Analysis of Factors Affecting Property Value at Residence with

Cluster Concept: Case Study - J City Residence

F. F. Sigit

, K. A. Fachrudin

and H. T. Fachrudin

Master of Property Management and Valuation Program, Universitas Sumatera Utara, Jl. dr. Mansur Campus USU,

Medan 20155

Faculty of Economic and Business, UniversitasSumatera Utara, Jl. TM Hanafiah Kampus USU, Medan 20155

Faculty of Engineering, UniversitasSumatera Utara, Jl. Almamater KampusUSU, Medan 20155

Keywords: Property value, Location, Facility, Design, Neighbourhood, Cluster Characteristic.

Abstract: Most of the citizens choose to live in the residence. The need of residence based on trends lead to the

development of many residential properties offering residence with cluster type. J City is one of the cluster

residences with three types of clusters that have different property values. The purpose of this research is to

know and analysis the impact of location, facility, design, neighbourhood and cluster character to property

value. The population was taken with a sample of 87 respondents in the residence. The testing of hypothesis

uses multiple linear regression test with the level of significance 5%. Statistical application program SPSS

and STATCAL are used to analysis data. The results of this study indicate that simultaneously and partially

where the location, facility, design, neighbourhood, and cluster characteristics have a positive and

significant effect on the value of residence property on J City residence cluster.

1 INTRODUCTION

The real estate market is one of the most rapidly

developing goods markets that attract massive

investments (Renigier-Biłozor, 2015). Some people

assume that live in the residence has many benefits

in terms of security, comfort, and tranquillity. Real

estate development is the continual reconfiguration

of the built environment to meet society’s needs

(Baldi, 2013).

The property value is determined by several

factors, namely: physical, location, and law. In

physical factor, there are several components that

are considered appropriate such as property area,

building facility, quality construction, and land area

(Fanning, 2005). Basically property prices affected

by demand, usability, scarcity and transferability

(Eldred, 1987). The factors that affect the value of a

property are divided into 4 factors, namely demand

and supply factor, physical property factor, location

and placement factor, and national and political

factors (Hidayati and Budi, 2001).

The needs of home based on trends cause many

development of residence property offering cluster

type residence. Along with the lifestyle of citizens

that is dynamic modern society is more likely to

require a home with various facilities such as sports

facilities, security, recreation in one area (Nugroho,

2015).

Currently in KaryaWisata region is growing with

various residential properties that are constantly

increasing. Various residences appear both

conventional and cluster residence.J City is one of

the cluster residence in Medan City with three

different cluster types namely J Crown, J Elite, and J

Metropolis. These three types of residence have

different property prices with different land values.

Table 1: Differences house price on J City

Cluster

Type

Property price Market Value

J Crown Rp1.680.160.000 Rp1.700.000.000

J Elite Rp 1.072.000.000 Rp 900.000.000

J Metropolis

 Monaco

 Milan



Madri

Rp 954.700.000

Rp 686.500.000

Rp 499.480.000

Rp 850.000.000

Rp 750.000.000

Rp 500.000.000

Table 1 showed that some market value is higher

than property value given from the developer but the

phenomenon in this research is where market value

Sigit, F., Fachrudin, K. and Fachrudin, H.

Analysis of Factors Affecting Property Value at Residence with Cluster Concept: Case Study - J City Residence.

DOI: 10.5220/0010074313471351

In Proceedings of the International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches (ICOSTEERR 2018) - Research in Industry 4.0, pages

1347-1351

ISBN: 978-989-758-449-7

1347

of J Elite and J Metropolis Monaco are lower than

new house’s property price.

The problem formulation in this research is

whether the location, facility, design,

neighbourhood, and cluster characteristics affect the

property value in J City residence. The purpose of

this research is to know and analysis simultaneously

and partially how big location, facility, design,

neighbourhood, and cluster character have influence

to value property at house J City.

2 LITERATURE REVIEW

2.1 Cluster Residence

Cluster residence is a cluster concept using one

access (gate) to exit and enter, the application of one

access allows all mobility within the cluster to be

monitored by security personnel (Widodo, 2012).

Residence with cluster type, which is residence that

classifies an architectural style of the same

residential building and is intended for upper middle

class society who tend to have a modern lifestyle

(Okterina, 2008).Cluster residence model is

collection of buildings without guard rail in real

estate with the main gate as security control, should

not modification facade to beautify the house or put

the guard rail to safety (Kustamar, 2013).

The advantages of cluster residenceare (Widodo,

2012):

 Resident’s privacy and safety are more safe with

one gate system

 The safety of children is higher, because the

traffic is not crowded

 Voice pollution can be suppressed

 Support the environmental program with the

existence of environmental planting as a water

catchment area

 There is a balance between integrated security

with a good socialization life

 Integrated housing becomes one, there are

workplaces, homes and recreation areas

The disadvantages of cluster residenceare

(Kustamar, 2013):

 There is an additional cost to pay for security

guards or housing security, but on the other hand

this is good because it can create new jobs

 The security of a secure housing environment in

cluster residence may be misused by residents by

parking vehicles carelessly on the road so that it

can disturb neighbuors or the other road users

 The absence of freedom in modifying the

architectural appearance of facade so that the

houses seems standard and uniform.

 Residents must really like the design of the house

because to add trinkets in the future especially

the fence design may not be possible unless the

cluster residence rules are no longer used

2.2 Property Value

The real property represents most of the world's

wealth, and its valuation is very important to the

survival of global property and financial markets

(IVSC, 2003). The value of a property such as land

influenced by factors influencing the motivation of a

human activity is differentiated into social,

economic, governmental, and environmental factors

(Walcott, 1987).

(Chin and Chau, 2002) classify attributes that

determine values on residential property are

locational, structural, and neighbourhood factors.

According to (Wong, 2002), property attributes are

classified into three classes, namely, location

attributes (access to social and economic facilities),

structural traits (floor area, floor height, etc.) and

neighbourhood characteristics (neighbourhood

quality). (Choy, 2007) mentioned that property

valuehas been established to be a function of some

attributes on the residence and supporting attributes

such as, neighbourhood characteristics, accessibility

and environmental quality.

Price of the real estate property in international

housing market have differences because in terms of

culture, economics, spatial and legal structures are

also different (Jenkins, 2000). This is the reason why

the value of real estate property is always associated

with location, location and location (Hui, 2007).

Based on the theory and conceptual framework

that has been described, the hypothesis that can be

proposed in this research is the location, facilities,

design, environment, and cluster characteristics have

a significant effect on the value of residential

property of J City.

3 METHOD

The population in this research is the resident of J

city residence in three different types with 692

families. The sampling method uses proportional

sampling method with number of respondents is 87.

Data collection methods conducted in two ways,

namely questionnaires and observations.

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1348

This research uses validity and reliability test to

test the questionnaire. Furthermore, SPSS and

STATCAL were used to perform classical

assumption test and linear regression (Gio, 2015).

4 RESULT AND DISCUSSION

4.1 Brief Overview of J City Residence

J City residence has an area of 23 ha with three

different clusters, namely J Crown, J Elite, and J

Metropolis. The facilities provided by this residence

include shopping centers, ATM centers, and banks.

The construction of this residence not only provides

complete facilities but also provides additional

infrastructure that is access between Karya Wisata

street and Pintu Air street.

Based on the interview results with management

of J City residence, development of residence and

unit house are still continuing. The management side

plans to add additional cluster type and shop-house

development in the prepared area but when the

researcher conducts this research, the process of

developing new cluster and shop has not been

realized so that the research is only limited to the

type of cluster that has been built.

4.2 Validity and Reliability Test

4.2.1 Validity Test

The questionnaire has 43 questions. Based on

validity test, all questions are valid with correlation

score > 0.361 (critical value). Table 2 is displayed

validity test.

Table 2: Validity test

Variable Question Correlati

on score

Desic

ion

Location

Near the main

access

0.836

Valid

Near school 0.833 Valid

Near office 0.836 Valid

Posisition 0.834 Valid

Being on the main

roa

0.868 Valid

ease of

trans

ortation

0.849 Valid

Facilities

Doctor / hospital

0.793 Valid

Recreation place

0.757 Valid

Sport facilities

0.804 Valid

Shopping center

0.717 Valid

ATM center

0.751 Valid

House of worship

0.827 Valid

Good road

0.810 Valid

Street lights

0.788 Valid

Design

Facade 0.780 Valid

Interiorarrangem

0.697 Valid

Inner layout 0.717 Valid

Window for

natural lighting

0.628 Valid

Openings for air

circulation

0.649 Valid

House structure 0.810 Valid

Soil absorbs water 0.629 Valid

Wall quality 0.745 Valid

wall paint quality 0.775 Valid

Ceramic / marble

floor

0.732 Valid

Roof quality 0.722 Valid

Door quality 0.751 Valid

Window quality 0.778 Valid

Installation of

lights

0.804 Valid

Neighbou

rhood

Low pollution 0.748 Valid

Low noise level 0.766 Valid

Safe from crime 0.735 Valid

Safe from

floodin

0.729 Valid

Tribal diversit

0.786 Valid

Close to family /

collea

ues

0.746 Valid

Side of the road

for parkin

0.793 Valid

Cluster

characteri

stic

One gate system 0.772 Valid

Special security 0.810 Valid

Park 0.701 Valid

Peddler 0.730 Valid

Waste maintenance 0.807 Valid

Electricitymainten

ance

0.797 Valid

Clean water

maintenance

0.739

Valid

Drainage

maintenance

0.812 Valid

4.2.2 Reliability Test

The next test is reliability test using Cronbach

Alpha. The expected Cronbach Alpha is greater than

0.6 (Gio, 2013). Table 3 is displayed reliability test.

Analysis of Factors Affecting Property Value at Residence with Cluster Concept: Case Study - J City Residence

1349

Table 3: Reliability test

Variable Cronbach

Alpha

Result

Location 0.919 Reliable

Facility 0.909 Reliable

Design 0.933 Reliable

Neighbourhood 0.887 Reliable

Cluster

characteristic

0.903 Reliable

4.3 Classical Assumption Test

4.3.1 Residual Normality Test

The assumption test of normality uses Kolmogorov-

Smirnov test. Based on the result of normality test,

the value of p-value (p) is 0.326 which is greater

than significance level 0.05, then normality

assumption of residuals is satisfied.

4.3.2 Heteroscedasticity Test

Heteroscedasticity test uses Glejser test. Based on

Glejser test in Table 4, all values of Sig Glejser<

0,05.

Table 4: Heteroscedasticity Test with Glejser Test

Coefficients

Model t Sig.

1 (Constant) -10.550 .000

Location 2.281 .025

Facilit

2.344 .022

Desi

n 3.215 .002

Neighbourhoo

3.119 .003

Cluster characteristic 3.517 .001

a. Dependent Variable: Y

4.3.3 Multicollinearity Test

Multicollinearity test uses variance inflation factor

(VIF). The expected VIF is less than 10 indicating

there is no multicollinearity symptom. Table 5 is

displayed multicollinearity test uses VIF. Based on

the multicollinearity test result in Table 5, VIF for

each independent variable are less than 10 indicating

there are no multicollinearity symptom.

Table 5: Multicolinearity Test with VIF

Variable VIF Conclusion

Location 2.072

There is no

multicollinearity

Facility 2.301

There is no

multicollinearity

Design 1.742

There is no

multicollinearity

Neighbourhood 1.464

There is no

multicollinearity

Cluster

characteristic

1.669

There is no

multicollinearity

4.4 Hypothesis Testing

4.4.1 Multiple Linear Regression

In this research, multiple linear regression is used to

test the hypothesis. This method is used to analysis

the magnitude of influence between independent

variable of location (X₁), facility (X₂), design (X₃),

environment (X₄), and cluster characteristic (X₅) to

dependent variable (Y) that is property value. Table

6 is displayed the result.

Table 6: Multiple Linear Regression Result

Variabel Sig. Result

Constant 0.000 Significant

Location 0.025 Significant

Facilit

0.022 Significant

Desi

n 0.002 Si

nificant

Nei

hbourhoo

0.003 Si

nificant

Cluster

characteristic

0.001 Significant

R Square

Adjusted R square

hitung

Sign. F

= 0.860

= 0.739

= 0.723

=45.975

=0.000

=0.05

1) Simultaneously Test (F test)

Based on simultaneously test with F test (Table 6),

the value of F statistic is 45,975, with p-value 0,000

< significance level 0,05. It means that location (X₁),

facility (X₂), design (X₃), environment (X₄) and

cluster characteristic (X₅) simultaneously have

significant effect to property value. The following is

multiple linear regression equation.

Y = -4049764189.88 + 34218078.92 X1 +

38971600.93 X2 + 23595663.95 X3 + 40064597.73

X4+ 37020304.41 X5

2) Partial Test (t Test)

Based on partial test with t test in Table 6:

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

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1. H₁: The location variable has significant effect to

property value, with p-value 0,025 < 0,05. The first

hypothesis is received.

2. H₂ : The facility variable has significant effect to

property value, with p-value 0,022 < 0,05. The

second hypothesis is received.

3. H₃ : The design variable has significant effect to

property value, with p-value 0,002 < 0,05. The

third hypothesis is received.

4.H₄: The neighbourhood variable has significant

effect to property value, with p-value 0,003

<0,05. The fouth hypothesis is received.

5. H₅ : The cluster characteristic variable has

significant effect to property value, with p-

value 0,001 <0,05. The fifth hypothesis is

received.

3) Coefficient of Determination

The value of coefficient determination is 0,739.

It means that location, facility, design,

environment and cluster characteristic can

affect property value as 73,9%, with 26,1% for

other factors.

5 CONCLUSIONS

Property value of J City Residence is affected by

location, facilities, design, neighbourhood, and

cluster characteristic based on the research result

thatsimultaneously and partially, the five variables

have a positive and significant effect on the property

value. Thus, respondent take notice for every aspect

of residential. The better the residential is managed

will causethe property value increased.

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