibility, architectural aesthetics, transport reliability, convenience and affordability,
comfort and regularity, durability; frequency and density, availability and capacity of public
facilities, and application of environmentally friendly concepts.
2. METHOD
2.1. Research Instrument
The research instrument is questionnaires distributed to respondents. The respondents consist
of the user in Islamic Junior High School covering manager, teacher, and student so that
knowing the development of Islamic Junior High School especially component physical
building. The instrument consists of building maintenance variables that carry on the previous
researches. Some previous researches became references in preparation instrument research
such as Sedayu in 2017 researched project evaluation based on sharia construction management
and green building principles. The method used is an Importance-Performance Analysis (IPA)
and Quality Function Deployment (QFD). The research variables reviewed are assurance,
responsibility and reliability, performance, aesthetics, easiness, durability, eco-friendly, and
Islamic design. Sedayu (2016) researched evaluation of green building cottage performance
boarding school with methods Importance-Performance Analysis (IPA) and Quality Function
Deployment (QFD). The research variable obtained were sustainable, earth-friendly, and highperformance building. Kusumawardani (2016) researched description component on facade
element at the grand mosque Malang. The method used is observation, qualitative, and
descriptive. The research variable obtained includes the form, dimension, material, colour, and
texture. This research combines two methods of qualitative and quantitative. Sedayu in 2016
had finished his research about Improving service and infrastructure performance with Quality
Function Deployment (QFD) and Affinity diagram. The variables studied are Facilities,
Convenience, Security, Safety, Cost and Management services. Sugiama (2015) researches
service quality modelling on green open space or with Importance-Performance Analysis (IPA)
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Effect of Building Maintenance Variables in Islamic Junior High School
method, Quality Function Deployment (QFD), and Focus Group Discussion (FGD). The
research variables include the capability filtering solid particles from the air, the capacity of
amelioration/improvement of urban climate, water conservation level, and environmental
aesthetics. Abimaje et al. (2014) finished research about wood assessment as a sustainable
material in Nigeria. Variable reviewed research such as Workability, Durability, low thermal
conductivity, preservative treatments, and fire retardant and afforestation. Carsten Hein (2014)
researched the construction development of composite wood on high rise building with
research variables include embodied energy, low carbon, and sustainability. Muzammil (2014)
produces research variables Flood intensity, groundwater quality, flood areas, and soil types
can be developed in this study. This research develops research variables from Hasan (2014)
which consist of energy efficiency, energy audit and building automation system. Komalasari
(2014) conducted a study that became the variable reference for this study. The research topics
discussed are Green Building assessment based on energy efficiency and conservation with
comparison study method, modelling with software, and direct measurement. Research
variables reviewed include energy efficiency measure, natural and artificial lighting,
ventilation, climate change Impact, vertical transportation, and air condition system. The
Research belongs to Adebara et al. (2014) become a reference for the methods development
that is about influence analysis of timber as building construction material with Investigated
and Ranking and Quality control measures. Research variables reviewed include domestic
purposes, deforestation, over cultivation, poor irrigation practices, resulting in the loss of
biological, economic productivity of the land (Mangkoedihardjo and Samudro, 2014).
Nurakumala (2014) conducted a study aimed at determining factors affecting productivity in
construction projects with dynamic systems. The method used is Second data observation,
qualitative description, and dynamic programming. The research variables that are produced
include employee, time of execution, cost, and work environment.
2.2. Validity and Realibility Test
The validity and reliability test conduct to the research instrument by using SPSS 20.0 program.
This test was conducted on 30 people (Sugiyono, 2009 ). A validity test to determine the
validity of a questionnaire. The validity test with calculates the correlation coefficient of each
item with a total score. In this study, an instrument has high validity if the correlation value is
above the number 0.6 (Sugiyono, 2009). The calculation invalidity test uses Pearson formula.
The reliability test aims for knowing the reliability level of instrument research as a tool data
collector. Instrument called reliable if value alpha coefficient (coefficient Alpha Cronbach )
above 0,60 ( Sugiyono, 2009). Research instruments in the form of questionnaires distributed
to respondents. The measurement scale used is scaled Likert consisting of,
1. Scale 1
= Not satisfactory
2. Scale 2
= Less satisfactory
3. Scale 3
= Quite satisfactory
4. Scale 4
= Satisfactory
5. Scale 5
= Very satisfactory
The respondent's research is the user of Islamic Junior high School covering manager,
teacher, and student as much as 380 people. The determination number of respondent use
Slovin formula (Ryan, 2013)
n=
N
(1)
(1+(N x e2 ))
380
to become n = (1+(380 x 0,052 )) = 194,87 ≈ 195
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Agung Sedayu and Harida Samudro
Wiht description,
n = number of respondent
N = Total population
e = 5% error rate
The test by using Slovin formula generates 195 respondents that become a target spread
questionnaire as instrument research.
2.3. Analisys of Structural Equation Modeling (SEM)
The analysis of Structural Equation Modeling (SEM) is used to evaluate influence inter variable
to the building performance. This analysis produces mathematical models that can predict the
maintenance quality and level of building performance. The analysis of SEM is assisted by
using AMOS version 2016. The model developed is a recursive path analysis to measure the
relationship directly and indirectly inter variable in the model. The path diagram of SEM is
shown in Figure 1.
Figure 1. Path Diagram Model of SEM
Figure 1 describes the structure equation model includes,
 Facility (X1) as an exogenous manifest variable 1
 Utility (X2) as an exogenous manifest variable 2
 Maintenance Quality (Xm) as an intermediate variable (moderator).
 Performance Building (Y) as manifest endogenous variables
The model equation is in Figure 1 as follow :
Y = aX1 + bX2 + cXm + e1
4
Xm = dX1 + fX2 + e2.
5
The first step to obtaining the model that normality test of the data from the minimum
number of respondents. Every variable manifest has minimal 15 data in the form of sample or
respondent (Santoso, 2011: 70) so that the model need 15 x 4 = 60 data. The significance test
of variables by comparing estimation value to probability value (p) in the maximum likelihood
estimates. The significantly if the estimated value for all variable greater than p-value. The next
test is the convergent validity test to find out the validity of the model by comparing Variance
Extracted (VE) to the value of 0,5. The variables have a valid model if VE smaller. Table 2
describes testing in Overall Model Goodness of Fit. The test has provisions if the index (at
Table 1) has value in the interval (cut off) 0,9 <.... ≤1 the model is fit models.
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Effect of Building Maintenance Variables in Islamic Junior High School
Table 1. Test of Overall Model Goodness of Fit
Goodness of Fit
Normal Fit Index (NFI)
Incremental Fit Index (IFI)
Comparative Fit Index (CFI)
Root Mean Square Error of Approximation (RMSEA)
Cut Off
0,90 < ...≤ 1
0,90 < ...≤ 1
0,90 < ...≤ 1
<1
3. RESULTS AND DISCUSSION
3.1. Results of Validity and Reliability Test
The results of the validity and reliability test of the four variables in the model (see Figure 1)
are shown in Table 2. Table 2 explains the correlation values and alpha values for four variables
are more significant than 0,6 so that the instrument can be declared valid and reliable. The
results of data collection with this instrument can be used in Structural Equation Modeling
(SEM).
Table 2. Result of Validity and Reliability Test in Research Instrument
No.
1
2
3
4
Research Variables
Validity Test (correlation value)
Reliability Test (alpha value)
Fasility (X1)
>0,6
>0,6
>0,6
>0,6
0,933 (>0,6)
0,918 (>0,6)
0,995 (>0,6)
0,986 (>0,6)
Utility (X2)
Maintenance Quality (Xm)
Building Performance (Y)
3.2. The Results of Structural Equation Modeling (SEM)
The research variables are divided into four variables as in the SEM model (see Figure 1). The
first stage is the normality test of data that the minimum number of respondents in the model
which is entirely a manifest variable at least each variable has 15 data in the form of sample or
respondent, so the model needs = 15 x 4 = 60 data. This research uses 95 respondents that
support the requirements of standard distributed data to be fulfilled. The significance test of the
variable is generated by comparing the estimated value with the probability value (p) in
Maximum Likelihood Estimates as in Table 3.
Table 3. Regression Weights Variabel
The Relationship Between Variables
Maintenance Quality
Facility (X1)
→
(Xm)
Estimate
S.E.
C.R.
P
Signicancy
0,302
0,247 3,774
***
Significant
Utility (X2)
→
Maintenance Quality
(Xm)
0,411
0,214 6,004
***
Significant
Facility (X1)
→
Building Performance
(Y)
0,376
0,138 3,847
***
Significant
Utility (X2)
→
Building Performance
(Y)
0,528
0,226 4,108
***
Significant
Maintenance Quality
Building Performance
→
(Xm)
(Y)
0,637
0,259 3,523
***
Significant
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Table 3 describes that value estimate for all variable greater than P value. The effect of
these variables is significant. The p-value = *** means 0,001. The convergent validity test to
know correlation model by comparing value Variance extracted to the value of 0,5.
Table 4. Standardized Regression Weights Variabel
The Relationship Between Variables
Estimate
Facility (X1)
→
Maintenance Quality (Xm)
0,478
Utility (X2)
→
Maintenance Quality (Xm)
0,449
Facility (X1)
→
Building Performance
0,492
Utility (X2)
→
Building Performance
Maintenance Quality (Xm)
→
Building Performance
(Y)
(Y)
(Y)
Variance extracted
Validity
0,215
Valid
0,268
Valid
0,527
0,534
The correlation describes the influence inter variable in the analysis of SEM is shown with
the value coefficient of determination. The influence model of maintenance quality and
building performance obtain:
 Influence Model of Total variable (overall) : Y = 0,492X1 + 0,527X2 + 0,534Xm
 Influence Model of intermediate variable (moderator) : Xm = 0,478X1 + 0,449X2
Table 4 describes the Variance extracted value is less than 0.5 (Santoso, 2011: 113) [18],
which can be calculated as follows,
-Variable of Maintenance Quality (Xm) =
0,4782  0,4492 0,228  0,202 0,430


 0,215< 0,5
2
2
2
-Variable of Building Performance (Y) =
0,4922  0,527`2 0,5342 0,242  0,278  0,285 0,805


 0,268 <
3
3
3
0,5
The model is valid with the arrangement of the variables. Table 5 shows the estimated value
between Facility (X1) with Utility (X2), whereas Table 6 show estimate value between
Maintenance Quality (Xm) with Building Performance (Y). The results of this analysis generate
a path diagram model as shown in Figure 2.
Table 5. Corelation X1 with X2
The Relationship Between Variables
Facility (X1)
↔
Estimate
Utility (X2)
0,385
Table 6. Corelation Xm with Y
Variable
Estimate
Maintenance Quality (Xm)
Building Performance (Y)
0,874
0,823
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Effect of Building Maintenance Variables in Islamic Junior High School
Figure 2. Model Diagram of SEM at Al- Rifaie Islamic Junior High School Malang
The relationship between variables shows a healthy level of significance. Table 4 shows
the path diagram model that Maintenance Quality (Xm) is explained by Facility (X1) and Utility
(X2) of 87,4 %. While Building Performance (Y) which can be explained by Facility (X1),
Maintenance Quality (Xm), and Utility (X2) of 82,3 %. While the path diagram model generates
direct and indirect influence inter variable. This results also obtain total influence = direct
influence + indirect influence. The conclusion of this results that relationship influence in the
model has positive values (see Table 7).
Table 7. The relationship influence between variables
Relationship between
Variable
X1 → Y
X2 → Y
Xm → Y
X1 → Xm
X2 → Xm
X1 → X2 (recursive)
Direct
Influence
0,492
0,527
0,534
0,478
0,449
0,385
Indirect Influence
Total Influence
(0,478) x (0,534) = 0,255
(0,449) x (0,534) = 0,240
-
0,747
0,767
0,534
0,478
0,449
0,385
4. CONCLUSION
The research results generate models of SEM with the facility (X1) as a variable manifest
exogenous 1, utility (X2) as a variable manifest exogenous 2, maintenance quality (Xm) as an
intermediate variable (moderator), and building performance (Y) as an endogenous manifest
variable. The first stage is the data normality test that the minimum number in the model which
is entirely a variable at least each variable has 15 data in the form of sample or respondent, so
it has 15 x 4 = 60 data. This research uses 95 respondents that support the requirements of the
data are normally distributed considered to be fulfilled. The significance tests of the variable
compare the estimated value with the probability value (p) in the maximum estimate value. The
estimate values that resulted from all variables are greater than the P value. It means that the
influence between variables is very significant. The results of analysis obtain value of variance
extracted smaller than 0.5, so it can be concluded that the model is valid. Model influence of
building maintenance at Al-Rifaie Islamic Junior High School in Malang consists of models
influence total variable (overall): Y = 0,492X1 + 0,527X2 + 0,534 Xm and model the influence
of the intermediate variable (moderator) : Xm = 0,478X1 + 0,449X2. The relationship between
variables shows a strong level of significance. The variability of maintenance quality (Xm) is
explained by the facility (X1) and Utility (X2) of 87,4 %. Whereas building performance (Y)
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which can be explained by the variability of the facility (X1), maintenance quality (Xm), and
utility (X2) of 82,3 %. While the path diagram model generates a direct and indirect influence
between variables. This results also generate total influence = direct influence + indirect
influence. The results conclude that the relationship influence in the model has positive values.
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