In
te
r
n
ation
a
l Jou
rn
al
o
f E
v
al
u
a
t
i
on
a
n
d
R
e
se
arc
h
in
Ed
u
c
ation
(
IJERE
)
V
o
l.6,
N
o.3,
S
eptem
b
er
2
01
7
,
pp. 198~
2
0
6
IS
S
N
: 2252-
88
22
198
Jou
rn
a
l
h
o
me
pa
ge
:
ht
tp:
//i
a
e
sj
ourn
a
l.
com
/
on
line
/
in
dex.
p
h
p
/
I
J
ERE
Zoo Simulato
r to In
crease
Children Learning Phase
R
e
n
d
y
,
M
a
r
c
e
l
Bo
na
r
K
r
i
s
t
a
n
d
a
,
Se
ng
H
a
n
s
u
n
Inf
o
r
m
atics Departme
nt
, Un
i
versitas Mu
ltimed
ia Nusant
a
ra,
Tange
ra
ng
, Ind
on
e
s
ia
Art
i
cl
e In
fo
ABSTRACT
A
r
tic
le hist
o
r
y
:
Re
ce
i
v
e
d
Ju
l
2
6,
201
7
Re
vise
d A
ug
1
, 2017
Ac
ce
p
t
ed
Au
g
3
0
,
2
017
Th
e
gro
w
th
o
f
ki
ds'
b
r
a
i
n
co
uld
b
e
o
p
tim
ized
by
reco
gn
izi
ng
som
et
h
i
ng.
Learn
i
ng
t
o
reco
gni
ze
ani
m
als
is
o
n
e
o
f
th
e
m
e
tho
d
s
t
o
s
ti
mulat
e
th
e
c
h
ildre
n
's
b
ra
in
g
rowth
to
i
ma
gi
ne
.
Ne
ve
rth
e
le
ss,
k
ids
te
nd
t
o
sp
en
d
all
thei
r
tim
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b
y
p
l
a
yin
g
a
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c
o
u
l
d
n
o
t
f
o
c
us
t
o
recog
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i
z
e
th
e
an
im
als
du
e
t
o
t
h
e
w
a
y
of
l
earnin
g
w
h
i
c
h
i
s
us
ually
n
ot
i
n
t
eracti
v
e
and
no
t
interes
t
i
n
g.
T
he
r
e
fore
,
a
g
a
me
a
pp
lic
a
t
io
n
wa
s
de
sig
n
e
d
a
n
d
de
ve
lop
e
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to
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s
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a
s
a
wa
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t
o
help
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l
d
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en
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n
reco
gn
izin
g the anim
a
l
s.
T
his
pro
g
ram
w
a
s
d
e
vel
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p
e
d
as
a
m
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i
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pp
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with
t
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a
nima
ti
on
and
at
tractive
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spl
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to
i
ncrease
t
h
e
ki
ds
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interest
t
o
learn
th
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ani
m
a
l
s
.
B
esi
d
e
that,
Fis
h
er-Yates
s
huffle
al
gori
thm
has
been
s
uc
ces
s
f
u
lly
i
m
p
l
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t
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on
t
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gam
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t
o
rando
m
i
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th
e
im
ages
wh
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can
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f
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on
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uzzl
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rand
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th
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ans
w
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m
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m
als
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ld
,
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ods
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s
,
and
rand
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h
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i
t
i
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p
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o
create
p
a
ttern
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o
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r
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e
a
n
i
m
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l
pu
zzles.
A
f
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t
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tation
and
tes
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o
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ap
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4.
18
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n
ARCS
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com
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with
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ext
b
o
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k
m
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only
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.
7
4
.
K
eyw
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A
n
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i
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trod
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Fisher
-yates
s
h
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ffle
Mo
bi
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am
e
Puz
z
le
g
am
e
Ra
nd
omiza
tio
n
Zo
o simula
tor
Co
pyri
gh
t © 2
017 In
stit
u
t
e
of Advanced
En
gi
neeri
n
g
an
d
Scien
ce.
All
rights
res
e
rv
ed.
Corres
pon
d
i
n
g
Au
th
or:
S
e
ng H
a
n
s
u
n
,
Inf
o
r
m
atics
Department
,
U
n
i
v
ersi
tas M
u
l
tim
ed
ia
N
usantara
,
Jl
.
S
c
ient
ia
B
o
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le
var
d
,
G
a
di
n
g
S
e
r
pon
g,
T
ange
ran
g
,
Bante
n
-15
81,
I
ndo
nes
i
a.
Em
ail:
han
s
u
n
@
umn.
ac.
id
1.
I
N
TR
OD
U
C
TI
O
N
The
i
n
tro
duc
t
i
on
of a ne
w
t
hi
ng o
n
ch
i
l
d
r
e
n sho
u
l
d be
g
i
v
e
n
o
n
e
a
r
l
y
d
at
es.
Acc
o
rd
i
n
g
to
H
art
a
ti
[
1
]
,
chi
l
d
ren,
u
sua
l
ly
h
av
i
n
g
a
gre
a
t
c
u
r
i
os
it
y,
i
s
a
un
i
q
ue
i
n
d
i
v
i
d
ua
l
,
h
a
s
t
he
p
o
t
en
t
i
al
f
or
l
ea
rn
ing
a
n
d
l
i
ke
s
to
i
m
ag
i
n
e
and
ph
a
n
t
a
sm.
It
c
an
b
e
con
c
l
u
d
e
d
th
at
c
h
i
ld
ren
h
a
s
t
h
e
m
ost
sui
t
a
b
l
e
a
g
e
t
o
b
e
p
r
o
vid
e
d
wi
t
h
a
n
in
t
r
od
uc
ti
on t
o
some
t
h
i
n
g
ne
w
so tha
t
c
h
i
l
d
re
n
ca
n
op
t
i
mi
ze
t
he
ir
g
row
i
n
g
. A
c
c
o
rdin
g
t
o
H
u
r
lo
c
k
[
2],
the a
g
e
range
t
hat c
a
n
be c
lass
i
f
i
e
d as
k
i
d
s
i
s
b
etw
e
e
n
2 –
12 ye
ars ol
d.
Th
e
f
i
rst
fiv
e
y
ea
rs
o
f
ag
e
i
s
a
p
e
r
i
o
d
o
f
r
ap
id
b
rain
d
e
v
el
op
m
en
t
tha
t
i
s
o
f
te
n
ca
l
l
e
d
a
s
t
h
e
go
l
d
e
n
age.
C
hi
ldren
with
a
ge
o
f
the
fi
rst
fi
v
e
y
e
a
rs
h
a
v
e
p
hot
ograp
hi
c
m
e
m
o
ry,
r
eca
lli
ng
a
s
the
e
y
e
of
t
he
cam
er
a
[
3
].
B
a
s
ed
o
n
t
h
e
res
e
a
r
ch
r
es
u
l
t
s
d
on
e
wi
th
c
h
i
ld
ren
a
g
es
4
y
e
a
r
s,
t
he
c
a
p
a
c
i
t
y
o
f
t
he
c
hi
ldr
e
n
ha
s
rea
c
he
d
50
%,
a
nd
w
i
ll
r
ea
ch
80%
a
t
t
h
e
age
o
f
8
y
e
a
rs
[
4].
A
g
e
5
w
a
s
th
e
i
d
ea
l
age
for
in
tro
d
u
c
in
g
t
h
em
w
it
h
new
t
h
i
n
gs,
on
e
o
f
t
h
e
m
i
s
t
h
e
i
ntro
du
c
t
io
n
of
t
he
a
ni
mal
s
.
Int
r
o
d
u
c
t
i
o
n
of
a
n
i
ma
l
s
t
o
c
h
i
l
dr
e
n
c
a
n
s
t
i
m
u
l
a
t
e
t
he
brai
n
t
o
i
m
a
g
i
ne
a
n
d
t
ra
in
t
h
e
c
hil
d
re
n’s
cre
a
ti
vi
ty
[
5],
an
d
a
t
t
h
e
t
i
m
e
w
a
s
s
t
ill
in
t
he
p
eak
o
f
a
ch
i
l
d
'
s
brain
deve
l
opm
en
t,
s
o
the
k
i
d
s
a
re
e
a
s
y
to
c
a
t
c
h
t
h
i
n
g
s
t
h
at
a
re
c
ons
ide
r
ed
t
o
be
n
e
w
a
n
d
i
t
is
i
mp
or
t
a
nt
f
or
chi
l
d
ren
to
l
ear
n abo
u
t
a
ni
m
a
l
s
[6].
I
n
t
he
i
ntro
d
u
c
t
i
o
n
t
o
t
he
a
ni
ma
l
w
i
l
l
t
yp
ica
lly
u
se
m
edia,
suc
h
a
s
p
oster
s
a
nd
e
n
cyc
l
ope
dia,
b
u
t
t
h
e
me
dia
has
no
t
been
a
b
l
e
t
o
a
t
t
ra
ct
t
he
i
ntere
s
t
of
t
he
c
hi
ld
t
o
k
n
o
w
a
b
o
u
t
a
n
i
m
a
l
s
[
6
]
.
A
c
c
o
r
d
i
n
g
t
o
R
i
g
a
s
a
n
d
A
y
a
d
[
7
]
,
a
n
i
n
t
e
r
e
s
t
i
n
g
,
i
n
t
e
r
a
c
t
i
v
e
,
a
n
d
f
u
n
m
e
d
i
a
c
a
n
a
t
t
r
a
c
t
c
h
il
d
r
en
t
o sta
y
f
oc
use
d
o
n
t
h
e
ac
tiv
i
t
i
e
s
bei
n
g
perform
ed.
P
a
ckag
i
n
g
a
me
dia
i
n
trod
uc
t
i
on
i
n
t
o
t
he
g
a
m
es
w
ill
b
e
m
o
re
i
n
t
era
c
t
i
ve
a
nd
c
o
m
p
e
lli
ng
[
8]
.
Ed
uca
t
i
ona
l
p
a
cki
n
g
i
n
t
o
t
he
g
a
m
e
is
one
o
f
t
h
e
m
e
tho
d
s
of
l
e
a
r
ni
ng
k
n
ow
n
as
l
og
ica
l
l
ear
n
i
n
g
Evaluation Warning : The document was created with Spire.PDF for Python.
IJERE
I
S
S
N
:
2252-
88
22
Z
oo Sim
u
l
a
tor
t
o
Incre
a
se
C
h
ildre
n
L
e
arn
i
n
g
Ph
ase
(Re
n
d
y
)
19
9
pro
g
re
ssi
o
n
[9].
I
n
di
g
i
ta
l
ga
me
,
the
p
l
a
y
e
r
w
ill
be
d
ire
c
t
e
d
t
o
ma
st
e
r
a
g
ame
c
o
n
cep
t
i
n
di
rec
t
l
y
t
o
c
o
mp
l
e
te
the ga
me
[1
0
]
.
Ba
se
d
on
t
h
e
r
e
s
e
a
rc
h
th
a
t
h
a
s
b
e
e
n
do
ne
by
Ai
nu
l
[
1
1
]
,
t
h
e
ap
p
l
i
ca
t
i
o
n
o
f
sim
u
l
a
tio
n
ga
m
i
ng
m
ed
i
a
is
p
rove
n
c
a
n
i
ncre
ase
t
h
e
mo
ti
va
tio
n
of
s
tu
de
nts
fr
om
4
9.
5%
t
o
7
8%,
an
d
ba
sed
on
the
rese
arc
h
c
on
d
u
cte
d
by
W
ina
r
t
i
[
12
]
it
i
s
p
ro
ve
n
ca
n
a
t
tr
ac
t
l
e
arni
n
g
i
n
t
e
r
est
i
n
c
hi
l
d
ren.
T
h
i
s
i
s
due
t
o
t
h
e
use
of
t
h
e
g
a
m
ing
me
dia
w
h
ic
h
c
a
n
i
ncr
ease
c
h
ildre
n
'
s
a
tten
t
i
o
n
vis
u
al
l
y
t
hr
o
u
g
h
p
i
c
t
ure
s
,
p
hot
os,
sou
n
d
s,
a
nd
a
n
im
a
t
i
o
ns.
Th
e
F
i
sher
-Y
ates
a
l
gor
it
hm
i
s
a
n
a
l
g
or
it
hm
t
ha
t
p
e
rforms
shuffl
i
ng
i
m
a
g
e
on
t
he
s
et
o
f
nu
mb
e
r
s
[
1
3
]
.
Th
e
F
i
sh
er-
Y
a
tes
a
l
gor
ith
m
is
a
g
o
od
r
a
nd
om
n
umbe
rs
g
ena
r
at
or
b
e
cause
t
h
i
s
a
l
gor
it
hm
g
e
n
era
t
e
s
t
he
s
am
e
ra
nd
om
arr
a
y
for
ever
y
p
e
rm
utat
io
n.
A
cc
ordin
g
t
o
H
a
d
i
tam
a
a
n
d
S
lam
e
t
[
1
4
],
t
he
F
i
s
her
-
Y
a
te
s
a
l
gor
it
hm
w
ill
gene
ra
te
a
r
an
dom
p
erm
u
t
a
t
i
on
w
h
ic
h
i
s
o
r
d
er
ed
s
o
a
s
t
o
m
a
ke
t
h
e
q
u
es
ti
on
tha
t
h
as
a
risen
w
i
l
l
n
o
t
a
ppea
r
aga
i
n i
n
the sa
m
e
se
ssio
n. Ba
s
ed o
n
t
h
e ab
o
v
e pro
b
l
em
s in
t
h
i
s
re
sear
ch, we will
cr
eate an an
i
m
a
l
r
eco
gn
i
tio
n
a
s
z
o
o
s
i
m
u
l
a
t
o
r
u
s
i
n
g
F
i
s
h
e
r
-
Y
a
t
e
s
a
l
g
o
r
i
t
h
m
t
o
h
e
l
p
i
n
c
r
e
a
s
i
n
g
c
h
i
l
d
r
en'
s
i
nt
e
r
est
i
n
t
h
e
i
nt
ro
du
ct
io
n
of
anim
al
s.
2.
F
I
S
H
ER
-
Y
AT
ES
S
HU
F
F
L
E
A
L
G
O
R
I
T
H
M
A
c
cordi
n
g
t
o
E
xr
idor
es
a
n
d
S
oprya
di
[
15
]
,
t
he
F
isher
-
Y
a
t
e
s
S
h
u
f
fle
a
l
g
o
r
it
hm
i
s
a
be
tt
e
r
m
etho
d
of
rand
om
izat
i
o
n
or
c
a
n
b
e
sai
d
t
o
b
e
s
uita
bl
e
for
ra
ndom
i
z
a
t
i
o
n,
w
ith
a
r
a
p
i
d
e
xec
u
t
i
o
n
tim
e
a
nd
do
e
s
n
o
t
requ
ire
a
l
o
n
g
time
t
o
do
a
rand
om
iza
t
io
n.
T
he
F
i
s
her
-
Y
a
te
s
S
h
u
ffle
a
l
g
o
r
it
hm
i
s
use
d
t
o
cha
nge
t
he
o
r
d
er
o
f
e
n
t
r
i
e
s
g
i
v
e
n
ra
n
d
o
m
ly
a
n
d
p
e
r
mut
a
ti
on
s
g
e
ne
rat
e
d
by
t
hi
s
algo
r
i
t
hm
c
om
es
u
p
w
i
t
h
t
h
e
s
am
e
p
r
ob
a
b
il
i
t
y
[
16].
A
c
cordi
n
g
t
o
A
tw
oo
d
[
17],
the
F
i
sher
-Y
ate
s
S
huff
l
e
i
s
b
e
tter
t
h
a
n
t
he
N
aive
S
h
u
ffle
a
l
gor
ithm
.
I
n
F
i
gure
1,
t
h
e
F
ishe
r-Y
a
t
es
S
huf
fle
has
a
n
a
v
e
rage
o
cc
ur
renc
e
of
t
he
c
om
bina
t
i
o
n
o
f
r
a
nd
omiz
at
io
n
w
h
i
c
h
i
s
alm
o
st
t
he
s
a
m
e
com
p
ar
ed
w
it
h
Naive
Sh
uffl
e
tha
t
h
a
s
a
p
ar
t
i
c
u
l
a
r
c
om
bina
t
i
o
n
t
ha
t
o
f
te
n
ap
pe
ars
.
T
he
expe
r
i
me
n
t
s
tr
ie
d to scr
am
bl
e
4-d
i
g
i
t num
ber
as m
uch
as 60
0
,
0
0
0
ti
m
e
s
[
17
]
.
F
i
gure
1.
T
he
c
om
paris
on re
sult
s of F
isher
-
Y
a
te
s
S
huff
l
e
w
ith N
a
i
ve S
huffle
[1
7]
The
r
e
are
four ste
ps in
the
F
i
s
h
er
-Y
ate
s
S
huf
fle a
l
gor
ithm
a
cco
r
d
in
g
to
E
x
r
id
ores a
nd S
oprya
di [
1
5
]
.
a.
Wr
ite
dow
n th
e
numbe
rs fr
o
m
1 to N.
b.
P
i
c
k
a
r
andom
num
ber
K
be
t
w
een
1
up
to
t
he
num
ber
of n
um
ber
s
t
h
at
h
as
n
ot
b
e
e
n
c
ro
ss
e
d
ou
t
.
c.
Cal
c
ul
at
e
d
f
rom
t
h
e
b
e
gi
nni
ng
o
f
th
e
st
re
ak
,
t
h
e
nu
mb
e
r
K
t
h
a
t
h
a
s
n
o
t
b
e
e
n
c
ro
ssed
out
,
and
wri
t
e
d
ow
n
tha
t
n
um
ber
elsew
h
e
r
e.
d.
Re
pea
t
s
t
e
p 2 a
nd ste
p
3
u
n
til
all t
h
e num
ber
s
ar
e
a
lrea
dy cr
os
se
d
o
u
t
. The se
que
nce
of n
um
ber
s
w
ritte
n in
ste
p
3
i
s
a
random
per
mutat
i
o
n
of t
h
e n
u
m
b
e
r
s.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2252-
8822
IJERE
V
ol
.
6,
N
o.
3,
S
eptem
b
er
20
17 :
1
9
8
– 206
20
0
3.
ARC
S
MEASURE
M
E
NT
I
n
t
e
rest
w
a
s
d
r
i
ve
n
b
y
t
he
d
e
s
ire
o
f
a
f
ac
tor
after
w
a
t
c
h
i
ng
,
o
bse
r
v
i
n
g
,
co
m
p
ar
i
n
g,
a
nd
c
ons
i
d
er
ing
the
nee
d
s
o
f
t
h
e
d
esire
d
[
18].
Inter
e
st
i
n
lea
r
nin
g
i
s
a
me
n
t
a
l
fram
e
w
o
rk
c
ons
i
s
ts
o
f
a
c
o
m
b
ina
t
i
o
n
of
m
otio
n
and
m
i
xt
ure
of
f
ee
li
n
g
s,
p
re
ju
dice
s,
a
n
x
i
o
us
a
nd
ten
d
e
n
cies
o
f
the
othe
r
ordi
nary
r
e
d
i
r
ect
s
the
ind
i
v
i
dua
l
t
o
a
part
icu
l
ar
o
p
t
i
on
[1
9].
Base
d
on
t
he
p
r
o
pos
ed
m
ode
l
of
J
o
h
n
K
e
l
le
r
w
ho
ha
s
m
a
de
a
n
i
n
str
u
m
e
ntal
me
asure
m
e
n
t
of
i
n
t
er
est
a
n
d
m
o
ti
va
tio
n,
i
nt
e
r
es
t
i
n
l
e
a
rni
n
g
c
a
n
be
b
ased
o
n
fo
ur
m
a
i
n
com
p
o
n
e
n
t
s
,
in
ac
corda
n
c
e
w
ith
t
he
m
ode
l,
n
am
ely A
RCS
[
20].
a.
A
tte
nt
ion
T
he
i
n
t
er
est
o
f
l
e
a
r
n
i
n
g
ac
tivi
t
i
e
s
m
ust
no
t
on
l
y
r
aise
d,
but
mu
st
a
l
s
o
b
e
m
ain
t
a
i
n
e
d
du
ring
l
e
a
r
ni
ng
ac
t
i
v
i
ti
e
s
ta
k
in
g plac
e.
b.
Re
leva
nc
e
R
e
l
ate
d
t
o
t
h
e
ali
g
nm
en
t of
t
h
e
lea
rni
ng m
a
t
e
ria
l
p
rese
nte
d
w
i
t
h
a
l
ear
ning
e
xper
i
e
n
ce.
c.
Confide
n
ce
R
e
l
ate
d
t
o
t
h
e
att
i
t
ude
o
f
trus
t,
i.e.
wil
l
b
e su
cc
essful or
t
ha
t
is a
ssoc
i
a
te
d w
i
t
h
the
h
o
p
e t
o
s
uc
ce
e
d
.
d.
Sa
ti
sfa
c
t
io
n
C
om
plac
e
n
c
y
c
a
n
a
rise
f
rom
w
ithi
n
t
he
i
nd
i
v
i
dua
l
h
i
m
s
e
l
f,
c
a
l
l
e
d
a
s
i
n
tr
is
t
i
k
pri
d
e
w
h
er
e
ind
i
v
i
dua
l
fee
l
s
sat
i
sf
ie
d a
nd pr
ou
d t
o
h
ave
su
c
cessful
l
y
e
xec
u
te
d,
a
chie
ve
d,
or
g
et som
eth
i
ng.
Tabl
e
1
i
s
t
h
e
s
c
o
ri
ng
i
nt
ere
s
t
of
A
RCS
[
21
].
A
p
o
s
i
t
i
v
e
st
at
e
m
ent
w
i
th
s
tron
g
l
y
a
g
r
ee
cr
i
t
e
r
ia
i
s
gi
ve
n
va
l
u
e
5
w
h
ile
t
he
c
ri
t
e
ria
o
f
v
e
r
y
disa
gr
ee
is
g
ive
n
t
he
va
lue
o
f
1
.
N
e
ga
tive
s
t
a
t
e
m
ent
va
l
u
at
i
o
n
ups
i
d
e
dow
n
fr
om
a
p
os
iti
ve
s
ta
tem
e
nt, beg
i
nn
ing
w
ith
a
scale
o
f
1
t
o
5
w
h
ich
sc
ale
s
f
r
o
m
st
r
ongl
y
a
g
re
e t
o
s
t
r
on
g
l
y
di
sa
gree
.
Ta
b
l
e 1.
Inde
x of
A
RCS
Cr
i
t
e
r
i
a
Sc
or
e
P
o
sitive
Sta
t
em
ents
N
e
ga
t
i
ve
Sta
t
em
e
n
ts
S
t
ro
ngl
y
a
g
ree
(SA
)
5
1
A
g
ree
(A
)
4
2
N
e
ut
r
a
l
(N)
3
3
No
t Ag
r
ee (
N
A
)
2
4
S
t
ro
ngl
y
not
A
gre
e
(
S
NA
)
1
5
(
1
)
Eq
uat
i
on
(
1
)
show
s
the
form
ula
t
o
c
alc
u
late
t
he
f
i
n
a
l
s
core
o
f
the
A
RCS
i
n
t
h
e
m
e
a
s
ur
e
m
ent
of
i
n
t
er
est
[
21].
The
ave
r
age
sc
ore
ca
n
be
g
e
n
er
ated
f
rom
the
sum
of
a
l
l
posi
t
i
v
e
a
n
d
n
e
g
a
t
i
v
e
sta
t
em
en
ts
t
he
n
d
i
v
i
de
d
b
y
t
he
numbe
r of s
tat
e
m
e
nt m
ul
tip
li
ed by
t
h
e
n
u
m
b
er
o
f
t
h
e
cor
r
espo
n
d
e
nts.
4.
RESEARCH
M
ETH
O
D
Rese
arc
h
m
eth
ods
u
sed i
n
t
hi
s re
sear
ch are
dev
i
d
ed
i
nt
o
si
x
ste
ps:
a.
Lit
e
rature S
t
u
dy
The
l
ite
rat
u
re
s
tud
y
i
s
t
h
e
pr
ocess
o
f
s
t
u
dy
i
ng
the
t
h
eorie
s
a
s
s
o
ci
at
ed
w
ith
th
e
g
a
mes
wi
ll
b
e
bu
i
l
t
,
suc
h
a
s
the
m
a
ki
n
g
o
f
t
h
e
ga
me
w
it
h
C
#
b
a
sed
A
ndr
o
i
d
app
l
i
c
a
t
i
o
n
,
t
h
e
F
i
she
r-Y
a
t
e
s
S
hu
ffle,
t
he
t
ype
s
of
anim
al
s and
th
e
i
r c
h
ara
c
teris
t
i
c
s, c
once
p
ts
a
nd c
a
te
g
o
ries
o
f e
duca
t
io
na
l g
a
me
s.
b.
Need
s An
aly
s
is
N
e
eds
ana
l
ys
is
o
f
fe
a
t
ures
t
ha
t
w
oul
d
be
n
e
e
d
e
d
t
o
do
th
e
d
e
si
g
n
a
nd
de
ve
lo
pme
n
t
o
f
t
he
s
im
ul
a
t
i
o
n
gam
e
s,
s
u
c
h
as
t
he
s
c
r
ip
t
co
n
t
rolle
r
t
o
b
e
m
a
de
,
is
d
o
n
e
i
n
t
h
i
s
ph
a
s
e
.
T
he
s
cri
p
t
cont
rol
l
e
r
is
a
n
ob
j
e
ct
t
h
a
t
serve
s
a
s
t
h
e
s
e
tt
i
ng
of
a
ll
t
h
e
G
r
oove
s
ys
te
m
found
i
n
t
he
g
a
m
e
.
C
o
n
t
r
o
l
l
e
r
c
o
n
t
a
i
n
e
d
i
n
a
g
a
m
e
i
s
v
e
r
y
di
verse,
such
as the
scrip
t c
o
n
t
r
o
l
l
er
a
nim
a
ti
on,
s
l
i
der
con
t
r
o
l
l
er,
and
musi
c
contr
o
l
l
er.
c.
A
p
p
l
i
c
a
t
io
n D
e
si
gn
F
l
owchar
t
de
si
gn
i
s
c
r
ea
te
d
f
o
r
e
a
s
i
er
v
iewi
ng
o
f
t
h
e
o
v
e
r
all
f
low
of
t
he
s
ys
tem
.
A
fter
t
he
d
e
s
ig
n
com
p
le
te
d,
w
e proce
e
d
w
i
t
h t
h
e
des
i
g
n
of
t
h
e playe
r
i
nter
fa
c
e
.
F
i
gure
2
(le
f
t
)
i
s
a
ge
nera
l
flo
w
char
t
of
t
h
e
g
am
es.
Whe
n
t
he
g
am
e
starts,
the
pr
ogr
am
w
ill
d
i
rec
tly
che
c
k
t
h
e
f
ile
.
I
f
t
he
X
M
L
f
i
l
e
doe
s
n
o
t
e
xi
st,
i
t
w
i
ll
be
i
n
s
t
a
n
t
l
y
cre
a
te
d
a
l
l
o
f
t
he
X
M
L
.
The
ne
xt
p
r
o
cess
ca
l
l
s the
v
i
ew
con
tro
l
l
e
r w
h
i
c
h ge
nera
ll
y se
t
w
h
ic
h pane
ls a
re
off an
d w
h
ic
h
a
r
e o
n
. A
f
ter
tha
t
t
he s
ys
t
e
m w
i
ll
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ERE
I
S
S
N
:
2252-
88
22
Z
oo Sim
u
la
to
r to
I
n
cre
a
se
C
h
il
dre
n
L
e
arn
i
n
g
Ph
ase
(
R
e
n
d
y
)
20
1
do
t
he
c
he
c
k
i
ng
w
h
e
t
her
t
h
er
e
is
a
b
u
t
to
n
th
at
i
s
pr
e
s
se
d.
I
f
a
ny
b
utt
o
n
is
p
re
sse
d
,
the
s
y
s
t
e
m
w
ill
im
me
di
a
t
el
y ca
ll
t
he c
o
n
t
r
o
lle
r
that ha
n
d
l
e
s
t
he
b
u
tto
ns.
F
i
gur
e
2 (
r
i
g
h
t
)
show
s
t
h
e
f
l
o
w
c
h
ar
t of
F
ish
e
r
-
Y
a
t
e
s
s
hu
ff
le
a
l
gor
i
t
h
m
.
The pr
o
cess
be
g
i
ns b
y ta
ki
n
g
t
h
e
l
e
n
g
t
h
o
f
a
n
a
r
r
a
y
.
I
f
t
h
e
a
r
r
a
y
l
e
n
g
t
h
i
s
n
o
t
g
r
e
a
t
e
r
t
h
a
n
o
ne,
the
n
t
he
p
roc
e
ss
w
ill
b
e
d
irec
tl
y
q
u
i
t
.
I
f
the
len
g
t
h
of
t
he
a
r
r
a
y
is
m
or
e
th
an
o
ne,
set
t
h
e
te
mp
v
a
l
ue
t
h
e
s
a
me
a
s
th
e
len
g
t
h
of
t
he
a
r
r
a
y.
A
f
t
e
r
t
ha
t,
t
h
e
tem
p
v
a
l
ue
i
s
d
e
c
r
ea
sin
g
1
.
I
f
the v
a
l
ue
i
s no
t
gr
e
a
ter
t
h
an or
e
qua
l
to
zer
o,
t
he
n
the pr
oc
es
s
of
r
a
n
d
o
miza
tio
n
is
c
o
n
s
i
der
e
d
c
o
mple
te
.
H
o
w
e
ve
r
,
i
f
the
va
lue
of
t
he
t
e
m
p
is
g
r
e
a
t
e
r
o
r
e
q
u
a
l
t
o
0
,
t
h
e
n
s
e
t
t
h
e
v
a
l
u
e
x
b
a
s
e
d
on
a
r
a
n
dom
num
ber
star
ts
f
r
o
m
0
t
o
t
em
p.
T
hen
sw
i
t
c
h
i
nde
x-
t
o
-
tem
p
w
i
t
h
i
nde
x-
t
o
-
x
,
a
n
d
de
cr
e
a
se
t
h
e
va
lue
o
f
t
em
p wit
h
1.
After
that r
epea
t the
p
r
oce
s
s
un
til t
h
e
t
em
p valu
e
eq
ual
s
z
ero.
Fi
g
u
r
e 2
.
M
a
i
n f
l
o
w
c
h
a
r
t
(l
eft) a
n
d
Fi
s
h
er-Y
at
e
s
shu
ffl
e flowch
a
r
t (
r
igh
t
)
d.
App
lica
tio
n D
e
vel
o
pm
ent
A
p
p
l
i
c
a
t
io
n
de
ve
lo
pm
ent
w
a
s
us
in
g
U
n
i
t
y
v
e
r
s
io
n
5.
1.
3
f
1
(
64-
b
i
t
)
a
nd
M
o
n
o
D
e
v
e
l
op
a
s
t
he
I
D
E
(
I
ntegr
a
t
e
d
D
e
vel
o
pme
n
t
En
v
i
r
o
nme
n
t)
.
I
n
t
he
d
e
v
e
l
o
p
me
n
t
o
f
t
h
e
g
a
m
e
,
p
r
o
gr
a
m
m
i
ng
l
a
ng
ua
ge
u
se
d
i
s
C
#
.
The
desi
g
n
o
f
t
h
e
spr
i
te
a
sse
ts
a
nd
o
t
her
a
n
i
m
atio
ns
w
er
e
c
r
e
a
t
ed
u
si
n
g
C
or
e
l
D
r
a
w
X
7
a
nd
A
dobe
P
h
o
tos
h
op
CS6.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
2
5
2
-
88
22
I
J
ERE
Vol.
6, No.
3
, Se
pt
e
m
b
e
r
2017
: 198
– 206
20
2
e.
Te
stin
g
a
n
d
S
u
r
v
eys
A
t
t
h
i
s
sta
g
e
,
t
he
g
a
m
e
a
p
p
l
i
c
atio
n
tes
tin
g
i
s
p
er
f
o
r
m
ed
b
y
us
i
n
g
t
h
e
S
a
m
s
u
n
g
G
a
l
a
x
y
M
e
g
a
6
.
3
,
S
a
m
s
ung
G
a
la
xy
G
r
a
nd
P
r
i
m
e,
a
nd
X
i
a
o
mi
R
e
d
m
i
3
s
m
a
r
t
ph
ones.
T
he
p
ro
ces
s
o
f
tes
t
in
g
perfo
r
m
ed
o
n
c
h
il
dr
e
n
w
it
h
t
h
e
age
r
a
nge
b
e
t
w
e
en
5
t
o
8
y
e
ar
s
ol
d.
Pha
s
es in te
st
i
ng a
r
e
as follo
ws.
1.
Th
e c
o
r
r
e
s
p
ond
e
n
t
was g
i
v
e
n
a
n
i
n
t
r
o
du
ct
ion
t
o
ani
ma
l
s
u
si
ng
t
e
xt
b
ook
me
thod.
2.
The
c
o
r
r
esp
o
nde
n
t
w
a
s
g
i
v
en
a
q
uest
i
o
nna
ir
e
m
easur
in
g
t
h
e
i
r
i
n
t
e
r
est.
D
urin
g
t
h
e
fi
lli
n
g
o
f
t
h
e
que
st
i
o
n
n
a
i
r
e
c
or
r
e
spo
n
d
en
ts
a
r
e
g
ive
n
a
n
ex
pla
n
a
t
i
o
n
of
t
h
e
i
n
te
n
t
of ea
ch
ques
tio
n.
3.
The
cor
r
espo
n
d
en
t
w
a
s
gi
ven
an
i
ntr
o
d
u
c
t
i
o
n
to
t
he
g
am
e
(zoo
s
i
mu
lato
r).
4.
The
cor
r
espo
n
d
en
t wa
s gi
ven
a que
stio
n
n
air
e
m
easur
i
ng
th
e
inter
est
b
a
ck
.
5.
Du
ri
ng
t
h
e
f
illi
ng
o
f
th
e
qu
esti
onn
ai
re
,
c
o
rre
s
p
o
n
d
e
nt
s
are
g
i
v
e
n
a
n
e
x
p
l
an
at
ion
o
f
t
h
e
i
nt
e
n
t
o
f
each
que
st
i
on.
6.
Co
rres
p
on
d
e
nt
s
we
re
as
k
ed
t
o fi
ll
ou
t
anot
h
e
r q
u
e
st
i
onn
a
i
re
reg
ar
din
g
t
he
l
oo
k
an
d
nav
i
ga
ti
on
of
t
he
g
am
e.
f.
Ev
a
l
u
a
t
i
on
At
t
hi
s
st
ag
e,
d
a
t
a
t
h
a
t
h
as
b
e
e
n
col
l
ect
ed
fro
m
su
rv
ey
b
e
f
o
r
e
a
nd
af
t
e
r
pl
a
y
ing
t
h
e
ga
m
e
w
il
l
be
e
v
al
ua
te
d.
A
RCS
i
s
a
fa
l
s
e
a
s
se
r
t
i
on
m
e
t
h
o
d
t
ha
t
i
s
u
se
d
t
o
f
i
n
d
ou
t
t
h
e
per
c
en
tage
o
f
suc
cess
i
n
i
n
t
r
o
duc
i
n
g
the
a
n
i
m
als
g
a
m
e
a
gain
st
t
he
i
n
t
ere
s
t
of
l
ea
rni
n
g,
w
her
eas
L
ike
r
t
s
c
a
le
i
s
a
me
t
hod
of
f
a
l
se
a
sse
r
t
i
o
n
a
p
p
lica
tio
n
use
d
t
o
f
i
nd
o
u
t
t
h
e
pe
r
c
e
n
t
a
ge
o
f
s
u
cc
ess
t
h
e
gam
e
a
ppl
ica
t
i
on
a
g
a
i
n
s
t
asse
ssm
e
nt
e
va
lua
tio
n
o
f
the
de
si
g
n
of
the
user
in
t
erfa
ce
a
n
d
n
av
i
g
a
t
i
on.
5.
RESU
L
T
S
A
ND ANALY
S
IS
F
i
gur
e
3
i
s
t
he
d
isp
l
a
y
o
n
t
h
e
lo
bby
p
a
n
e
l
w
hi
c
h
c
o
n
ta
i
n
s
f
our
bu
tto
ns,
i.
e
.
z
oo
r
e
v
i
ew
,
o
f
f
i
ce
,
stor
e
(
i
n
t
h
e
for
m
o
f
a
bu
ild
i
ng)
,
a
n
d
mi
ni
g
am
es
(
i
n
t
he
f
or
m
o
f
t
he
b
uil
d
i
n
g
)
.
Zoo
rev
i
e
w
w
i
l
l
c
a
ll
a
p
opup
t
h
a
t
di
sp
la
ys
t
he
g
r
a
din
g
o
n
al
l
z
o
os
t
he
p
la
yer
ha
s,
z
oo
of
fi
ce
w
i
l
l
d
i
s
p
la
y
be
a
s
ts
d
a
t
a
w
h
ic
h
ha
ve
b
e
e
n
o
bta
i
ne
d,
the
s
t
ore
serve
s
t
o
s
t
or
e.
exe
p
o
p
u
p
c
al
l
t
h
a
t
c
on
ta
in
s
som
e
S
t
a
tes
tha
t
c
a
n
b
e
pur
chase
d
b
y
p
l
ayer
s,
a
nd
mini-
ga
me
s
w
ill
f
e
a
t
ur
e
a
m
i
n
i
g
a
m
ing
sce
n
e
in
t
he
Z
oo
S
i
m
ul
ator
.
F
i
gu
re
4
s
h
o
w
s
th
e
c
a
ges
c
ont
a
i
ni
ng
a
n
i
ma
l
s
wit
h
fu
ll hu
n
g
r
y
b
ar
, a
nd will
gene
ra
te
a
c
oin
pe
r m
i
nu
t
e
.
F
i
gur
e
3.
L
ob
b
y
p
ane
l
d
ispla
y
F
i
gur
e
4.
A
nim
a
l
di
sp
l
a
y
F
i
gur
e
5
sh
ow
s
t
h
e
i
n
t
e
r
f
ace
o
f
t
h
e
sce
n
e
w
i
t
h
t
he
t
ype
o
f
r
e
sc
ue
c
om
m
on
a
n
ima
l
s,
w
i
t
h
th
e
r
e
su
lts
of
F
is
her
-
yate
s
shu
f
f
l
e
a
l
gor
i
t
h
m
implem
e
n
t
a
ti
o
n
t
o
per
f
or
m
a
n
i
m
a
l
p
h
o
t
o
s
a
nd
a
n
sw
er
r
a
ndom
iza
t
i
o
n
.
T
he
di
sp
la
y
c
o
n
t
a
i
n
s
a
p
h
o
t
o
o
f
a
n
an
im
al
t
ha
t
ha
s
bee
n
s
c
r
am
bl
ed
a
n
d
t
h
e
r
e
a
r
e
f
o
u
r
c
h
o
i
c
e
s
o
f
a
n
s
w
e
r
s
.
I
n
t
h
i
s
ty
pe
o
f
r
e
scue
,
p
l
a
yer
s
a
r
e
r
e
qui
r
e
d
to
g
uess
t
h
e
nam
e
o
f
the
a
nima
l.
F
i
gur
e
6
s
h
ow
s
t
h
e
di
sp
la
y
w
i
t
h
a
r
ar
e
typ
e
r
escue
,
a
nd
the
r
e
s
ul
ts
o
f
F
i
she
r
-
Y
a
t
e
s
a
lg
or
i
t
hm
t
o
d
o
the
r
a
n
dom
iza
t
i
o
n
plac
em
e
n
t
pa
tter
n
t
o
lo
o
k
f
or
.
The
sc
e
n
e
show
in
g
t
h
e
n
u
mbe
r
o
f
a
ttem
p
t
tha
t
c
a
n
b
e
pe
r
f
or
m
e
d,
p
hot
os
o
f
an
ima
l
s,
a
nima
l
pa
tte
r
n
t
o
l
o
ok
f
o
r
in
t
he
b
o
x
4
x
4,
n
a
m
e
s
o
f
an
ima
l
s
wi
t
h
a
4
x
4
box
in
i
t
a
l
r
e
a
dy
c
o
nt
a
i
ns
p
a
tter
n
s
of
a
n
i
ma
l
s
,
c
o
in,
a
n
d
z
o
nk.
T
he
p
laye
r
mu
st
ope
n
t
h
e
bo
x
one-
by-
one
u
n
til
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
IJERE
I
S
S
N
:
2252-
88
22
Z
oo Sim
u
l
a
tor
t
o
Incre
a
se
C
h
ildre
n
L
e
arn
i
n
g
Ph
ase
(Re
n
d
y
)
20
3
ca
n
fin
d
a
p
a
t
t
e
r
n
t
o
d
o
t
he
a
ni
m
a
l
s
r
escue
.
F
igure
7
s
h
o
w
s
the
l
o
o
k
o
f
t
h
e
m
i
n
i
g
am
e
scene
.
I
n
the
mini-
gam
e
,
the
p
l
a
y
er
can
c
o
llec
t
c
o
i
n
as
m
uc
h
as
p
o
ssi
ble
to
i
ncre
a
se
h
is
c
oi
n
bes
i
de
s
t
h
e
c
o
i
n
w
h
i
c
h
w
as
pro
duce
d
b
y th
e
anim
als he
h
as.
F
i
gure
5.
R
e
s
c
u
e
com
m
on
ty
pe
di
s
p
l
a
y
F
i
gure
6.
R
e
s
c
u
e
rare type
d
ispla
y
F
i
gure
7.
M
i
n
i
G
a
me dis
pla
y
5.1.
Fisher-Yates s
huffle
In
t
h
i
s
t
e
st
,
we
w
i
l
l
se
e
i
f
F
is
h
e
r-Yat
es
a
l
g
o
r
it
h
m
c
an
g
en
era
t
e
a
per
m
uta
t
io
n
b
y
l
i
k
e
l
y
a
l
m
o
s
t
t
he
s
a
m
e
e
a
c
h
t
i
m
e
.
F
r
o
m
T
a
b
l
e
2
,
t
h
e
a
v
e
r
a
g
e
o
c
c
u
r
r
e
n
c
e
o
f
5
0
0
t
i
m
es,
1,000
t
i
m
e
s
,
and
1
0
,
0
00
tim
es
rand
om
izat
i
o
n
is
±
2
5%.
Ther
e
is
n
o
sig
n
i
f
ic
a
n
t
d
i
ffere
nce
in
t
he
p
e
r
ce
n
t
a
g
e
o
f
o
cc
urr
e
nce
for
eac
h
a
n
i
m
a
l
.
There
f
ore
,
w
e
c
a
n
co
ncl
u
de
t
ha
t
the
ra
n
d
o
miza
ti
o
n
e
x
p
e
rim
e
nt
a
s
m
u
c
h
as
5
0
0
t
i
m
es,
1,000
tim
es,
and
10,0
0
0
tim
es n
ot a
ffe
c
t
to m
u
c
h
t
h
e
oc
c
u
rre
nce
per
cen
tage
of
an
im
als
tha
t
w
e
r
e random
i
zed.
Ta
ble
2.
P
ercenta
ge
o
f Anim
als Oc
curr
ence
s
in 5
00,
1
,00
0
,
a
nd
1
0
,
00
0 t
i
m
e
s
ra
ndomi
z
a
t
i
o
n
An
i
m
al
N
ame
P
e
r
cen
t
a
g
e
Occu
r
r
e
n
c
e
s
Nu
m
b
er
o
f
R
a
ndo
m
i
z
a
t
i
o
n
K
a
n
goroo
24.
6%
500
Tim
e
s
S
h
e
l
du
c
k
25.
6%
Ec
hidna
s
24.
8%
L
y
r
e
bird
25%
K
a
n
goroo
24.
2%
1,
000
Tim
e
s
S
h
e
l
du
c
k
24.
5%
Ec
hidna
s
25.
7%
L
y
r
e
bird
25.
6%
K
a
n
goroo
25.
24%
10,
000
Tim
e
s
S
h
e
l
du
c
k
24.
85%
Ec
hidna
s
25.
24%
L
y
r
e
bird
24.
67%
F
i
gure
8
sh
ow
s
the
pe
rce
n
t
a
ge
o
ccurr
ence
r
esul
t
s
f
rom
t
h
re
e
var
i
a
nt
s
of
r
an
do
mi
z
a
t
i
on,
w
h
e
re
w
e
ca
n
see
t
h
e
Re
d
L
i
ne
i
s
a
l
m
o
s
t
s
trai
gh
t.
T
his
pr
o
v
es
t
hat
t
h
e
F
i
s
he
r-Ya
t
e
s
a
l
go
ri
t
h
m
coul
d
g
e
n
e
ra
te
perm
uta
t
i
o
ns
w
hi
c
h
g
iv
in
g
almos
t
t
he
s
a
m
e
poss
i
bi
l
i
t
y
f
o
r
e
ac
h
sh
uf
fli
n
g
ti
me
w
i
t
h
out
b
e
i
n
g
in
fl
u
e
nce
d
by
the n
u
m
b
er
of
rand
om
izat
i
on
do
ne.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
2
5
2
-
88
22
I
J
ERE
Vol.
6, No.
3
, Se
pt
e
m
b
e
r
2017
: 198
– 206
20
4
F
i
gur
e
8.
I
m
a
ge
r
a
ndomiza
tio
n
r
e
sul
t
s
gr
a
ph
for
50
0,
1
,
0
0
0
,
and
10,
0
0
0
t
i
m
e
s
5.
2.
ARCS
s
co
res
T
o
kno
w
t
h
e
ac
ce
p
t
an
c
e
l
e
v
el
o
f
Z
o
o
Si
mu
la
t
o
r
an
d
i
t
s
e
ffe
ct
o
n
c
hil
d
re
n
l
e
a
r
n
i
ng
p
h
a
se,
a
su
rv
e
y
w
a
s
c
onduc
te
d
usi
n
g
A
R
CS
que
sti
o
n
n
a
i
r
e
.
I
t
h
a
s
b
e
e
n
u
s
e
d
b
y
m
a
n
y
re
se
arc
h
ers,
s
uc
h
as
M
a
l
i
k
[
2
2
]
w
ho
use
d
A
R
C
S
t
o
over
c
ome
non
c
om
ple
t
i
on
r
a
t
e
o
f
st
ude
n
t
s
in
d
ist
a
n
c
e
e
d
u
c
a
t
i
o
n
,
a
n
d
F
e
n
g
a
n
d
T
u
a
n
[
2
3
]
w
h
o
use
d
A
RCS
m
ode
l
to
p
r
o
m
o
t
e
1
1
th
g
r
a
der
s
’
mot
i
v
at
i
on
i
n
l
e
a
r
n
in
g
c
h
em
istr
y.
H
w
a
ng
e
t
a
l
.
[
2
4]
a
lso
s
t
ate
d
tha
t
d
ue
t
o
i
t
s
na
tur
e
t
o
pr
o
v
i
d
e
cha
l
l
e
n
g
in
g
tasks,
t
o
e
n
c
o
ur
a
ge
d
if
fer
e
n
t
l
eve
l
s
o
f
i
nter
ac
tio
n,
a
nd
t
o
p
r
o
vi
de
en
j
o
y
a
bl
e
mu
lt
i
m
e
d
i
a
a
n
d
i
n
st
ant
f
eedb
a
ck
,
c
o
mp
ut
er
g
a
m
e
s
h
a
v
e
th
e
pot
en
t
i
a
l
to
p
r
o
vid
e
s
tu
de
nt
s
with
d
eep
a
nd
m
eani
n
gf
u
l
l
e
a
r
n
in
g
e
x
pe
r
i
enc
e
s.
I
n
t
hi
s
r
e
sea
r
ch,
a
t
o
ta
l
of
3
2
par
t
ici
p
a
n
ts,
w
ho
a
r
e
ki
ds
w
ith
a
g
e
r
a
n
g
e
s
f
r
o
m
5
–
8
y
e
a
r
s
o
l
d
,
w
e
r
e
ga
the
r
ed
a
t
c
h
il
dr
en
p
lay
g
r
o
un
ds
a
nd
ma
ll
s.
W
e
use
d
t
hr
e
e
d
ev
ic
es
o
n
t
h
e
ev
al
u
a
tio
n
p
h
a
se
,
i
.
e.
S
a
m
sung
G
a
lax
y
M
e
g
a
6.
3
,
S
a
m
sung
G
r
a
nd
P
r
ime,
a
nd
X
i
a
o
m
i
R
edm
i
3
P
r
o
.
O
n
th
is
p
hase,
we
a
lso
c
o
n
d
u
cte
d
e
xper
i
m
e
nts
t
o
k
n
o
w
t
h
e
c
h
i
l
dr
e
n
l
ea
r
n
in
g
i
n
ter
e
s
t
u
sin
g
t
ext
b
o
o
k
a
n
d
u
si
ng
gam
e
,
i.
e
.
t
he
Z
o
o
S
im
u
l
a
t
or
,
a
nd
t
h
er
e
f
or
e
tw
o
ty
pes
of
q
u
e
st
io
n
n
air
e
s
w
e
r
e
g
ive
n
t
o
ea
ch
p
a
rt
ici
p
a
n
t.
B
a
se
d
on
t
he
c
alcu
la
t
i
o
n
o
f
the
f
i
r
s
t
q
u
es
t
i
on
na
ir
e
t
o
k
n
o
w
t
h
e
c
hi
l
d
r
e
n
l
e
arni
ng
i
nt
ere
s
t
us
ing
tex
t
bo
o
k
,
w
e
g
et
a
n
A
R
C
S
s
cor
e
o
f
2.
7
4
,
w
h
ic
h
w
a
s
qu
ite
g
oo
d.
T
her
e
for
e
w
e
ca
n
c
onc
l
ude
t
ha
t
t
e
xtb
o
o
k
usa
g
e
is
q
u
i
te
l
i
k
e
d
by
the
ch
il
dr
en
t
o
le
ar
n
a
n
i
m
al
s’
i
ntr
o
duc
ti
on
.
F
u
rt
he
rmo
r
e
,
b
ase
d
o
n
th
e
c
a
l
c
ul
ati
on
of
the
sec
o
n
d
que
st
i
o
n
n
a
i
r
e
t
o
know
t
he
c
hi
ldr
e
n
lea
r
n
i
n
g
i
nt
er
e
s
t
u
si
ng
g
a
m
e (
Z
oo S
i
m
u
l
a
tor
)
,
w
e
ge
t
a
sc
or
e
o
f
4.
18
o
u
t
of
5
.
I
t
m
e
a
ns
t
hat
t
h
e
gam
e
u
sa
ge
i
s
l
i
ke
d
b
y
t
h
e
c
hi
l
d
r
e
n
t
o
l
ea
r
n
a
n
i
m
a
ls’
i
n
tr
od
uc
ti
o
n
.
F
i
gur
e
9
show
s
a
r
e
su
lt
gr
ap
h
f
r
o
m
t
h
e
fi
na
l
c
o
un
t
i
n
g
of
A
RCS
q
ue
st
io
n
n
a
ir
e
r
e
ga
r
d
i
ng
the
a
n
im
al
i
n
t
r
o
d
u
c
t
io
n
usi
n
g
tex
t
bo
o
k
a
nd
g
a
m
e
(
Zoo
S
i
mula
t
o
r
)
m
e
tho
d
.
I
t
c
a
n
be
c
on
c
l
ude
d
t
ha
t
the
in
tro
d
u
ct
i
on
m
e
tho
d
u
s
i
ng
t
h
e
Z
o
o
S
i
mulat
o
r
i
s
m
ore
exc
iti
n
g
the
c
h
i
l
dre
n
's
i
n
t
er
est.
T
his
find
i
n
g
s
i
n
l
i
ne
w
it
h
othe
r
r
e
sults
f
r
o
m
othe
r
r
e
sea
r
che
r
s,
a
s w
e
c
an
s
e
e
on
the
w
o
r
k
s
of
P
r
i
ns
e
t
al.
[25]
,
R
osas
e
t
al.
[2
6]
,
a
nd
Bai
e
t
a
l
.
[27]
.
Fi
g
u
r
e
9
.
G
ra
p
h
i
c c
o
mp
a
r
i
s
o
n
b
e
t
we
en
Ga
m
e a
n
d
Te
xt
book
me
t
h
od
Evaluation Warning : The document was created with Spire.PDF for Python.
IJERE
I
S
S
N
:
2252-
88
22
Z
oo Sim
u
l
a
tor
t
o
Incre
a
se
C
h
ildre
n
L
e
arn
i
n
g
Ph
ase
(Re
n
d
y
)
20
5
6.
CONCL
U
S
ION
Base
d
o
n
the r
ese
a
rc
h t
h
at ha
s
bee
n d
one,
w
e
c
an c
o
n
c
l
u
d
e
t
h
a
t
Z
oo S
i
m
u
lat
o
r
as
a
m
edi
a
o
f
a
n
im
a
l
s
in
t
r
od
uc
ti
on
usin
g
F
i
she
r-Y
a
t
es
s
h
u
ffl
e
a
l
go
rit
h
m
has
bee
n
s
ucc
e
ssfu
lly
d
e
s
igne
d
a
nd
b
u
il
t
u
s
i
n
g
U
n
i
t
y3D
.
The
gam
e
bui
l
t
h
a
s
a
r
esc
u
e
feat
ure
wit
h
t
wo
d
iffer
e
n
t
p
uzz
l
e
t
yp
e
s
,
no
tif
i
c
ati
o
n
f
eatu
r
e
t
o
r
emi
n
d
p
l
a
y
e
r
s
tha
t
t
her
e
i
s
a new
inc
o
mi
n
g
m
e
s
sa
ge,
foo
d
bu
tto
n
tha
t
w
i
l
l
m
a
k
e
i
t
e
a
s
ie
r
to
c
a
s
t i
n
t
h
e
a
n
i
m
a
l
'
s
c
a
g
e
t
h
a
t a
r
e
hu
n
g
ry
t
o
be
f
e
d
,
m
i
ni
g
am
e
s
f
e
a
t
u
re
t
ha
t
c
a
n
be
u
sed
to
g
e
t
a
d
dit
i
o
n
a
l
c
oi
ns,
me
nu
c
r
edi
t
w
h
i
c
h
w
il
l
fea
t
u
r
e
all
i
ndi
v
i
dua
ls
a
ssoc
i
a
t
ed
w
i
t
h
ar
ch
it
e
c
t
ure
of
t
he
g
am
e,
a
nd
a
ni
ma
l
in
fo
f
ea
tu
re
t
h
a
t
wi
ll
d
i
s
pl
ay
a
b
rief
in
form
ation
of
a
nim
a
ls
w
ith
i
t
s
p
i
c
t
u
r
e
.
The
use
of
g
a
m
e
m
e
tho
d
h
as
b
een
s
how
n
t
o
i
ncre
ase
i
n
ter
e
st
i
n
c
h
ild
re
n
l
e
arni
n
g
ph
as
e
co
mp
are
t
o
t
e
x
tb
ook
m
e
t
h
o
d
.
T
h
e
re
i
s
an
i
ncre
as
em
ent
from
2
.
74
t
o
4
.1
8
a
f
te
r
game
me
tho
d
i
mp
le
m
e
nted
b
a
s
ed
on AR
C
S
in
t
ere
s
t
me
asure
m
ent
sc
ore
.
The
r
e
are
a
l
so
s
ome
sug
g
es
t
i
ons
f
or
f
u
t
ure
resea
r
che
s
,
i
.
e.
p
er
f
o
rma
n
ce
p
art
s
can
b
e
e
n
h
a
n
c
ed
,
so
tha
t
t
he
l
a
g
c
a
u
se
d
by
t
h
e
c
o
lli
der
on
t
h
e
m
o
v
i
n
g
o
b
j
ec
t
c
a
n
be
r
e
duce
d
.
Mor
e
o
v
er,
sati
sfac
t
i
o
n
f
ac
tor
on
t
h
e
que
st
ion
n
a
i
r
e
o
n
the
me
asur
em
ent
o
f
i
nter
est
us
i
ng
t
h
e
g
a
m
e
g
e
t
t
he
s
ma
l
l
e
s
t
va
lue
com
p
a
r
e
d
t
o
t
h
e
o
t
her
f
a
c
t
o
r
s. Th
e
se
f
a
c
to
rs
r
el
at
ed
t
o
s
a
ti
sf
acti
o
n
,
s
o
t
h
e
addi
tio
n
of cha
llen
g
e
a
nd
di
ffic
ul
t
y
el
e
me
nt
s in gam
es c
an
be
c
o
n
side
re
d.
T
he
a
w
a
rd
g
rant
t
o
t
h
e
p
l
a
y
e
r
a
ls
o
c
a
n
g
i
ve
s
a
t
i
sfa
c
t
io
n
a
n
d
mot
i
va
ti
on
in
o
rder
t
o
ke
ep
pla
y
in
g
.
REFE
RENCES
[1]
S
.
H
artati
, “L
earn
i
n
g
D
evel
opme
n
t
o
n
T
od
d
l
ers,
”
Depd
ik
nas,
J
ak
a
rta, 20
0
5
.
[2]
B. Hu
r
lock
, “Ph
ysco
l
o
gy
o
f Develop
m
en
t,” Er
l
a
n
g
g
a
,
Jak
a
rt
a, 20
0
6.
[3]
M
.
M
alt
z
,
“
T
he M
ag
ic
P
ow
er
o
f
S
e
lf
I
m
a
ge
P
h
y
scol
og
y,
”
Mitra U
t
a
m
a
,
J
a
kar
t
a, 19
9
6
.
[4]
D.
K
as
du,
“
S
m
a
r
t
Child
r
en,
”
P
usap
S
wara,
pp.
143,
2
0
04.
[5]
P
.
R
osy
a
d,
“
An
im
al
I
ntro
duct
i
o
n
u
sin
g
A
u
g
m
e
nt
ed
R
ealit
y
Based
o
n
An
droi
d,
”
Th
e
s
is
,
Uni
v
ersit
a
s
M
u
h
a
mm
adiy
ah S
u
r
akarta,
20
14.
[6]
A.
R
izk
y
,
“
D
ev
elop
m
e
n
t
o
f
Anim
al
I
ntrod
u
ctio
n
Mag
i
c
Boo
k
A
p
p
li
c
atio
n
f
o
r
Toddl
ers
usin
g
A
u
g
m
ented
Real
ity,
”
Th
e
s
is
,
Un
ik
o
m
,
201
3.
[7]
D.
R
i
g
as
a
nd
A
y
ad
,
“
A
n
Em
p
i
rical
I
n
v
es
ti
gati
on
on
E
f
f
ecti
v
en
es
s
o
f
Gam
e
-bas
ed
L
earn
i
n
g
,”
R
e
cent A
d
va
nces i
n
So
ft
ware
Engin
e
eri
ng,
Para
ll
el,
a
n
d
Dist
ri
bu
ted Syst
em
, p
p.
2
24
-22
7
, 2
01
0.
[8]
J.
E
.
K
e
mp
a
nd
D.
K
.
D
a
yt
on
,
“
P
l
a
nni
ng
a
n
d
P
rodu
cti
n
g
Instructi
on
al
M
ed
ia,”
H
arp
e
r
&
Row
P
u
b
l
i
s
h
e
r,
N
ew
York
, 19
8
5
.
[9]
A.
C
hev
t
chen
ko
,
“
G
amified
E
ducatio
n:
I
ntrod
u
cing
G
am
e
Elem
e
n
ts
i
n
to
t
he
S
choo
l
En
virom
e
nt
t
o
E
n
h
a
nce
S
t
ud
e
t
M
o
tivatio
n an
d Perf
o
r
m
a
nce,”
The
s
is
, E
rasm
us U
niv
e
rsi
t
y
Rotte
rdam
,
N
et
herland,
201
3.
[10]
I.
G
lo
ver,
“
Play
a
s
Y
o
u
L
earn:
G
am
ificati
o
n
as
T
echn
i
qu
es
f
or
M
ot
ivatin
g
Learners
,
”
i
n
Wor
ld
Co
nfe
r
e
n
c
e
on
Educat
ional
M
u
ltimedi
a
,
Hype
rm
edia and
Tel
ecommunication
s
, V
ict
o
ria,
BC, Canad
a, 2
013
.
[11]
A.
A
in
u
l
,
“Im
p
le
me
nta
tio
n
o
f
S
i
m
ula
t
ion
Ga
me
M
e
t
ho
d
on
S
ub
je
c
t
s
t
o
Im
p
r
ov
e
Stu
d
y
Resu
lt
a
n
d
Le
a
r
ning
Motivation of S
tudents,”
Th
e
s
i
s
, U
ni
vers
i
t
as Negeri S
e
m
b
ilan
, 2
0
1
2.
[12]
W.
Y
eni,
“
Imp
l
e
m
en
tation
of
Q
uest
E
du
cati
on
Gam
e
w
it
h
W
h
o
W
a
nts
t
o
be
a
M
i
llionai
rre
t
he
me
f
or
Element
a
r
y
Stud
e
n
ts,
”
Th
e
s
i
s
,
Un
iv
ers
i
t
a
s
N
u
s
a
nt
ara P
G
RI, 2
01
6.
[13]
E.
B
enders
ky
,
“Th
e
I
nt
u
iti
on
beh
i
n
d
F
isher-Y
ates
S
hufflin
g,
”
20
10.
[14]
I.
H
adita
ma,
et
a
l
.,
“
Fish
er-Y
ates
a
n
d
F
uzzy
T
su
kam
o
t
o
I
m
p
l
e
me
n
t
at
io
n
on
Q
u
i
z
G
a
m
e
T
e
bak
N
a
da
S
und
a
Bas
e
d
on Android
,
”
JO
IN
,
v
o
l
/
i
s
su
e:
1
(
1
), p
p.
51
-
58
,
20
16
.
[15]
R.
N
ug
ra
ha
,
et a
l
.
,
“Im
p
lem
e
n
t
ati
o
n
of
F
is
h
e
r-Y
ates
A
lg
orithm
o
n
t
he
L
o
s
t
Ins
ect
Ap
p
l
icat
io
n
f
o
r
In
se
cts
Int
r
odu
cti
on
Based
on
U
nit
y
3
D,”
20
12.
[16]
A.
F
arisi,
“
Com
p
ari
s
on
A
nalysi
s
of
F
i
s
h
e
r-Yates
S
huff
l
e
and
Nai
ve
S
hu
ffle
A
lgo
r
ith
m
s
,
”
Thesi
s
,
Universi
tas
In
do
ne
sia
,
2
01
5
.
[17]
J. Atwoo
d, “Th
e Dang
er of
Naivete,”
200
7.
[18]
E.
B
enn
y
a
nd
Y
us
kar,
“
M
o
tiv
ation
Effect
o
n
Ac
co
un
ti
ng
S
t
udents
Interes
t
t
o
E
n
ro
ll
P
end
i
dik
a
n
Prof
esi
Aku
n
t
a
nsi
(PPA)
,
”
i
n
S
i
mp
osiu
m Na
sio
n
a
l
Ak
un
ta
ns
i
9
, Pa
d
an
g, In
d
o
n
esi
a
,
2
0
0
6
.
[19]
D. K.
S
u
k
a
rdi
, “C
a
reer Cou
nseli
n
g in
Sch
oo
ls,” Balai
P
u
s
t
a
k
a
,
J
ak
ar
t
a
,
1
9
8
7
.
[20]
J.
K
eller,
“W
h
a
t
Is
M
o
ti
vati
on
a
l
D
esi
g
n
?
”
20
06.
[21]
L.
M
.
S
i
h
a
loh
o
,
“
E
ff
ecti
v
en
ess
of
5
E
Cycl
e
Learn
i
ng
M
od
el
i
n
Im
pro
v
i
n
g
L
e
a
rning
Mo
tiva
tio
n
a
n
d
Co
nc
e
p
t
M
a
st
e
r
y
o
n
A
cid-Bas
e
s S
u
bj
ect,”
The
s
i
s
,
Un
iv
e
r
si
ta
s
L
a
mpu
n
g
,
20
1
3
.
[22]
S
.
M
alik,
“
E
ff
ecti
v
en
ess
o
f
A
RCS
M
o
d
e
l o
f
M
o
t
iv
atio
nal
Desig
n
t
o O
v
erco
me
N
o
n
Co
m
p
l
etio
n Rat
e
of
S
t
ud
ents in
Di
s
t
ance Ed
ucat
io
n,”
T
u
rk
i
s
h
On
li
ne Jo
urn
a
l o
f
Dist
an
ce Ed
uca
t
ion
,
vol/is
sue:
15(
2),
pp. 194-200,
2
014.
[23]
S
.
L
.
F
e
n
g
a
n
d
H
.
L
.
T
u
a
n
,
“
U
s
i
n
g
A
R
C
S
M
o
d
e
l
t
o
P
r
o
m
o
t
e
1
1
th
G
rad
e
rs’
M
o
tiv
a
t
i
on
and
Ach
i
evem
en
t
i
n
Learn
i
ng
ab
out
A
c
i
ds
and
Bases,
”
In
tern
a
t
io
nal
Jo
ur
na
l of S
c
ience an
d M
a
t
h
emati
c
s E
d
u
c
ation,
vol
/i
ss
ue:
3(3
)
,
pp.
46
3-4
84,
2
0
0
5
.
[24]
G.
J
.
Hwang,
et a
l
.,
“
A
C
o
n
cep
t
M
a
p-E
m
bedd
ed
E
du
catio
nal
Co
m
p
uter
G
am
e
f
o
r
Im
pro
v
i
n
g
S
t
u
d
e
nt
s’
L
e
a
rn
in
g
P
e
rf
orm
a
nce i
n
Natu
r
al S
ci
ence Co
urses
,
”
Co
mp
ute
r
s &
Ed
uc
a
t
i
o
n
, vo
l
.
69
,
pp
. 1
21
-1
30
,
2
0
1
3
.
[25]
P.
J
.
M.
P
rin
s
,
e
t
a
l
.,
“
D
oes
Co
m
p
u
t
eri
zed
W
o
r
ki
ng
M
e
m
o
r
y
Train
i
ng
w
i
t
h
Gam
e
E
l
e
m
e
nt
s
E
nhan
ce
M
o
t
i
vat
i
on
and
Trai
ni
ng
Effi
cacy
i
n
Ch
il
dr
en
w
i
t
h
ADHD
?”
Cyber
p
sych
ol
o
g
y,
Beh
a
vi
or,
a
n
d
So
cial
Ne
tworki
ng
,
v
o
l
/
i
s
s
u
e
:
14
(3),
p
p.
1
1
5
-122,
2
0
1
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
2
5
2
-
88
22
I
J
ERE
Vol.
6, No.
3
, Se
pt
e
m
b
e
r
2017
: 198
– 206
20
6
[26]
R.
R
os
as
,
et
a
l
.
,
“
B
ey
ond
N
intend
o:
D
esig
n
and
Asses
s
m
e
nt
o
f
E
ducat
io
nal
Vi
d
e
o
G
a
mes
f
o
r
First
and
Second
G
r
ade S
t
uden
t
s
,
”
Comp
ute
r
s
&
Ed
uc
a
tion
,
v
o
l.
4
0,
pp.
7
1
-
94
,
2003
.
[27]
H.
B
a
i
,
et
a
l
.,
“Ass
essin
g
t
h
e
E
ff
ecti
v
en
ess
of
a
3
-D
I
ns
tru
c
ti
ona
l
Gam
e
o
n
Imp
rov
i
n
g
M
ath
e
matics
Achi
evem
en
t
an
d
M
o
t
i
vatio
n
of
M
id
dl
e
S
c
h
ool
S
tud
e
nt
s,
”
British Journal of E
d
uc
at
ional Technology,
v
ol/is
sue:
4
3
(
6),
pp
.
99
3
-
10
03
, 20
1
2
.
BIOGRAPHI
E
S
OF
AUT
HORS
Rendy
l
ives
i
n
Tan
g
eran
g,
I
n
d
o
n
es
ia.
H
e
g
rad
u
ated
f
ro
m
U
n
ivers
i
t
a
s
M
u
l
t
im
e
d
ia
N
us
a
n
ta
r
a
(UM
N
)
an
d
con
f
erred
a
B
ach
elo
r
D
egre
e
i
n
C
o
m
p
u
ter
S
c
i
e
nce
(S
.Ko
m
.
)
.
H
i
s
i
n
t
e
r
e
s
t
s
i
n
g
a
m
e
tech
nol
og
y,
i
nteract
iv
e
t
e
c
h
no
lo
gy
,
w
e
b
dev
e
lop
m
ent
i
n
c
l
udi
ng
w
eb
a
pp
li
catio
n
and
E
-
Learni
ng
so
ftware
d
ev
elo
p
m
e
nt
,
m
a
de
h
i
m
s
tan
douts
his
thes
is
r
es
earch.
H
e
w
a
s
als
o
r
ec
ogn
ized
e
x
c
el
i
n
C
o
m
p
u
t
e
r
G
r
a
p
h
i
c
s
a
n
d
A
n
i
m
a
t
i
o
n
,
a
l
s
o
M
o
b
i
l
e
P
r
o
g
r
a
m
m
i
n
g
.
H
e
’
s
work
in
g
in
a
n
ind
i
e
ga
me
st
udio
an
d
al
ready
pu
bli
s
h
e
d
s
e
veral
mo
bile
g
am
es
i
n
ap
pli
catio
n
portal
like
G
o
ogle
P
l
a
yStore
and
Ap
ple S
t
ore.
M
a
rc
el
Bo
n
ar K
ri
st
and
a
li
v
es
i
n
J
a
karta, Ind
ones
i
a.
He recei
ved
in
Bachel
or D
egre
e i
n
Co
m
pu
t
e
r
Sc
ie
n
c
e
(S.Kom
)
fro
m
U
nive
rs
ita
s
Mu
l
t
ime
d
ia
N
usantara,
Tan
g
eran
g
,
B
an
ten,
i
n
201
1
and
M
a
ster of
S
c
i
e
n
c
e i
n
In
f
orm
a
ti
on
M
anag
em
e
n
t from
Chi
n
es
e Cultur
e Un
iv
ersit
y
,
Ta
i
p
ei,
Tai
w
an
,
in
2
015
.
F
r
om
201
1,
h
e
beg
a
n
hi
s
caree
r
in
u
ni
vers
ity
as
A
ss
ist
ant
Lecturer,
un
till
h
e
came
back
f
r
o
m
h
is
m
ast
e
r
st
ud
y
an
d
b
ecom
e
L
ectu
r
e
r
i
n
th
e
Com
p
ut
er
S
cien
ce
Dep
a
rtm
e
nt
,
U
n
i
v
ersitas
M
u
ltim
e
d
i
a
Nusant
ara.
T
hen
,
h
e
w
a
s
en
tru
s
t
e
d
t
o
l
ead
L
earn
i
n
g
C
e
n
te
r
De
pa
r
t
me
n
t
i
n
20
16
,
a
n
d
f
o
cus
e
d
i
n
d
evelop
in
g
E
-
Learni
n
g
P
la
tf
orm
and
Dev
e
lo
pm
ent.
H
is
researches
a
re
b
as
ed
o
n
h
i
s
interests
in
m
obile
t
ech
no
log
y
,
mo
bi
le
a
pp
licat
ion
development
,
w
eb
d
ev
elo
p
m
e
nt
a
nd
s
o
ftw
a
re
eng
i
neeri
n
g
.
H
is
e
xt
ens
i
ve resarches
can be seen i
n sev
e
ral
p
u
b
lis
h
ed
p
apers in
b
o
t
h
nat
i
o
n
al
a
nd
international jou
r
nals
a
nd
conferences.
S
e
ng
H
a
ns
un
lives
i
n
Tan
g
eran
g,
I
n
don
esi
a
.
He
r
eceiv
e
d
t
h
e
Bc.
deg
r
ee
i
n
M
at
hem
a
ti
cs
(
S.Si
.)
fro
m
U
n
i
v
e
rsita
s
Ga
dja
h
M
a
d
a
,
Y
og
ya
k
a
rta
,
i
n
20
08
a
nd
M
.
C
s.
d
e
g
rees
i
n
Comp
ut
er
S
cien
ce
f
r
o
m
t
he
s
am
e
un
iv
ersity,
Universi
tas
Gad
j
ah
M
ada,
Y
og
yak
a
rt
a,
i
n
201
1.
S
ince
20
11
,
h
e
h
as
been
a
L
ectu
r
er
w
ith
t
h
e
C
o
m
pu
ter
S
c
i
e
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.
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research
interests
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tech
nol
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y.
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