Internati
o
nal
Journal of Ele
c
trical
and Computer
Engineering
(IJE
CE)
Vol
.
4
,
No
. 5, Oct
o
ber
2
0
1
4
,
pp
. 66
8~
67
8
I
S
SN
: 208
8-8
7
0
8
6
68
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJECE
Adjusting ICT Capacity Planning
by Minimizing Cyber Crime
Effects in Urban
Area: A Sy
stem Dynamics Approach
Feldians
yah B
i
n Bakri
Nasu
ti
o
n
,
No
r Er
ne
Na
zir
a
Ba
zin
Computer Scien
ce Dep
a
rtment,
Un
iversiti Tekno
logi Ma
lay
s
ia (U
TM), Johor
B
a
hr
u, Malay
s
ia
Article Info
A
B
STRAC
T
Article histo
r
y:
Received J
u
l
2, 2014
Rev
i
sed
Sep
18
, 20
14
Accepted
Sep 29, 2014
In
doing the
ICT
capacit
y
p
l
anni
ng, m
o
st organizations or institut
i
ons ignore
unconsciously
other condition
s
excep
t
st
atistical data of
b
a
ndwidth or
utili
zat
ion of
IC
T products. On
this oc
casion, th
e ICT
cap
acit
y
planning
is
anal
yz
ed b
y
us
ing s
y
s
t
em
d
y
n
a
m
i
cs
with con
s
idering s
o
m
e
factors
or
components which ar
e
combinations be
tween technical
a
nd non
technical
things such as:
business, education,
ICT
infrastr
u
cture, ICT usag
e and
cy
ber
crime. Simulatio
n of interrelatio
n
ship
between the components is conducted
to understand
th
e behav
i
or of
th
e s
y
stem
. S
y
stem d
y
namics giv
e
s us an input
about corr
ection
of the statistical data
b
y
minimizing cy
ber
crime effects. In
this paper
,
it
is also introdu
ced
th
e s
y
stem breakdown structur
e (SBS), a
techn
i
que
to b
r
eakdown a b
i
g and complex
s
y
stem into
smaller
and
manageable co
mponents. The objective
of this SB
S is to
make s
y
stem
d
y
namics more
expandab
l
e in h
i
erar
ch
y w
a
y in
a
n
al
yz
in
g
a
s
y
s
t
e
m
.
Keyword:
C
a
paci
t
y
pl
an
n
i
ng
ICT
Syste
m
breakdown st
ruct
ure
Sy
st
em
dy
nam
i
cs
Copyright ©
201
4 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
Feld
ian
s
yah
Bin
Bak
r
i
Nasu
tio
n,
C
o
m
put
er Sci
e
nce
Depa
rt
m
e
nt
, Facul
t
y
o
f
C
o
m
put
i
ng,
Un
i
v
ersiti Tekn
o
l
o
g
i
Malaysia,
Sk
udai
,
J
o
h
o
r
B
a
hr
u, M
a
l
a
y
s
i
a
.
Em
a
il: feld
ian
s
yah
2
@liv
e.u
t
m
.
my
1.
INTRODUCTION
ICT h
a
s
b
e
come a
m
a
j
o
r req
u
i
rem
e
n
t
in
u
r
b
a
n
areas
wheth
e
r to
d
o
some fu
n
activ
ities, su
ch
as in
o
n
lin
e
g
a
m
e
s, so
cial m
e
d
i
a,
ch
attin
g
and
co
mm
u
n
i
catio
n
o
r
t
o
do
m
o
re seriou
s
o
r
wo
rk
related
activ
ities,
su
ch
as in
b
u
sin
e
ss ERP ap
p
lication
,
co
llab
o
ratio
n
and co
mm
u
n
i
cati
o
n
wh
ich
co
nfid
en
tiality, in
teg
r
ity
,
av
ailab
ility (CIA)
o
f
the d
a
ta
are m
o
re i
m
p
o
r
tan
t
[1
], [2
]. App
licatio
n
such
as em
ail
sys
t
e
m
, n
e
ws and
so
cial
media is a nece
ssity for urban
people
[3].
Bu
sin
e
ss withou
t ICT will lo
se its ab
ility to
win
co
m
p
etitio
n
[4
]. Bu
si
n
e
ss secto
r
is
d
e
p
e
n
d
e
n
t
a lo
t
on
IC
T beca
us
e i
t
adds m
o
re val
u
es a
nd l
e
a
d
s t
o
fi
na
nc
i
a
l
bene
fi
t
s
. N
o
wa
day
s
, IC
T
has
evol
ved i
n
t
o
a
t
ool
n
o
t
on
ly to
add
valu
es t
o
the bu
sin
e
ss
activ
ities, bu
t also to
g
e
n
e
rate new bu
si
n
e
ss activ
ities to
co
ntrib
u
t
e
m
o
re reve
nue
s
to the c
o
m
p
an
y
[5]
.
A si
g
n
i
f
i
cant
gr
owt
h
of
b
u
si
ness
ge
ner
a
t
e
s a dem
a
nd f
o
r a bet
t
e
r IC
T i
n
f
r
ast
r
uct
u
re. IC
T
i
n
fra
st
ruct
ure c
onsi
s
t
s
o
f
net
w
or
k, st
o
r
a
g
e, se
rve
r
, an
d da
ta
cen
ter in
frastructu
res [6
], [7
], [8
].
W
ithou
t a g
ood
ICT in
frastru
c
tu
re, so
m
e
p
e
o
p
l
e are
relu
ctan
t to
u
s
e the e-bu
sin
e
ss ap
p
lication
in
th
e in
tern
et. A p
oor
per
f
o
r
m
a
nce o
f
c
o
n
n
ect
i
o
n i
s
a m
a
jor
rea
s
on
f
o
r t
h
em
n
o
t
t
o
u
s
e
IC
T
i
n
s
o
m
e
regi
ons
.
To
ha
ve
a g
o
od
p
e
rform
a
n
ce, at least
th
e ICT in
frastru
ct
u
r
e
need
s to
m
a
in
tai
n
50
% av
ailab
i
lity
o
f
its cap
acity fo
r sp
ik
e
usag
e.
It becom
e
s the buffe
r for any unus
ual activities. Som
e
a
pplications are
tim
e
sensitive, and
need
very fast
resp
o
n
se.
Thi
s
bu
ffe
r i
s
a
b
l
e
t
o
ove
rc
om
e t
hose
pr
o
b
l
e
m
s
.
Th
e
ICT tech
no
log
y
ev
o
l
v
e
s
d
y
n
a
m
i
call
y
to
b
e
co
m
e
m
o
re
co
m
p
lex
and
need
s m
o
re sp
ecial sk
ill sets
[9]
,
[1
0]
.
It cre
a
tes m
o
re dem
a
nd
s in e
d
ucation
secto
r
to sup
port th
e
requ
i
r
em
en
ts. Unfo
rtu
n
a
tely, edu
c
ation
secto
r
is no
t fast eno
ugh
to follo
w th
e gro
w
t
h
o
f
bu
sin
e
ss secto
r
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE Vo
l. 4
,
N
o
. 5
,
O
c
tob
e
r
20
14
:
668
–
6
78
66
9
Edu
catio
n
po
sitiv
ely co
n
t
ributes cyb
e
r crime awaren
e
ss to p
e
op
le [1
1
]
,
[1
2
]
. Th
is awaren
ess is t
o
o
v
e
rco
m
e c
y
b
e
r crim
e effects, th
e n
e
g
a
tiv
e i
m
p
acts o
f
IC
T g
r
o
w
t
h
. Some p
e
o
p
l
e are still relu
ctan
t
to
u
s
e
ICT, especially for busi
ness transactions, bec
a
use of th
e cyber crim
e. The a
p
propri
ate education increase
s
the
p
e
op
le’s awaren
ess to
do
th
e
righ
t way o
f
bu
sin
e
ss tran
sactio
n
s
v
i
a in
ternet. Th
e righ
t ed
u
cation
wit
h
eth
i
cs
an
d
laws in
IC
T m
a
k
e
s p
e
o
p
l
e
m
o
re respo
n
sib
l
e to
th
eir activ
ities. It redu
ces th
e cy
b
e
r
crim
e
in
th
e society.
In th
e end
,
t
h
is d
e
creases t
h
e i
lleg
a
l activ
ities and
th
e resistan
ce to use ICT.
These positive
and negative
com
pone
nts
influe
nce
how people use
ICT.
Th
e
phe
nom
enon
of ICT
usa
g
e
occu
rs
a
s
t
h
e
u
p
a
n
d
d
o
w
n
p
r
oce
ss, i
n
acc
or
da
nce
wi
t
h
t
h
e c
o
m
pone
nt
s t
h
at
s
u
p
p
o
r
t
a
n
d
hi
n
d
e
r
i
t
.
T
o
g
e
t th
e op
tim
a
l
resu
lt, it d
e
pen
d
s
o
n
h
o
w
g
ood
we are t
o
m
i
n
i
m
i
ze th
e n
e
g
a
tiv
e im
p
act and
m
a
x
i
mize th
e
p
o
s
itiv
e im
p
a
c
t
. In our case,
th
e adju
stm
e
n
t
will b
e
do
n
e
b
y
m
i
n
i
mizin
g
th
e cyb
e
r crime effects to
ach
i
ev
e
opt
i
m
al
out
co
m
e
of
IC
T
In
fr
ast
r
uct
u
re.
At th
e ti
m
e
th
at th
e d
e
m
a
n
d
o
f
ICT in
creases co
n
tinuo
usly, it
m
a
k
e
s t
h
e ICT to
b
e
co
m
e
m
o
re
critical. ICT inevitably bec
o
mes a necessit
y
, no longer ju
st
a
t
ool
.
W
i
t
h
o
u
t
IC
T,
t
h
e un
de
rt
ake
n
pr
o
cess
i
s
di
sr
upt
e
d
.
Di
sr
upt
i
o
n m
a
y
be cause
d by
t
h
e
equi
pm
ent
fai
l
ure
or t
h
e i
n
c
o
m
p
et
ence i
n
pl
anni
ng a
n
d p
r
e
d
i
c
t
i
n
g
t
h
e fut
u
re
usa
g
e. In t
h
i
s
pape
r
,
i
t
i
s
di
scussed
m
o
re ab
out
IC
T usag
e i
n
t
h
e
fut
u
re.
H
o
w IC
T capaci
t
y
pl
anni
ng
is ab
le to suppo
r
t
t
h
e
g
r
o
w
t
h
o
f
econo
m
i
c a
n
d bu
si
n
e
ss
[
1
3
]
.
ICT cap
acity plan
n
i
ng
is n
e
ed
ed
t
o
m
a
in
tai
n
su
stainab
ility an
d
con
tinu
a
tio
n
of bu
sin
e
ss. By u
s
ing
ri
g
h
t
m
e
t
hodol
ogy
,
a
go
o
d
I
C
T In
fr
ast
r
uct
u
re
can
p
r
o
v
i
d
e
peo
p
l
e
wi
t
h
m
o
re rel
i
a
bl
e ser
v
i
ces. B
u
si
ness
secto
r
, edu
catio
n
sector
and
oth
e
rs will
co
n
t
i
n
u
e
t
o
g
r
o
w
positiv
ely. ICT In
frastru
c
ture at least will n
o
t
h
i
nd
er
t
h
e gr
o
w
t
h
o
f
t
h
ese sect
ors.
On t
h
e co
nt
r
a
ry
, i
f
t
h
e pr
o
cess of IC
T c
a
paci
t
y
pl
anni
ng i
s
n
o
t
co
n
duct
e
d
p
r
op
erly,
b
u
siness opp
ortun
ities will b
e
lo
st
[1
3
]
, [1
4
]
.
Wh
at
will h
a
pp
en if
ICT infrastru
c
tu
re is
n
o
t
ab
le to fo
llo
w t
h
e
g
r
o
w
t
h
o
f
bu
sin
e
ss
?
Defi
n
itely,
p
e
op
le
w
ill lo
se op
portun
ities, esp
ecially in
bu
sin
e
ss secto
r
.
Th
e govern
m
e
n
t
w
ill lo
se
o
ppo
rt
u
n
i
t
i
es to
in
crease co
m
p
etitiv
en
ess an
d also
p
r
o
s
p
e
rit
y
o
f
th
e
n
a
tion
.
In
t
h
is
p
e
rsp
e
ctiv
e, ev
en
i
f
the ICT infrastru
c
ture is
p
r
ov
id
ed b
y
p
r
i
v
ate co
m
p
an
y,
g
o
v
e
rn
m
e
n
t
is
still resp
on
sible to
in
fl
u
e
n
c
e th
em
th
ro
ug
h
supp
ortiv
e regu
latio
ns.
Th
e ap
pro
p
riate p
l
an
o
n
this IC
T
Infrast
ru
ct
u
r
e i
n
creases
n
a
tio
nal o
r
reg
i
on
al co
m
p
etitiv
e ad
van
t
ag
e
[1
5
]
.
Man
y
cap
acity p
l
ann
i
ng
pro
c
esses are
d
o
n
e
in
sta
tic way, b
y
assu
m
i
n
g
th
at cu
rren
t con
d
ition
s
will
not
be cha
nge
d. C
a
paci
t
y
pl
anni
ng
by
anal
y
z
i
ng t
h
e st
at
i
s
t
i
cal
dat
a
of p
r
o
d
u
ct
i
on c
o
n
d
u
ct
ed i
n
t
h
e
pa
st
and
pre
d
i
c
t
i
ng
fut
u
re dem
a
nd i
s
not
e
n
o
u
g
h
.
The l
e
vel
o
f
de
m
a
nd i
s
not
o
n
l
y
m
easured
by
t
h
e pr
o
duct
i
on o
f
statistical data, but also be
ha
vior of the exist
i
ng syst
em
. Co
m
ponents of the system
affect and infl
ue
nce each
ot
he
r. It
i
s
dy
n
a
m
i
c, not
st
at
i
c
. A
d
j
u
st
m
e
nt
or i
n
t
e
rve
n
t
i
o
n
i
n
cert
a
i
n
c
o
m
ponent
s ca
n
be d
o
n
e t
o
ac
h
i
eve a
bet
t
e
r out
c
o
m
e
[
16]
.
In t
h
e
sy
st
em
dy
nam
i
cs, com
ponent
s w
e
r
e
st
udi
e
d
dy
n
a
m
i
cal
ly
t
o
obt
ai
n o
p
t
i
m
al
out
put
a
n
d
beha
vi
o
r
of
sy
st
em
by
sim
u
l
a
t
i
ng
few
di
f
f
e
r
ent
sce
n
a
r
i
o
s.
Thi
s
i
s
e
x
pl
ai
n
e
d
wel
l
by
Jay
Fo
rrest
e
r
[
1
7]
,
[1
8]
,
[1
9]
, Jo
h
n
St
e
r
m
a
n [16]
, Pet
e
r Sen
g
e [
2
0]
and
ot
he
r ex
p
e
rt
s i
n
sy
st
em
dy
nam
i
cs. C
a
paci
t
y
pl
anni
n
g
wi
t
h
syste
m
d
y
n
a
m
i
cs ap
pro
a
ch
is to
o
p
tim
ize
th
e cap
acity
pl
ann
i
ng p
r
o
cess an
d t
o
i
d
ent
i
f
y
t
h
e dy
nam
i
c beh
a
vi
o
r
as th
e co
rrection
o
f
th
e statistical d
a
ta.
2.
CYBE
R
CRI
ME EFFE
CTS in I
C
T
and
ECONO
M
IC GRO
W
TH
CORRELATION
It h
a
s b
e
co
m
e
ev
id
en
t to
u
s
th
at ICT and
eco
no
m
i
c g
r
o
w
t
h
h
a
v
e
a po
sitiv
e co
rrelation
[4], [2
1
]
, [22
]
.
A
goo
d
I
C
T i
n
fr
astru
c
tur
e
pr
ov
id
es economic o
p
p
o
r
t
u
n
i
t
i
es f
o
r
th
e
u
s
er
s to
ob
tain
inf
o
r
m
at
io
n
,
bu
sin
e
ss
o
ppo
rt
u
n
ities an
d o
t
h
e
rs. B
o
th
o
f
th
em
h
a
ve m
u
tu
ally rein
fo
rci
n
g relatio
n
s
h
i
p
[16
]
. If nu
m
b
er of
IC
T u
s
ers
in
crease, th
ey
will in
crease t
h
e ICT
u
s
ag
e
an
d
sub
s
e
q
u
e
ntly in
crease eco
no
m
i
c g
r
owth
.
And
v
i
ce versa, i
f
eco
no
m
i
c g
r
owth
i
n
creases,
it will in
crease
th
e u
tilizatio
n
o
f
ICT and
th
e
n
u
m
b
e
r
o
f
ICT u
s
ers.
It is th
e k
e
y o
f
su
ccess to
u
t
ilize ICT o
p
timall
y
fo
r econo
m
i
c
g
r
owth. If so, th
en
IC
T will g
r
ow
alo
n
g
with
econ
o
m
ic d
e
v
e
lopmen
t, b
u
t
k
e
ep in
m
i
n
d
ab
ou
t
th
e facto
r
s i
n
h
i
b
itin
g
it. In
creased
u
tilizati
o
n
o
f
IC
T i
s
not
bi
g en
o
u
g
h
t
o
p
r
o
v
i
d
e a
d
eq
uat
e
bene
fi
t
s
i
f
y
ou
ha
ve bi
g
n
e
gat
i
v
e ef
fect
s
any
w
ay
. C
o
n
c
ret
e
exam
pl
e i
s
ut
ili
zat
i
on of IC
T
i
n
t
h
e busi
n
ess
worl
d, s
u
ch as
e-comm
erce,
whic
h tr
ansacti
ons a
r
e m
a
de online
usi
n
g cr
edi
t
ca
rd
. It
i
s
a c
o
m
m
on t
h
i
ng i
n
d
e
vel
o
ped
co
u
n
t
r
i
e
s w
h
i
c
h est
a
bl
i
s
he
d l
a
ws a
nd
re
gul
at
i
o
ns
are i
n
place. B
u
t in
s
o
m
e
count
ries,
it is still a horri
ble thin
g
beca
use of the
ris
k
of e
x
isting cy
be
r crim
e.
Bad
p
e
rson
is
m
o
tiv
ated
to
d
o
illeg
a
l activ
ities
o
r
cyb
e
r crim
e if
th
e p
e
rform
a
n
ce o
f
ICT
in
frastru
ct
u
r
e
an
d th
e
u
tilizatio
n
of ICT u
s
ag
e in
crease. On
th
e con
t
rary, cyb
e
r crim
e i
m
p
acts n
e
g
a
tively to
IC
T
usage
an
d
sub
s
eq
ue
nt
l
y
t
o
IC
T i
n
frast
ru
ct
ure.
It
i
s
cal
l
e
d as
bal
a
nci
n
g l
o
o
p
rel
a
t
i
o
n
s
hi
p
[
16]
.
Th
e in
ab
ility t
o
prov
id
e a
b
e
t
t
er ICT in
frast
r
u
c
t
u
re to
sup
p
o
r
t ICT
u
s
ag
e
is th
e
m
a
in
n
e
g
a
tiv
e th
ing
whi
c
h c
oul
d i
n
habi
t
t
h
e ec
on
om
i
c
gro
w
t
h
.
I
T
U
(I
nf
o
r
m
a
tion
Tec
h
n
o
l
o
gy
U
n
i
o
n)
has
a
bi
g c
o
ncer
n
o
n
t
h
i
s
,
an
d th
ey co
m
e
with
t
h
e i
n
d
i
cato
r t
h
at th
ey called
it as
Dig
i
tal Access
Index
(DAI), and
n
o
w t
r
an
sfo
r
med
int
o
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
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8-8
7
0
8
Ad
ju
sting
ICT
Ca
pa
city Plann
ing
b
y
Mi
n
i
mi
zin
g
Cyb
e
r Crime Effects in Urb
a
n
Area
: …
(
F
el
di
ansy
a
h B
B
N
)
67
0
IDI (ICT
Deve
lopm
ent Inde
x) [23]. If
the negative effects are overc
o
m
e
,
it will acce
lerate the absorpti
on a
nd
u
tilizatio
n
of ICT.
3.
SYSTE
M
DY
NA
MI
C APP
R
O
A
C
H
Sy
st
em
dy
nam
i
cs whi
c
h
was
fi
rst
i
n
t
r
o
duce
d
by
Jay
F
o
r
r
e
s
t
e
r [
17]
has
b
een
gr
owi
n
g
a
n
d
p
r
o
v
i
d
i
n
g
a new
pers
pect
i
v
e fo
r anal
y
z
i
ng
phe
n
o
m
e
na, suc
h
as i
n
econom
i
cal, political, social
and cultural aspect
s. On
th
is o
ccasion
,
au
tho
r
will atte
m
p
t to
u
s
e t
h
is app
r
o
a
ch
t
o
i
d
en
tify t
h
e co
rrectio
n on statistically ICT cap
acity
pl
an
ni
n
g
aft
e
r
m
i
nim
i
zi
ng co
m
ponent
s o
f
c
y
ber cri
m
e effect
s. The st
at
i
s
t
i
cal
l
y
dat
a
of t
h
e IC
T
usa
g
e
wi
t
h
o
u
t
sy
st
em
dy
nam
i
cs ap
pr
oac
h
ca
n
be
used
as t
h
e basel
i
n
e
f
o
r t
h
e m
odel
.
B
y
s
i
m
u
l
a
t
i
ng i
n
t
e
r
r
el
at
i
ons
hi
p
be
t
w
ee
n
com
pone
nt
s o
n
b
u
si
ne
ss, I
C
T i
n
frast
ruct
ure
,
IC
T u
s
ag
e, ed
ucat
i
on a
nd cy
ber cri
m
e, t
h
e pa
ram
e
t
e
rs o
f
com
pone
nt
s ar
e i
d
ent
i
f
i
e
d.
It is called
as t
h
e id
eal m
o
d
e
l, if it is ab
le to
si
m
u
late th
e real syste
m
. Th
e
resu
lt of id
eal m
o
d
e
l is th
e
sam
e
as th
e resu
lt th
at
will be h
a
p
p
en
ed
i
n
th
e real
system
. Fo
r so
m
e
cases, it is
v
e
ry
h
a
rd to id
en
tify th
e
cor
r
ect
com
p
o
n
ent
s
a
nd
para
m
e
t
e
rs t
o
m
a
tch t
h
e real
sy
st
em
. In p
r
act
i
ce, i
t
i
s
sugge
st
ed t
o
f
o
cu
s on t
h
e
certain a
r
ea
we
nee
d
to study
[16].
In
o
u
r case
,
t
h
e m
odel
i
s
repr
esent
e
d
by
fi
ve
bi
g c
o
m
pone
n
t
s. The i
n
t
e
rrel
a
t
i
on
bet
w
ee
n
com
pone
nt
s
and the
beha
vi
or of each c
o
m
ponent (see
Figure 1) are
determ
ined. The ne
xt step is to
m
i
nim
i
ze
the cyber
crim
e effects to
find the
corre
ction.
3.
1.
In
tegr
a
t
i
n
g Sys
t
em C
o
mpone
n
ts
It is
h
a
rd
t
o
find
a m
o
d
e
l with h
i
gh sim
i
larit
y
to
th
e real
syste
m
. In th
is
research,
ICT sy
ste
m
is o
n
l
y
foc
u
s t
o
t
h
e fi
ve com
pone
nt
s
whi
c
h a
r
e b
u
s
i
ness, ed
ucat
i
o
n, IC
T i
n
frast
r
u
ct
u
r
e, IC
T u
s
age an
d cy
ber
cri
m
e.
Business
and e
ducation c
o
m
pone
nt creat
e t
h
e reinforcing
or positive loops
toget
h
er
with ICT
usage
and ICT
i
n
fra
st
ruct
ure
com
pone
nt
s [
1
6]
. O
n
t
h
e c
o
n
t
rary
, cy
be
r c
r
i
m
e com
ponent
i
s
a b
a
r
r
i
e
r
fo
r IC
T
I
n
f
r
ast
r
u
c
t
u
re
and ICT
usa
g
e
com
pone
nt to continue
growing. Of c
o
urse, it will also inhi
bit indirectly the
devel
opm
ent
of
ot
he
rs s
u
c
h
as
busi
n
ess
an
d e
ducat
i
o
n c
o
m
pone
nt
s.
Furt
herm
ore, t
h
e com
pone
nt
s of t
h
e sy
st
em
are st
il
l
bi
g eno
u
g
h
f
o
r a
n
al
y
s
i
s
. It
i
s
m
u
ch easi
e
r i
f
th
ese co
m
p
onen
t
s are
broken
d
o
wn
in
to sm
a
ller co
mp
on
en
ts.
Au
t
h
o
r
calls th
is t
ech
n
i
q
u
e
as
Syste
m
Breakdown St
ruct
ure
(SBS). The
goa
l
o
f
th
is SBS is to
find
t
h
e
o
p
tim
ized
b
u
s
in
ess ou
tco
m
e
.
Th
e
com
pone
nt
s wi
l
l
be
m
a
rked
b
y
num
beri
n
g
i
n
t
h
e Sy
st
em
Dy
nam
i
cs Di
agram
Vi
ew (S
DD
V)
. T
h
i
s
n
u
m
beri
ng
lo
ok
s sim
p
le bu
t it will b
e
u
s
efu
l
wh
en an
al
yzin
g
a co
m
p
lex
system
s.
Fi
gu
re
1.
Sy
st
em
Dy
nam
i
cs Di
ag
ram
View (before
the
brea
kdown)
Aft
e
r
ex
pa
ndi
ng
Fi
g
u
r
e
1,
b
y
usi
n
g sy
st
e
m
breakd
o
w
n
st
ruct
u
r
e,
i
t
be
com
e
s Fi
gure
2.
IC
T
usa
g
e
(3.1) stim
u
l
ate
s
so
m
e
n
e
w bu
sin
e
ss
o
ppo
rt
u
n
ities. Th
e h
i
g
h
e
r t
h
e IC
T
u
s
ag
e (3
.1) is u
tilized
, t
h
e
h
i
gh
er
b
u
s
i
n
ess activ
i
t
y (1
.2
) i
n
creases. Lik
e
wise,
ICT ed
u
c
atio
n
(4
.1
)
p
r
od
u
c
es sk
illed
m
a
n
p
o
wer to
su
stain
g
r
o
w
t
h
o
f
bu
sin
e
ss act
iv
ities (1
.2).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
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088
-87
08
I
J
ECE Vo
l. 4
,
N
o
. 5
,
O
c
tob
e
r
20
14
:
668
–
6
78
67
1
Fi
gu
re
2.
Ex
pa
nde
d
Sy
st
em
Dy
nam
i
cs Di
agr
a
m
Vi
ew
The business
activity
(1.2) doe
s not
al
wa
ys
im
p
act pos
itively to othe
r c
o
m
pone
nts. It im
pacts
negatively by increasi
ng
business cybe
r cri
m
e (5.1). E
v
en
m
o
re if it is sup
p
o
rte
d
by
g
o
o
d
ICT in
fra
s
t
ructu
r
e
(2.1), th
e
b
a
d
p
e
rson
will u
s
e it easil
y wit
h
wrong
in
ten
t
io
n
.
An
o
t
h
e
r
neg
a
tiv
e im
p
act
, so
cial and
cultu
ral
cyber crim
e (5.5) continues i
n
creasi
ng
if IC
T usage
(3.1) increase
s
. The
ba
d
pers
o
n
co
ul
d p
u
t
som
e
int
e
r
n
et
co
n
t
en
ts wh
ich i
m
p
act n
e
g
a
tiv
ely to
th
e so
ciety. Un
lik
e
bu
si
ness cy
be
r cr
im
e, i
t
does n
o
t
im
pact
di
rect
l
y
on
fi
na
nci
a
l
aspec
t
s. Im
pro
v
em
ent
s
i
n
t
h
e
fi
el
d
of
cy
ber
law /
regu
latio
n and
en
fo
rcem
ent (5.3); and cy
ber
crim
e
aware
n
ess
(4.3) are
ve
ry
helpful
in
figh
t ag
ain
s
t cyb
e
r crime.
In this
researc
h
, fe
w sce
n
ari
o
s are c
r
eated
with
an
d
wi
t
h
out
a
d
j
u
st
m
e
nt
of ce
rt
ai
n pa
r
a
m
e
t
e
rs. B
y
redu
cing
th
e
delay o
f
ICT ed
u
cation
ad
op
t
i
o
n
(4
.2)
and
th
e d
e
lay of law adop
tio
n
(5.4
), it will
min
i
m
i
z
e
cyb
e
r crim
e effects. Th
e result will in
fo
rm
u
s
th
e co
rrec
tio
n
on
th
e statistically
d
a
ta o
f
ICT cap
acity plan
n
i
ng
pr
ocess
.
It
i
s
t
o
su
p
p
o
r
t
m
o
re dem
a
nds o
f
t
h
e IC
T
us
ag
e in
th
e fu
ture if
th
e in
terv
en
tion
,
m
i
n
i
mizin
g
cyb
e
r
crim
e effects, is im
ple
m
ented.
3.
2.
Runnin
g
the
Sim
u
lation and
An
alysi
s
Fro
m
th
e r
e
su
lts of
the
p
r
ev
iou
s
secti
o
n, conf
igu
r
ing
si
m
u
latio
n
so
ftw
a
r
e
is
condu
cted
. Th
e
soft
ware is
Ve
nsim
PLE fo
r
W
i
n
d
o
w
s
v
6
.
2
fr
om
Vent
ana
Syste
m
, Inc. B
a
sed
on
the SDDV
(see
Figure 1), a
Struct
ure
d
View Ta
ble (SVT) is created.
Tabl
e 1. St
ru
ct
ure
Vi
e
w
Ta
bl
e
(S
VT
) of Fi
g
u
re
1
No. Description
Equation
Type
Value
Unit
1.
Business
(3
) +
(4
)
2
.
ICT In
f
r
astru
c
tu
re
(1
)
–
(5
)
3
.
ICT Usag
e
(1
) +
(2
)
4.
I
C
T
E
ducation
(
3
)
5
.
Cyb
e
r Cr
i
m
e
(3
) +
(4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
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:
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8-8
7
0
8
Ad
ju
sting
ICT
Ca
pa
city Plann
ing
b
y
Mi
n
i
mi
zin
g
Cyb
e
r Crime Effects in Urb
a
n
Area
: …
(
F
el
di
ansy
a
h B
B
N
)
67
2
Each
item
in
descrip
tion
co
lum
n
is actu
a
lly
th
e co
m
p
on
en
t of th
e system
.
Th
e nu
m
b
er
of th
e ite
m
is
t
h
e sam
e
as t
h
e com
ponent
n
u
m
b
er on t
h
e
SD
DV (
s
ee Fi
gu
re 1
)
. Th
e n
u
m
b
er i
s
used t
o
creat
e equat
i
on
o
r
al
go
ri
t
h
m
whi
c
h e
xpl
ai
n
s
t
h
e
r
e
l
a
t
i
onshi
p
bet
w
een
com
p
o
n
e
n
t
s
. S
u
c
h
as:
Business
=
ICT Usa
g
e +
ICT
Ed
ucatio
n
(1
)
If y
o
u
see
t
h
e
SD
D
V
(see
Fi
gu
re
1)
, t
h
e
“B
usi
n
ess” c
o
m
pone
nt
rece
i
v
e t
w
o i
n
p
u
t
s
fr
om
“IC
T
Usag
e” an
d “I
C
T
Educat
i
o
n”
com
ponent
. “B
usi
n
ess” i
s
re
prese
n
t
e
d
by
n
u
m
b
er (1
), “IC
T
usage” i
s
(
3
) an
d
“ICT ed
u
cation
”
is
(4). And
t
o
m
a
k
e
it easy an
d sim
p
le, it can
b
e
rewritten as:
(1
) =
(
3
) +
(
4
)
(2
)
Thi
s
i
s
sh
ow
n
i
n
eq
uat
i
on c
o
l
u
m
n
i
n
t
a
bl
e abo
v
e as “(
3
)
+ (4)
”
. T
h
e b
u
si
ness w
h
i
c
h i
s
r
e
prese
n
t
e
d
b
y
(1) is in
th
e d
e
scrip
tion
co
lu
m
n
. Th
e rest o
f
co
lu
m
n
s are for typ
e
o
f
th
e eq
u
a
tion
o
r
algo
rith
m
,
certain
value t
h
at aut
h
or
nee
d
t
o
indi
cate to and
unit of
data
or
inform
ation.
At this m
o
m
e
nt, it is not
necessary to fill
in
tho
s
e co
lu
m
n
s.
Next, after applying the
SBS
(see Fi
gure
2),
the m
o
re
detail Struct
ure
d
Vi
ew Ta
ble (SVT) is c
r
eated
as in
Tab
l
e
2
.
In
t
h
is tab
l
e, so
m
e
assu
m
p
tio
n
s
are
created. Econom
i
c growth
(1.1)
value is a c
onsta
nt, si
x.
Thi
s
num
ber i
s
t
o
s
h
ow t
h
at
t
h
e ec
on
om
i
c
fr
om
ot
her sect
o
r
s
has s
u
pp
ort
e
d
wel
l
i
n
t
o
o
u
r
sy
st
em
. Every
2
0
0
g
i
g
a
b
y
tes p
e
r
m
o
n
t
h
o
f
ICT
u
s
ag
e (3.1) wil
l
g
e
n
e
rate on
e
p
o
i
n
t
o
f
b
u
s
i
n
ess activ
ity (1
.2). Th
e activ
ities co
u
l
d
b
e
setting
up
a n
e
w co
m
p
an
y, creating a
p
r
oj
ect
o
r
o
t
h
e
rs.
No
t
all bu
sin
e
sses are run
n
i
ng
well, it is assu
m
e
d
th
at 1
%
of bu
sin
e
ss activ
ity (1
.2
)
will g
o
to b
a
nk
rup
t
cy
(1.3) o
r
failu
re. In
itial v
a
lu
e of ICT in
frastructu
r
e
(2.1) is
1
0
0
g
i
gab
y
tes p
e
r m
o
nth
.
An hun
dred po
in
ts
o
f
bu
si
n
e
ss activ
ity (1.2) will create
g
r
o
w
t
h
4
0
g
i
g
a
b
y
tes
per
m
ont
h
on
IC
T i
n
frast
ruct
ure
(
2
.
1
)
an
d
IC
T
usage
(
3
.
1
)
.
It
m
eans o
n
e
poi
nt
of
b
u
s
i
n
ess act
i
v
i
t
y
(
1
.
2
)
u
tilizes 0
.
4
g
i
gab
y
te p
e
r m
o
n
t
h
o
f
traffic. Cy
b
e
r crim
e effects (5.1) and
(5.2
) will m
a
k
e
so
m
e
p
e
op
le rel
u
ctan
t
to
u
s
e i
n
tern
et
in
th
eir activ
ities. On
e
p
o
i
n
t
in
creases of
cy
b
e
r crim
e effects (5
.1) and
(5.2
), th
is
will d
ecrease
0.
4 gi
ga
by
t
e
p
e
r m
ont
h of I
C
T usage (
3
.
1
). A
n
h
u
n
d
r
ed
poi
nt
s of
busi
n
ess act
i
v
i
t
y
wil
l
creat
e one p
o
i
n
t
o
f
b
u
s
i
n
ess cyb
e
r cri
m
e (5
.1).
An
hu
ndred
g
i
g
a
b
y
tes p
e
r m
o
n
t
h
of ICT in
frastru
c
ture (2
.1
)
will create o
n
e
p
o
i
n
t
of
b
u
si
ne
ss cy
ber
cri
m
e (5.
1
). T
h
e
bet
t
e
r
I
C
T i
n
f
r
ast
r
uct
u
re
(
2
.
1
)
i
s
d
e
vel
o
ped
,
t
h
e
m
o
re con
v
e
n
i
e
nt
ba
d
p
e
rson
do
es their illeg
a
l act
i
v
ities. Th
e id
eal ICT u
s
ag
e (3
.1
) is no
t
m
o
re th
an
5
0
%
of ICT in
frastructu
re
(2.1).
If t
h
e
ICT u
s
ag
e (3
.1) is m
o
re th
an 50
% ICT infrastru
c
tu
re (2
.1
), it is assu
m
e
d
th
at
p
e
rfo
rman
ce
d
e
grad
atio
n
is
started
.
Th
is sl
o
w
s
do
wn
th
e
g
r
o
w
t
h
of
ICT u
s
ag
e
(3
.1
).
In
th
is cond
ition
,
it is assu
m
e
d
th
at
th
e in
crease is o
n
l
y 2
5
%. An
hu
ndred
g
i
gab
y
tes p
e
r m
o
n
t
h
of ICT usag
e (3
.1
) will g
e
n
e
rate on
e po
in
t of
cyber law / re
gulation and e
n
forcem
ent (5.3); and one poi
nt
of soci
al
a
nd c
u
l
t
u
ral
cyber crim
e (5.2). Social
an
d cu
ltural st
reng
th
(5
.5
)
valu
e is sev
e
n
.
It is assu
m
e
d
th
at th
e urb
a
n p
e
o
p
l
e still has a goo
d
so
ci
al an
d
cultural st
ren
g
t
h
(5
.5
).
Tabl
e 2. St
ru
ct
ure
Vi
e
w
Ta
bl
e
(S
VT
) of Fi
g
u
re
2
No. Description
Equation
Type
Value
Unit
1 Business
1.
1 E
c
ono
m
i
c
Gr
owth
6 Cons
Point
1.
2 Business
Activity
(
1
.
1
)
+
(
4
.
1
)
+ (
3
.
1
)
/ 200
Point
1.
3 Bankr
uptcy
(
1
.
2
)
/ 100
Point
2
ICT
Infra
s
tru
c
tu
re
2.
1
I
C
T
I
n
fr
astr
uctur
e
(
2
.
2
)
–
(
2
.
3
)
L
e
vel
I
n
it = 100
Gigaby
tes per
m
onth
2.
2
Pr
oductivity
(
1
.
2
)
* 0.
4
(
2
.
1
)
per
m
onth
2.
3
I
n
activity
(
1
.
3
)
– (
2
.
1
)
per
m
onth
3 ICT
Usage
3.
1
I
C
T
Usage
(
3
.
2
)
– (
3
.
3
)
L
e
vel
I
n
it = 80
Gigaby
tes per
m
onth
3.
2
gr
owth of usage (
N
orm
a
l)
(
1
.
2
)
* 0.
4 +
(
4
.
1
)
* 0.
4
M
a
x =
(
2
.
1
)
* 0.
5
(
3
.
1
)
per
m
onth
gr
owth of usage
(
C
ondition)
(
1
.
2
)
* 0.
1 +
(
4
.
1
)
* 0.
1
if (
3
.
1
)
> (
2
.
1
)
* 0.5
(
3
.
1
)
per
m
onth
3.
3
decr
ease of usage
(
5
.
1
)
* 0.
4 +
(
5
.
2
)
* 0.
4
– (
3
.
1
)
per
m
onth
4. ICT
Education
4.
1
I
C
T
E
ducation
(
4
.
2
)
/ 100
Point
4.
2
Delay in E
ducatio
n
Adoption
Delay (
3
.
1
)
,
24
m
o
nth
Delay
Point
4.
3
Cy
ber
Crim
e Awareness
(
4
.
1
)
Point
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE Vo
l. 4
,
N
o
. 5
,
O
c
tob
e
r
20
14
:
668
–
6
78
67
3
5. Cyber
Cri
m
e
5.
1
Business Cy
ber
Crim
e
(
1
.
2
)
/ 100 + (
2
.
1
)
/ 100 –
(4
.3
) –
(5
.3
)
Min = 0
Point
5.
2
Social and Cultur
a
l Cy
ber
Cri
m
e
(
3
.
1
)
/ 100 – (
4
.
3
)
– (
5
.
3
)
–
(5
.5
)
Min = 0
Point
5.
3 Cy
ber
L
a
w/Regulation
and E
n
for
c
em
ent
(
5
.
4
)
/ 100
Point
5.
4
Delay in L
a
w Ado
p
tion
Delay (
3
.
1
)
,
36
m
o
nth
Delay
Point
5.
5
Social and Cultur
a
l
Str
e
ngth
7 Cons
Point
After all
of the assum
p
tions
are create
d
a
nd
put
in
to
t
h
e eq
u
a
ti
o
n
and alg
o
rith
m
,
Ven
s
im
PLE is
u
s
ed
to ru
n four typ
e
s
of sim
u
latio
n
:
(1
)
Run
-
No F
eedbac
k
and
Nor
m
al
Delay
. In
th
is test, t
h
ere is
no
feed
b
a
ck
fro
m
th
e ICT usag
e
(3.1) to th
e
ICT in
frastru
c
t
u
re (2
.1
).
No
co
rrectio
n
o
n
th
e
pro
d
u
c
tiv
ity
o
f
th
e ICT in
frastru
ct
u
r
e (2.1),
ev
en
t
h
oug
h th
e ICT
u
s
ag
e
(3.1
) h
a
s tak
e
n
mo
re th
an
5
0
%
of th
e ICT i
n
frastru
c
ture
(2.1)
cap
acity.
(2
)
Ru
n-No Feedbac
k
an
d Adjuste
d
Del
a
y
. N
o
fee
dba
ck as ex
pl
ai
n i
n
n
o
.
1 ab
ove
,
but
t
h
ere a
r
e
ad
ju
stm
e
n
t
s on
th
e “Delay
in
Edu
catio
n Ad
op
tion
(4.2
)” and
“Delay in
Law Ado
p
tion
(5
.4
)”. Th
ese
ad
ju
stm
e
n
t
s will
m
i
n
i
mize th
e cyb
e
r crim
e effects. Th
e adj
u
st
m
e
n
t
s are :
a) “
D
el
ay
i
n
E
ducat
i
o
n
A
d
o
p
t
i
on
(4
.2
)”
fr
o
m
24 m
ont
hs i
n
t
o
6 m
ont
h
s
.
b)
“Del
ay
i
n
L
a
w
Ad
o
p
t
i
o
n
(
5
.
4
)”
f
r
om
36
m
ont
hs i
n
t
o
1
2
m
ont
hs.
(3
)
Ru
n-Fee
d
back and Nor
m
al
Delay
. In
th
is test, th
e d
i
ag
ram
v
i
ew
is
m
odified (see Table 3.) to
take the ICT usage (3.1) as feedbac
k
to the
ICT infrast
ruc
t
ure (
2
.
1
)
.
If th
e gr
owt
h
of th
e ICT usage
(3
.1
) i
s
v
e
ry
fast, t
h
e i
n
terv
en
tion
is
n
eed
ed
t
o
m
a
k
e
th
e
ICT
in
fra
structu
r
e (2
.1
) follo
w
t
h
e
ICT
usa
g
e (3
.1
) gr
owt
h
.
(4
)
Run-Feed
back
an
d Ad
juste
d
Del
a
y
. The fee
d
bac
k
is in place a
s
explained i
n
no. 3. T
h
e
adjustm
e
nts are as e
xplaine
d
in no. 2.
In
SVT b
e
low (Tab
le. 3),
th
e ICT
in
frastru
c
t
u
re (2
.1
) al
wa
y
s
keeps t
h
e ut
i
l
i
zat
i
on bel
o
w
50%
o
f
i
t
s
capacity. If the
ICT Usage increases consist
e
ntly to take
m
o
re than 50
% of ICT in
fra
structu
r
e, the
n
m
a
nual
in
terv
en
tion
is
g
i
v
e
n
.
In
t
h
is case, th
e
o
w
n
e
r
will up
gr
ad
e the ICT i
n
frastructu
re
(2
.1
) wit
h
ad
d
ition
a
l
5
0
% of
ICT usage
.
Tabl
e
3.
St
ru
ct
ure
Vi
e
w
Ta
bl
e (S
VT
)
of M
o
di
fi
ed
Fi
g
u
re
2
No. Description
Equation
Type
Value
Unit
2.
2
Pr
oductivity
(
N
or
m
a
l)
(
1
.
2
)
* 0.
4
Norm
al
(
2
.
1
)
per
m
onth
Productivity
(Condition)
(1.2) * 0.4 +
(3.1)
* 0.
5
if (3.1) > (2.1
)
* 0.5
(2.1) per
m
onth
3.
3.
T
h
e Out
p
ut of
Si
mul
a
ti
on
The
res
u
l
t
s
o
f
f
o
u
r
t
e
st
s a
r
e
re
prese
n
t
e
d
i
n
so
m
e
fi
gu
res.
I
n
Fi
gu
re
3,
t
h
e
l
i
n
e
1 a
n
d
2 a
r
e
not
sm
oot
h
and
di
ffe
re
nt
fr
om
l
i
n
e 3 and
4. Th
e l
a
dde
r o
n
l
i
n
e 1 an
d 2
are t
h
e effect
o
f
t
h
e cor
r
ect
i
o
n i
n
p
u
t
fr
om
t
h
e IC
T
usa
g
e (3.1) as the feedbac
k
to the IC
T infrastru
c
ture (2
.1).
W
itho
u
t
th
i
s
feedb
ack, the g
r
o
w
t
h
o
f
t
h
e ICT
u
s
ag
e (3
.1) an
d th
e
b
u
sin
e
ss activ
ity
(1.2) are slower
(see li
ne
3 a
n
d 4).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Ad
ju
sting
ICT
Ca
pa
city Plann
ing
b
y
Mi
n
i
mi
zin
g
Cyb
e
r Crime Effects in Urb
a
n
Area
: …
(
F
el
di
ansy
a
h B
B
N
)
67
4
Fi
gu
re
3.
Ti
m
e
(m
ont
h)
v
s
IC
T I
n
f
r
ast
r
uct
u
r
e
(
g
i
g
a
b
y
t
es pe
r m
ont
h)
The g
r
a
ph l
e
ge
nd
of si
m
u
l
a
t
i
on i
s
t
h
e
bl
ue
l
i
n
e 1 f
o
r “R
u
n
-F
eed
bac
k
an
d A
d
just
e
d
De
l
a
y
”
, t
h
e red
line 2 for “Run-Feedbac
k
an
d N
o
rm
al
Del
a
y
”
, t
h
e gree
n l
i
n
e 3 f
o
r “R
un
-
N
o Fee
d
back a
nd
Ad
j
u
st
ed
D
e
l
a
y
”
and the
grey line
4
for “R
un-No Fee
dbac
k
a
n
d Norm
al Delay”.
The ne
xt
t
e
st
i
s
t
h
e adjust
m
e
nt
of del
a
y
com
ponent
s
i
n
ado
p
t
i
n
g cy
ber l
a
w/
reg
u
l
a
t
i
on an
d
enforcem
ent (5.4); and als
o
ICT educa
tion
(4
.2
). It
shows t
h
at th
e faster it can adop
t th
e
ch
ang
e
s on
t
h
e ICT
usa
g
e (3.1), the higher it
ca
n increase t
h
e business
ac
tiv
ity (1
.2
) (see
Fig
u
re
5
)
. Th
is i
s
th
e goo
d
i
npu
t to
go
ve
rnm
e
nt
t
o
speed
u
p
pr
o
cess of c
r
eat
i
n
g t
h
e cy
be
r l
a
w /
reg
u
l
a
t
i
on an
d en
f
o
rce
m
ent
;
and desi
gni
ng
a
go
o
d
pr
o
g
ram
fo
r e
ducat
i
o
n
s
ect
or t
o
l
ear
n t
h
e
new
t
ech
nol
ogy
.
Figu
re 4.
Tim
e
(M
o
n
th
) vs IC
T
Usa
g
e (
G
iga By
tes
per
M
o
n
t
h)
Fi
gu
re
5.
Ti
m
e
(M
o
n
t
h
)
vs B
u
si
ness
Act
i
v
i
t
y
(P
oi
nt
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE Vo
l. 4
,
N
o
. 5
,
O
c
tob
e
r
20
14
:
668
–
6
78
67
5
Th
e co
rrectio
n facto
r
is id
entified
b
y
calculatin
g
fro
m
ICT u
s
ag
e (3
.1
)
in
Figu
re
4
wi
th
adj
u
sted
d
e
lay (A) as lin
e
1
an
d normal (N) as lin
e
2. Th
e form
u
l
a i
s
Cor
r
ection
Fac
t
or
=
( A – N ) /
N
(3
)
Based
o
n
th
e
sim
u
la
tio
n
of
IC
T Usag
e, th
e c
o
rrection fact
or is calculate
d
below.
Table 4. ICT Usage of
Figure 4
No.
M
onth
A
N
Cor
r
ection
Factor
(%)
1.
0
80
80
0
2.
12
104
98
6
3.
24
139
118
17
4.
36
177
145
22
5.
48
221
180
23
6.
60
267
213
25
7.
72
321
251
28
8.
84
376
294
28
9.
96
440
334
32
10.
108
510
382
34
11.
120
584
436
34
12.
132
671
487
38
13.
144
761
545
40
14.
156
861
612
41
15.
168
979
688
42
16.
180
1095
752
46
17.
192
1228
832
48
3.
4.
ICT
C
a
p
a
ci
t
y
Pl
a
nni
n
g
An
al
ysi
s
B
a
sed o
n
dat
a
from
ITU (w
ww
.i
t
u
.i
nt
) an
d In
d
one
si
an s
t
at
i
s
t
i
c
s burea
u
(ww
w
.
b
ps.
g
o.
i
d
), t
h
e IC
T
u
s
ag
e of Pek
a
n
b
a
ru
,
o
n
e
of th
e cities in
Indo
n
e
sia is
esti
m
a
ted
(see Tab
l
e 5).
It
is assu
m
e
d
th
at th
e
g
o
v
e
rn
m
e
n
t
is ab
le to
exp
e
d
ite th
e
d
e
lays to
min
i
mize cyb
e
r crim
e effects
in
201
4.
Table 5. ICT Usage Peka
nbaru
City
No.
Descr
i
ption
2000
2001
2010
2011
2012
1.
T
o
tal Br
oadband Subscr
iber
(
x
1000 )
4
13
…
2280
2736
2983
2.
Total ICT
Usage
(t
erabytes
per
m
onth
)
16
60
…
9121
1094
6
1193
2
3.
T
o
tal people of I
ndonesia (
x 10000
0
0
)
206
206
…
238
238
238
4.
T
o
tal people of Pekanbar
u
City
(
x
1000)
586
598
…
898
898
898
5.
Per
centage of people
0.
28
0.
28
…
0.
38
0.
38
0.
38
6.
Total ICT
Usage i
n
Pe
kanbar
u
City
(gigaby
t
es
per
m
onth)
45
168
…
3466
0
4159
3
4534
1
In
Table
5, it i
s
assum
e
d that
each
broa
dba
nd s
ubs
cr
ibe
r
ge
nerates 4 giga
bytes
per m
onth of traffic.
The
perce
n
t
a
g
e
of
pe
opl
e i
s
t
o
t
a
l
peo
p
l
e
o
f
Peka
nba
r
u
ci
t
y
di
vi
de
d
by
t
o
t
a
l
pe
opl
e
of
In
d
onesi
a.
The
IC
T
usa
g
e o
f
Pe
ka
nba
r
u
ci
t
y
i
s
t
h
e perce
n
t
a
ge
o
f
pe
o
p
l
e
m
u
lti
p
lied
b
y
To
tal
ICT Usag
e. The italic b
l
u
e
num
b
e
rs
are estim
ated ones.
The
reg
r
essi
on
i
s
d
one
by
as
s
u
m
i
ng t
h
at
t
h
e
IC
T u
s
ag
e gr
ow
th
is
0
.
9
i
n
ev
er
y
year after
th
e last d
a
ta
(see Table 5).
This bec
o
m
e
s ICT usage
before the adjustm
e
nt
, or it is cal
le
d
as no
rm
al (N). It is n
o
rm
al r
e
su
lt
bef
o
re
ap
pl
y
i
n
g
c
o
r
r
ect
i
o
n
fa
ct
or
fr
om
t
h
e sim
u
l
a
t
i
on o
f
t
h
e m
odel
(see
Fi
g
u
re
4)
. E
q
uat
i
o
n
(
3
)
i
s
u
s
ed t
o
calculate the ICT usa
g
e a
f
ter
the adjustm
e
nt (A) a
n
d Ta
ble
6 is c
r
eated.
A
= N x ( 1
+ C
o
r
r
ect
i
o
n
Fac
t
or )
(4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Ad
ju
sting
ICT
Ca
pa
city Plann
ing
b
y
Mi
n
i
mi
zin
g
Cyb
e
r Crime Effects in Urb
a
n
Area
: …
(
F
el
di
ansy
a
h B
B
N
)
67
6
Table 6. ICT Usage of
Figure 4
No.
M
onth
Year
Cor
r
ection
Factor
(%)
N
A
1.
0
2014
0
5597
7.
284
0
5597
7.
284
0
2.
12
2015
6
6219
6.
982
2
6592
8.
801
1
3.
24
2016
17
6910
7.
758
0
8085
6.
076
8
4.
36
2017
22
7678
6.
397
7
9367
9.
405
2
5.
48
2018
23
8531
8.
219
7
1049
41.
41
02
6.
60
2019
25
9479
8.
021
9
1184
97.
52
74
7.
72
2020
28
1053
31.
13
54
1348
23.
85
34
8.
84
2021
28
1170
34.
59
49
1498
04.
28
15
9.
96
2022
32
1300
38.
43
88
1716
50.
73
92
10.
108
2023
34
1444
87.
15
42
1936
12.
78
67
11.
120
2024
34
1605
41.
28
25
2151
25.
31
85
12.
132
2025
38
1783
79.
20
28
2461
63.
29
98
13.
144
2026
40
1981
99.
11
42
2774
78.
75
99
14.
156
2027
41
2202
21.
23
80
3105
11.
94
56
15.
168
2028
42
2446
90.
26
44
3474
60.
17
55
16.
180
2029
46
2718
78.
07
16
3969
41.
98
45
17.
192
2030
48
3020
86.
74
62
4470
88.
38
44
Below is t
h
e
graph of
ICT
usa
g
e
before
and a
f
ter the
adjust
ment.
Figu
re 6.
Tim
e
(y
ear
) vs ICT Usag
e (
g
iga
b
y
t
es pe
r m
onth
)
after
(A
) a
n
d
b
e
fo
re
(N
) a
d
jus
t
m
e
nt.
4.
CO
NCL
USI
O
N
The sy
st
em
dy
nam
i
cs i
s
a recom
m
e
nded
m
e
t
h
o
dol
ogy
t
o
i
d
ent
i
f
y
c
o
m
p
o
n
ent
s
w
h
i
c
h a
r
e us
ual
l
y
not
seen
in
th
e classical way o
f
cap
acity p
l
an
n
i
n
g
. It g
e
n
e
rates
m
o
d
e
l. Mo
st
o
f
th
e tim
e,
mo
d
e
l is no
t a co
m
p
lete
and i
d
eal
o
n
e.
It
m
eans t
h
e behavi
or o
f
m
odel
i
s
not
exact
l
y
t
h
e sam
e
as
or hi
gh si
m
i
l
a
r
i
t
y
t
o
t
h
e real
sy
st
em
.
B
u
t
at
l
east
,
i
t
can be use
d
t
o
i
s
ol
at
e cert
a
i
n
com
ponent
s t
o
i
d
ent
i
f
y
h
o
w
t
h
ey
i
n
fl
uence
t
h
e beha
vi
o
r
of t
h
e
syste
m
.
In
ou
r case, t
h
e del
a
y
on ap
p
l
y
i
ng of cy
be
r
l
a
w /
regul
at
i
o
n an
d en
fo
rce
m
ent
(5.
4
);
an
d ad
opt
i
o
n i
n
IC
T ed
ucat
i
on
(4
.2
) are bei
n
g
st
udi
ed
. These
com
ponent
s a
r
e rel
a
t
e
d t
o
cy
ber cri
m
e effect
s. B
y
adjust
i
n
g t
h
e
param
e
t
e
r of t
h
ese del
a
y
s
, i
t
gi
ves a bet
t
e
r
pi
ct
ure o
n
t
h
e
im
pact
s of t
h
ese t
w
o com
pone
nt
s i
n
m
i
nim
i
zi
n
g
cyber crim
e effects and optimizing IC
T capaci
t
y
pl
anni
n
g
p
r
oce
ss t
o
s
u
p
p
o
rt
IC
T
us
age (
3
.
1
) a
nd
busi
n
ess
activ
ity (1
.2
).
M
a
ny
ot
he
r
un
i
d
ent
i
f
i
e
d
com
p
o
n
e
n
t
s
co
ul
d
i
n
fl
uence t
h
i
s
I
C
T capaci
t
y
pl
anni
ng
p
r
oce
s
s
as wel
l
.
F
o
r
furth
e
r stud
y, it is reco
mmen
d
e
d
t
o
m
a
k
e
th
e co
m
p
o
n
en
ts m
o
re
d
e
tail o
r
break it d
o
wn
i
n
to
smaller
com
pone
nts. T
h
is will ide
n
tify
m
o
re c
o
m
ponents
,
a
n
d m
o
re be
havi
ors
of
the system
.
Differen
t
g
o
a
ls will d
i
fferen
tiate h
o
w
to
b
r
eak
dow
n
th
e sy
ste
m
an
d
h
o
w to
op
ti
m
i
ze th
e
o
u
t
co
m
e
. In
ou
r case,
ou
r
goal
i
s
t
o
opt
i
m
i
ze t
h
e busi
n
ess sect
o
r
. T
h
e b
r
eak
d
o
w
n
i
s
gui
de
d t
o
achi
e
ve t
h
e
b
u
si
nes
s
co
m
p
etitiv
e ad
v
a
n
t
ag
e [1
5
]
.
Th
e o
t
h
e
r ex
am
p
l
e
o
f
th
is SBS is in
ed
u
c
atio
n
secto
r
wh
ich
ev
ery case h
a
s
speci
fi
c
goal
s
[
24]
,
[
25]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE Vo
l. 4
,
N
o
. 5
,
O
c
tob
e
r
20
14
:
668
–
6
78
67
7
Ev
en
th
is p
a
p
e
r is far fro
m
th
e ex
actn
e
ss
o
f
th
e real syste
m
, b
u
t
it id
en
tifi
e
s th
e i
m
p
acts o
f
d
e
lay o
n
th
e im
p
l
e
m
en
tatio
n
th
e
cyb
e
r crim
e law / reg
u
l
ation
an
d
en
fo
rcem
en
t; an
d adop
tio
n
i
n
ICT ed
u
cation
.
Th
e
lo
ng
er t
h
e pro
c
ess ru
n
s
, th
e sl
o
w
er th
e
p
e
o
p
l
e tak
e
s th
e
advan
t
ag
e
o
f
t
h
e ICT in
frastru
c
tu
re. It
will b
eco
m
e
a
go
o
d
i
n
p
u
t
n
o
t
onl
y
t
o
pri
v
a
t
e com
p
any
w
ho
o
w
n
s
IC
T
i
n
fra
st
ruct
ure
,
but
al
s
o
t
o
t
h
e
go
ve
rnm
e
nt
t
o
act
ap
pro
p
r
i
ately an
d co
m
e
w
ith
a go
od
pu
b
lic
po
licy.
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