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-
b
ased
lear
n
in
g
p
latf
o
r
m
s
to
en
h
an
ce
s
tu
d
en
t
en
g
ag
em
en
t
in
h
ig
h
e
r
ed
u
ca
tio
n
.
An
o
t
h
er
s
tu
d
y
b
y
Glig
o
r
ea
et
a
l
.
[
6
]
r
ev
iewe
d
tr
en
d
s
in
th
e
u
s
e
o
f
AI
ac
r
o
s
s
v
ar
io
u
s
ed
u
ca
tio
n
al
s
ec
to
r
s
,
h
ig
h
lig
h
tin
g
th
e
ad
ap
tab
ilit
y
o
f
A
I
tech
n
o
lo
g
y
to
s
u
p
p
o
r
t
a
d
ap
ti
v
e
lear
n
in
g
.
Me
an
wh
ile,
Dim
itria
d
o
u
a
n
d
L
an
itis
[
7
]
em
p
h
asized
th
at
teac
h
er
tr
ain
in
g
in
th
e
u
s
e
o
f
AI
tech
n
o
lo
g
y
is
a
k
ey
f
ac
to
r
in
th
e
s
u
cc
ess
f
u
l
in
teg
r
atio
n
o
f
AI
in
class
r
o
o
m
s
.
As
AI
tech
n
o
lo
g
y
co
n
ti
n
u
es
to
ev
o
lv
e
r
ap
id
ly
,
s
o
t
o
o
d
o
es
th
e
d
e
m
an
d
f
o
r
n
ew
s
tr
ateg
ies
to
o
p
tim
ize
its
u
s
e
in
th
e
class
r
o
o
m
[
8
]
.
T
h
er
e
f
o
r
e,
th
i
s
s
tu
d
y
aim
s
to
ex
p
lo
r
e
h
o
w
AI
ca
n
b
e
u
tili
ze
d
to
im
p
r
o
v
e
d
ig
ital
lear
n
in
g
s
tr
ateg
ies
in
th
e
Dep
a
r
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
.
T
h
is
r
esear
ch
f
o
cu
s
es
o
n
an
al
y
zin
g
cu
r
r
en
t
tr
en
d
s
an
d
p
r
o
p
o
s
in
g
p
r
ac
tical
s
o
lu
ti
o
n
s
f
o
r
b
etter
im
p
lem
e
n
tatio
n
.
T
h
is
s
tu
d
y
o
f
f
er
s
a
n
o
v
el
co
n
t
r
ib
u
tio
n
b
y
f
o
c
u
s
in
g
o
n
th
e
o
p
tim
izatio
n
o
f
AI
-
b
ased
d
ig
it
al
lear
n
in
g
s
tr
ateg
ies
in
th
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
,
an
ar
ea
th
at
h
as
b
ee
n
r
elativ
ely
u
n
ex
p
lo
r
e
d
in
p
r
io
r
r
esear
ch
[
9
]
–
[
1
1
]
.
W
h
ile
p
r
e
v
io
u
s
s
tu
d
ies,
s
u
ch
as
Alm
u
s
ae
d
et
a
l
.
[
5
]
,
h
av
e
h
ig
h
lig
h
t
ed
AI
'
s
p
o
ten
tial
to
en
h
an
ce
s
tu
d
e
n
t
en
g
ag
em
en
t
,
an
d
Glig
o
r
ea
et
a
l
.
[
6
]
,
h
a
v
e
r
ev
iewe
d
AI
u
s
ag
e
tr
en
d
s
i
n
th
e
ed
u
ca
tio
n
s
ec
to
r
,
th
eir
ap
p
r
o
ac
h
es
ten
d
to
b
e
g
en
er
al
an
d
d
o
n
o
t
ad
d
r
ess
th
e
s
p
ec
if
ic
n
ee
d
s
o
f
th
e
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
d
is
cip
lin
e.
Fu
r
th
er
m
o
r
e,
Dim
itria
d
o
u
a
n
d
L
an
itis
[
7
]
em
p
h
a
s
ized
th
e
im
p
o
r
tan
ce
o
f
teac
h
er
tr
ain
in
g
as
a
k
ey
f
ac
to
r
in
th
e
s
u
cc
ess
f
u
l
in
teg
r
atio
n
o
f
AI
.
Ad
d
r
ess
in
g
th
es
e
g
ap
s
,
th
is
r
esear
ch
d
e
v
elo
p
s
a
f
r
am
ew
o
r
k
f
o
r
d
ig
ital
lear
n
in
g
s
tr
ateg
ies
th
at
lev
er
ag
e
AI
s
p
ec
if
ically
to
i
m
p
r
o
v
e
lear
n
in
g
o
u
tc
o
m
es,
o
v
er
co
m
e
ed
u
ca
to
r
s
'
lim
ited
u
n
d
e
r
s
tan
d
in
g
,
an
d
m
ax
im
ize
th
e
u
s
e
o
f
ad
a
p
tiv
e
te
ch
n
o
lo
g
ies
s
u
ch
as
p
er
s
o
n
aliz
ed
lear
n
i
n
g
s
y
s
tem
s
an
d
a
u
to
m
ated
ass
ess
m
en
t
to
o
ls
[
3
]
,
[
1
2
]
.
T
h
u
s
,
t
h
is
s
tu
d
y
n
o
t
o
n
l
y
p
r
o
v
id
es
in
n
o
v
ativ
e
s
o
lu
tio
n
s
to
in
ter
n
al
an
d
e
x
ter
n
al
c
h
allen
g
es
b
u
t
a
ls
o
co
n
tr
ib
u
tes
to
t
h
e
en
h
an
c
em
en
t
o
f
h
i
g
h
er
ed
u
ca
ti
o
n
q
u
ality
an
d
g
r
a
d
u
ates'
r
ea
d
in
ess
to
m
ee
t th
e
d
em
an
d
s
o
f
AI
-
d
r
iv
en
i
n
d
u
s
tr
ies
[
1
3
]
–
[
1
5
]
.
T
o
ad
d
r
ess
th
is
g
ap
,
th
is
s
tu
d
y
in
tr
o
d
u
ce
s
a
co
n
tex
t
-
s
p
ec
if
ic
an
d
em
p
ir
ically
g
r
o
u
n
d
e
d
s
tr
ateg
ic
f
r
am
ewo
r
k
f
o
r
o
p
tim
izin
g
AI
-
in
teg
r
ated
d
ig
ital
lear
n
in
g
in
th
e
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
cu
r
r
icu
lu
m
,
r
esp
o
n
d
in
g
to
th
e
lack
o
f
ac
tio
n
ab
le
m
o
d
els
th
at
tr
an
s
late
AI
ad
o
p
tio
n
in
to
co
n
cr
ete
cu
r
r
icu
lar
an
d
p
ed
ag
o
g
ical
p
r
ac
tices
in
I
s
l
am
ic
h
ig
h
e
r
e
d
u
ca
tio
n
[
1
6
]
,
[
1
7
]
.
T
h
e
p
r
in
cip
al
co
n
tr
i
b
u
tio
n
lies
in
th
e
d
ev
elo
p
m
e
n
t
o
f
a
s
tr
en
g
th
s
,
wea
k
n
ess
es,
o
p
p
o
r
t
u
n
ities
,
an
d
th
r
ea
ts
(
SW
OT
)
-
b
ased
(
in
te
r
n
al
f
ac
to
r
an
aly
s
is
s
u
m
m
ar
y
(
I
FAS
)
–
ex
ter
n
al
f
a
cto
r
an
al
y
s
is
s
u
m
m
ar
y
(
E
F
AS)
)
s
tr
ateg
ic
m
o
d
el
th
at
s
y
s
tem
atica
lly
alig
n
s
in
ter
n
al
in
s
titu
tio
n
al
r
ea
d
in
es
s
with
ex
ter
n
al
o
p
p
o
r
tu
n
ities
,
en
ab
lin
g
tar
g
eted
,
s
u
s
tain
ab
le,
an
d
s
ca
lab
le
AI
in
teg
r
atio
n
b
ey
o
n
d
ad
h
o
c
tech
n
o
lo
g
ical
im
p
lem
en
tatio
n
[
1
8
]
,
[
1
9
]
.
B
y
o
p
er
atio
n
alizin
g
AI
-
b
ased
to
o
ls
s
u
ch
as
ad
ap
tiv
e
lear
n
in
g
s
y
s
tem
s
,
au
to
m
ated
ass
ess
m
en
ts
,
an
d
in
tellig
en
t
tu
to
r
in
g
,
th
is
f
r
a
m
ewo
r
k
p
r
o
v
i
d
es
a
r
o
b
u
s
t
p
ath
way
f
o
r
en
h
an
ci
n
g
p
er
s
o
n
aliza
tio
n
,
ed
u
ca
tio
n
al
q
u
ality
,
an
d
in
s
titu
tio
n
a
l
co
m
p
etitiv
en
ess
,
p
ar
ticu
lar
ly
with
in
s
tate
I
s
lam
ic
r
elig
io
u
s
u
n
i
v
er
s
ities
o
r
p
er
g
u
r
u
a
n
tin
g
g
i
ke
a
g
a
ma
a
n
is
la
m
n
eg
eri
(
PTKI
N)
i
n
f
o
r
m
atics
-
r
elate
d
p
r
o
g
r
am
s
[
2
0
]
–
[
2
2
]
.
T
h
e
co
n
tr
ib
u
tio
n
o
f
th
is
r
esear
ch
lies
in
its
n
o
v
el
ap
p
r
o
ac
h
to
co
m
b
in
in
g
AI
tec
h
n
o
lo
g
y
with
d
ig
ital
lear
n
in
g
s
tr
ateg
ies
s
p
ec
if
ically
tailo
r
ed
t
o
th
e
n
ee
d
s
o
f
in
f
o
r
m
atics
en
g
in
ee
r
in
g
s
tu
d
en
ts
.
W
h
ile
p
r
ev
io
u
s
s
tu
d
ies
h
av
e
ex
p
lo
r
ed
th
e
ap
p
licatio
n
o
f
AI
in
ed
u
ca
tio
n
m
o
r
e
b
r
o
a
d
ly
,
f
ew
h
av
e
f
o
cu
s
ed
o
n
th
e
u
n
iq
u
e
r
eq
u
ir
em
e
n
ts
o
f
tech
n
ical
p
r
o
g
r
am
s
.
B
y
p
r
o
v
i
d
in
g
clea
r
s
tr
a
teg
ies
f
o
r
in
teg
r
atin
g
AI
with
i
n
th
e
co
n
tex
t
o
f
th
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
,
th
is
s
tu
d
y
aim
s
to
s
et
a
p
r
ec
ed
en
t
f
o
r
f
u
tu
r
e
ad
v
an
ce
m
en
ts
i
n
ed
u
ca
tio
n
al
tech
n
o
lo
g
y
.
Fu
r
th
er
m
o
r
e,
th
is
r
esear
ch
will
o
f
f
e
r
v
alu
ab
le
in
s
ig
h
ts
f
o
r
ed
u
ca
to
r
s
an
d
in
s
titu
tio
n
s
s
ee
k
in
g
to
o
p
tim
ize
th
eir
d
ig
i
tal
lear
n
in
g
en
v
i
r
o
n
m
e
n
ts
to
b
etter
p
r
e
p
ar
e
s
tu
d
en
ts
f
o
r
th
e
r
ap
id
ly
ev
o
lv
in
g
d
em
an
d
s
o
f
th
e
jo
b
m
ar
k
et.
2.
M
E
T
H
O
D
T
h
is
s
tu
d
y
a
d
o
p
ts
a
q
u
alitativ
e
r
esear
ch
a
p
p
r
o
ac
h
u
s
in
g
S
W
OT
an
aly
s
is
to
f
o
r
m
u
late
s
tr
ateg
ies
f
o
r
o
p
tim
izin
g
AI
-
b
ased
d
ig
ital
l
ea
r
n
in
g
in
th
e
De
p
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
[
2
3
]
.
SW
OT
an
aly
s
is
is
em
p
lo
y
ed
to
s
y
s
tem
atica
lly
i
d
en
tify
i
n
ter
n
al
a
n
d
ex
ter
n
al
f
ac
to
r
s
th
at
in
f
lu
e
n
ce
AI
in
teg
r
atio
n
in
d
ig
ital
lear
n
in
g
e
n
v
ir
o
n
m
en
ts
,
en
a
b
lin
g
s
tr
ateg
ic
ev
alu
atio
n
r
ath
e
r
th
an
p
u
r
ely
tech
n
ical
ass
ess
m
en
t
[
2
4
]
.
Data
wer
e
co
llected
f
r
o
m
m
u
ltip
le
s
o
u
r
c
es
to
en
s
u
r
e
an
al
y
tical
r
ig
o
r
a
n
d
tr
ia
n
g
u
latio
n
.
T
h
e
p
r
im
ar
y
d
ata
we
r
e
o
b
tain
ed
th
r
o
u
g
h
in
-
d
ep
t
h
in
ter
v
iews
in
v
o
lv
in
g
1
5
r
esp
o
n
d
en
ts
,
co
n
s
is
tin
g
o
f
7
f
ac
u
lty
m
em
b
er
s
,
6
0
u
n
d
er
g
r
ad
u
ate
s
tu
d
en
ts
,
an
d
2
ac
ad
em
ic
a
d
m
in
is
tr
ato
r
s
s
elec
ted
u
s
in
g
p
u
r
p
o
s
iv
e
s
am
p
lin
g
b
ased
o
n
t
h
eir
d
ir
ec
t
in
v
o
lv
em
e
n
t
in
cu
r
r
icu
lu
m
d
ev
elo
p
m
en
t
an
d
d
ig
ital
lear
n
in
g
im
p
lem
e
n
tatio
n
[
2
5
]
.
Seco
n
d
a
r
y
d
ata
wer
e
g
ath
er
ed
th
r
o
u
g
h
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
S
tr
a
teg
ic
o
p
timiz
a
tio
n
o
f a
r
tifi
cia
l in
tellig
en
ce
d
ig
ita
l le
a
r
n
i
n
g
in
in
f
o
r
ma
tics
en
g
in
ee
r
in
g
(
A
a
n
A
n
s
o
r
i)
3001
in
s
titu
tio
n
al
d
o
cu
m
en
t
a
n
aly
s
is
,
in
clu
d
in
g
cu
r
r
icu
lu
m
g
u
id
el
in
es,
ac
ad
em
ic
p
o
licy
d
o
c
u
m
e
n
ts
,
an
d
lab
o
r
at
o
r
y
r
ep
o
r
ts
,
co
m
p
lem
en
ted
b
y
a
s
t
r
u
ctu
r
ed
liter
atu
r
e
r
e
v
iew
o
n
AI
ap
p
licatio
n
s
in
h
i
g
h
er
e
d
u
c
atio
n
[
2
6
]
.
T
h
e
q
u
alitativ
e
d
ata
wer
e
co
d
ed
an
d
ca
teg
o
r
ized
in
t
o
f
o
u
r
SW
OT
d
im
en
s
io
n
s
-
w
h
ich
wer
e
s
u
b
s
eq
u
en
tly
q
u
an
tifie
d
u
s
in
g
th
e
I
FAS
an
d
E
FAS
m
atr
ices.
E
ac
h
f
ac
to
r
was
ass
ig
n
ed
a
weig
h
t
b
ased
o
n
its
r
elativ
e
im
p
o
r
tan
ce
(
r
an
g
in
g
f
r
o
m
0
.
0
0
t
o
1
.
0
0
)
an
d
a
r
ati
n
g
r
ef
lectin
g
its
im
p
ac
t
(
1
=
v
er
y
wea
k
/p
o
o
r
t
o
4
=
v
er
y
s
tr
o
n
g
/ex
ce
llen
t)
[
2
7
]
,
[
2
8
]
.
T
h
e
weig
h
ted
s
co
r
e
s
wer
e
ag
g
r
eg
ated
to
p
r
o
d
u
c
e
o
v
er
all
I
FAS
an
d
E
FAS
s
co
r
es,
wh
ich
in
d
icate
th
e
d
ep
ar
tm
en
t
’
s
in
ter
n
al
r
e
ad
in
ess
an
d
ex
ter
n
al
s
tr
ateg
i
c
p
o
s
itio
n
.
Hig
h
er
E
FAS
s
co
r
es
s
ig
n
if
y
s
tr
o
n
g
er
ex
ter
n
al
o
p
p
o
r
tu
n
ities
r
elativ
e
to
th
r
ea
ts
,
wh
ile
I
FAS
s
co
r
es
r
ef
lect
in
ter
n
al
ca
p
ab
ilit
y
to
s
u
p
p
o
r
t
AI
-
b
ase
d
lear
n
in
g
[
2
9
]
.
I
n
a
d
d
iti
o
n
t
o
th
e
s
t
r
at
eg
ic
SW
O
T
a
n
a
ly
s
is
,
th
is
s
tu
d
y
p
r
o
p
o
s
es
an
d
e
v
al
u
at
es
a
c
o
n
ce
p
t
u
a
l
A
I
-
e
n
h
a
n
c
ed
d
i
g
i
tal
le
ar
n
i
n
g
f
r
a
m
ew
o
r
k
t
o
d
em
o
n
s
t
r
at
e
t
ec
h
n
i
ca
l
f
e
asi
b
il
it
y
.
T
h
e
f
r
am
ew
o
r
k
c
o
n
s
is
ts
o
f
th
r
e
e
la
y
e
r
s
:
i
)
a
d
at
a
la
y
e
r
c
o
n
ta
in
in
g
le
ar
n
i
n
g
m
ate
r
i
als,
s
tu
d
e
n
t
i
n
te
r
ac
ti
o
n
l
o
g
s
,
a
n
d
ass
ess
m
e
n
t
r
e
c
o
r
d
s
;
ii
)
an
i
n
t
e
lli
g
e
n
c
e
l
ay
e
r
i
n
c
o
r
p
o
r
a
ti
n
g
s
u
p
e
r
v
is
e
d
m
a
ch
in
e
lea
r
n
i
n
g
a
l
g
o
r
i
th
m
s
,
i
n
c
lu
d
i
n
g
d
e
cisi
o
n
tr
ee
s
a
n
d
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
s
(
SVM
)
,
to
m
o
d
el
s
t
u
d
e
n
t
l
ea
r
n
in
g
b
e
h
a
v
i
o
r
;
a
n
d
iii
)
a
n
a
p
p
li
ca
t
io
n
lay
e
r
t
h
at
d
eli
v
e
r
s
a
d
a
p
ti
v
e
l
ea
r
n
in
g
c
o
n
te
n
t
a
n
d
m
o
n
it
o
r
in
g
d
as
h
b
o
ar
d
s
f
o
r
s
tu
d
en
ts
an
d
le
ctu
r
er
s
[
3
0
]
–
[
3
2
]
.
T
o
ev
alu
ate
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
p
r
o
p
o
s
ed
AI
co
m
p
o
n
en
t,
a
s
im
u
latio
n
was
co
n
d
u
cted
u
s
in
g
an
o
n
y
m
ized
h
is
to
r
ical
ac
ad
em
ic
d
ata
f
r
o
m
6
0
u
n
d
er
g
r
ad
u
ate
s
tu
d
en
ts
.
T
h
e
m
ac
h
in
e
lear
n
in
g
m
o
d
els
wer
e
tr
ain
ed
an
d
test
ed
u
s
in
g
s
tan
d
ar
d
ev
al
u
atio
n
m
etr
ics,
in
cl
u
d
in
g
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e,
to
ass
ess
p
r
ed
ictio
n
ac
c
u
r
ac
y
,
alo
n
g
with
u
s
er
s
atis
f
ac
tio
n
s
u
r
v
e
y
s
to
m
ea
s
u
r
e
p
e
r
ce
iv
ed
c
o
n
ten
t
r
elev
an
ce
an
d
en
g
ag
em
e
n
t
[
3
3
]
–
[
3
5
]
.
T
h
e
r
e
s
u
lts
in
d
icate
an
im
p
r
o
v
em
en
t
o
f
ap
p
r
o
x
im
ately
1
5
–
2
0
%
i
n
lear
n
er
e
n
g
ag
em
e
n
t
an
d
co
n
ten
t
r
ele
v
an
ce
c
o
m
p
ar
ed
to
a
s
tatic
d
ig
ital
lear
n
in
g
m
o
d
el,
p
r
o
v
i
d
in
g
em
p
ir
i
ca
l
s
u
p
p
o
r
t
f
o
r
th
e
p
o
ten
tial
ef
f
ec
tiv
en
ess
o
f
th
e
p
r
o
p
o
s
ed
AI
-
b
ased
lear
n
in
g
s
tr
ateg
y
[
3
6
]
,
[
3
7
]
.
Ov
e
r
all,
t
h
e
m
eth
o
d
o
lo
g
ical
p
r
o
ce
s
s
in
teg
r
ates
q
u
alitativ
e
s
tr
ateg
ic
an
aly
s
is
with
lim
ited
em
p
ir
ical
ev
alu
atio
n
to
e
n
s
u
r
e
th
at
th
e
p
r
o
p
o
s
ed
AI
-
b
ased
d
ig
ital
lear
n
in
g
f
r
a
m
ewo
r
k
is
b
o
th
co
n
tex
tu
ally
g
r
o
u
n
d
ed
an
d
p
r
ac
tically
v
i
ab
le.
T
h
is
a
p
p
r
o
ac
h
en
ab
les
th
e
f
o
r
m
u
latio
n
o
f
ev
i
d
en
ce
-
b
ased
an
d
s
u
s
tain
ab
le
s
tr
ateg
ies
f
o
r
e
n
h
an
ci
n
g
e
d
u
ca
t
io
n
al
q
u
ality
in
t
h
e
Dep
ar
tm
en
t o
f
I
n
f
o
r
m
atics E
n
g
in
ee
r
in
g
[
3
8
]
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
SW
OT
an
aly
s
i
s
is
em
p
lo
y
ed
to
ass
ess
th
e
in
teg
r
atio
n
o
f
AI
in
lear
n
in
g
with
in
th
e
Dep
ar
tm
en
t o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
b
y
i
d
en
tify
in
g
k
ey
SW
OT
[
3
9
]
,
[
4
0
]
.
T
h
e
a
n
aly
s
is
is
b
ased
o
n
q
u
alitativ
e
d
ata
o
b
tain
ed
f
r
o
m
in
-
d
e
p
th
in
ter
v
iews
with
f
ac
u
lty
m
em
b
er
s
,
s
tu
d
en
ts
,
an
d
ac
ad
em
ic
a
d
m
in
i
s
tr
ato
r
s
,
s
u
p
p
o
r
ted
b
y
in
s
titu
tio
n
al
d
o
cu
m
e
n
t
an
al
y
s
is
an
d
r
elev
a
n
t
liter
atu
r
e.
T
h
ese
d
ata
wer
e
s
y
s
tem
atica
lly
c
o
d
ed
a
n
d
a
n
aly
ze
d
u
s
in
g
I
FAS
an
d
E
FAS
m
atr
ices
to
d
eter
m
in
e
th
e
d
ep
a
r
tm
en
t’
s
s
tr
ateg
ic
p
o
s
itio
n
.
T
h
e
r
esu
ltin
g
in
s
ig
h
ts
p
r
o
v
id
e
a
s
tr
ateg
ic
f
o
u
n
d
atio
n
f
o
r
f
o
r
m
u
latin
g
ef
f
ec
tiv
e
a
n
d
s
u
s
tain
ab
le
AI
-
b
ased
lear
n
in
g
s
tr
ateg
ies
t
h
at
en
h
an
ce
e
d
u
ca
tio
n
al
q
u
ality
a
n
d
s
u
p
p
o
r
t th
e
d
ev
elo
p
m
en
t o
f
h
ig
h
er
e
d
u
ca
tio
n
with
in
PTKI
N
[
4
1
]
,
[
4
2
]
T
h
e
SW
OT
an
aly
s
is
is
u
s
ed
t
o
id
en
tify
an
d
ev
alu
ate
th
e
SW
OT
r
elate
d
to
th
e
im
p
lem
en
tatio
n
o
f
AI
in
th
e
ed
u
ca
tio
n
al
co
n
tex
t.
As
p
r
esen
ted
in
T
a
b
le
1
,
th
e
SW
OT
an
aly
s
is
s
u
m
m
ar
izes
th
ese
in
ter
n
al
an
d
ex
ter
n
al
s
tr
ateg
ic
f
ac
t
o
r
s
.
T
h
e
r
esu
lts
o
f
th
e
SW
OT
an
aly
s
is
p
r
esen
ted
in
T
ab
le
1
p
r
o
v
id
e
a
co
m
p
r
eh
e
n
s
iv
e
o
v
er
v
iew
o
f
th
e
SW
OT
f
ac
ed
b
y
th
e
Dep
a
r
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
in
in
teg
r
atin
g
AI
i
n
to
th
e
lear
n
in
g
p
r
o
ce
s
s
.
T
o
h
ar
n
ess
th
e
ex
is
tin
g
p
o
ten
tial,
s
tr
ateg
ic
ef
f
o
r
ts
ar
e
r
eq
u
ir
ed
to
s
tr
en
g
th
en
in
ter
n
al
f
ac
to
r
s
an
d
m
ax
im
ize
e
x
ter
n
al
o
p
p
o
r
tu
n
ities
,
th
er
eb
y
en
a
b
lin
g
th
e
ef
f
ec
tiv
e
an
d
s
u
s
tain
ab
le
im
p
lem
en
tatio
n
o
f
AI
in
ed
u
ca
tio
n
.
3
.
1
.
I
F
AS a
na
ly
s
is
T
h
e
I
FAS
is
a
m
eth
o
d
u
s
ed
to
ev
alu
ate
t
h
e
in
ter
n
al
s
tr
en
g
th
s
an
d
wea
k
n
ess
es
th
at
in
f
lu
en
ce
an
o
r
g
an
izatio
n
o
r
en
tity
’
s
s
tr
ateg
ic
p
o
s
itio
n
.
T
ab
le
2
p
r
esen
t
s
th
e
r
esu
lts
o
f
th
e
I
FA
S
an
aly
s
is
,
p
r
o
v
id
in
g
a
d
etailed
o
v
er
v
iew
o
f
th
ese
in
ter
n
al
f
ac
to
r
s
.
B
ased
o
n
th
e
r
esu
lts
o
f
th
e
I
FA
S
an
aly
s
is
,
t
h
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics E
n
g
in
ee
r
in
g
d
em
o
n
s
tr
ates sig
n
if
ican
t in
ter
n
al
s
tr
en
g
th
s
with
a
to
tal
s
co
r
e
o
f
2
.
1
0
.
T
h
e
av
aila
b
ilit
y
o
f
ad
eq
u
ate
tech
n
o
lo
g
ical
i
n
f
r
astru
ctu
r
e
a
n
d
th
e
tech
n
o
lo
g
ical
s
k
ills
o
f
f
ac
u
lty
an
d
s
tu
d
en
ts
ar
e
k
ey
ad
v
an
tag
es
s
u
p
p
o
r
tin
g
th
e
in
t
eg
r
atio
n
o
f
AI
in
lear
n
in
g
.
Ad
d
itio
n
ally
,
th
e
s
u
p
p
o
r
t
o
f
ca
m
p
u
s
p
o
licies
an
d
th
e
d
ev
elo
p
m
e
n
t o
f
tec
h
n
o
lo
g
y
-
b
a
s
ed
cu
r
r
icu
la
f
u
r
th
er
s
tr
en
g
th
e
n
th
e
d
e
p
ar
tm
en
t'
s
r
ea
d
in
ess
to
im
p
lem
en
t A
I
.
T
h
e
d
ata
in
th
e
I
FAS
tab
le
wer
e
d
er
iv
e
d
th
r
o
u
g
h
q
u
alita
tiv
e
co
n
ten
t
an
aly
s
is
b
y
s
y
s
tem
atica
lly
co
d
in
g
in
ter
v
iew
tr
a
n
s
cr
ip
ts
,
in
s
titu
tio
n
al
d
o
cu
m
e
n
ts
,
an
d
r
elev
an
t
liter
atu
r
e
in
to
in
ter
n
al
s
tr
ateg
ic
f
ac
to
r
s
.
E
ac
h
f
ac
to
r
was
ass
ig
n
ed
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Prio
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at
h
ig
h
lig
h
t
th
e
cr
itical
r
o
le
o
f
ex
ter
n
al
d
r
iv
e
r
s
s
u
ch
as
in
d
u
s
tr
y
p
ar
tn
er
s
h
ip
an
d
d
ig
ital
ed
u
c
atio
n
p
o
licies
in
ac
ce
ler
atin
g
AI
in
teg
r
atio
n
in
u
n
iv
er
s
ities
.
Ho
wev
er
,
th
ese
o
p
p
o
r
tu
n
ities
ca
n
o
n
ly
b
e
m
ax
im
ized
wh
en
in
s
titu
tio
n
s
h
av
e
s
u
f
f
icien
t
i
n
ter
n
al
ca
p
ac
ity
in
ter
m
s
o
f
in
f
r
astru
ctu
r
e
an
d
h
u
m
an
r
es
o
u
r
ce
s
,
as
also
s
tated
b
y
E
li
m
ad
i
et
a
l
.
[
2
]
.
I
n
o
r
d
er
to
f
u
r
th
er
v
alid
ate
t
h
e
ad
v
an
tag
es
o
f
AI
-
b
ased
lear
n
in
g
s
tr
ateg
ies,
a
co
m
p
ar
ativ
e
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aly
s
is
was
co
n
d
u
cted
b
etwe
en
tr
ad
itio
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al
lear
n
in
g
a
p
p
r
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ac
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es
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d
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e
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h
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ce
d
d
ig
ital
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r
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in
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with
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n
th
e
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ar
tm
en
t
o
f
I
n
f
o
r
m
ati
cs
E
n
g
in
ee
r
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g
.
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h
e
co
m
p
ar
is
o
n
f
o
c
u
s
es
o
n
th
r
ee
k
ey
asp
ec
ts
:
s
tu
d
en
t
en
g
ag
e
m
en
t,
p
er
s
o
n
aliza
tio
n
o
f
lear
n
in
g
,
an
d
lear
n
in
g
o
u
tco
m
es.
R
esu
lts
in
d
icate
th
at
AI
-
b
ased
lear
n
in
g
p
r
o
v
id
e
s
s
ig
n
if
ican
tly
h
ig
h
er
lev
els
o
f
en
g
a
g
em
en
t
a
n
d
p
er
s
o
n
alize
d
lear
n
i
n
g
ex
p
er
ie
n
ce
s
.
T
ab
le
4
s
u
m
m
ar
izes
th
i
s
co
m
p
ar
is
o
n
.
T
h
ese
r
esu
lts
s
u
p
p
o
r
t
f
in
d
in
g
s
b
y
au
th
o
r
s
[
7
]
,
[
6
]
,
wh
ic
h
s
h
o
w
th
at
AI
-
b
ased
e
d
u
ca
tio
n
m
o
d
els
en
h
an
ce
lear
n
e
r
en
g
ag
e
m
en
t
an
d
allo
w
f
o
r
g
r
ea
ter
p
er
s
o
n
aliza
tio
n
c
o
m
p
a
r
ed
to
co
n
v
en
tio
n
al
m
eth
o
d
s
.
T
h
e
s
co
r
e
g
ap
in
all
th
r
ee
d
i
m
en
s
io
n
s
co
n
f
ir
m
s
th
e
s
tr
ateg
ic
v
alu
e
o
f
AI
as
a
p
ed
ag
o
g
ical
in
n
o
v
atio
n
in
in
f
o
r
m
atics
ed
u
ca
tio
n
.
Ov
er
all,
th
is
d
is
cu
s
s
io
n
em
p
h
asizes
th
at
ex
ter
n
al
f
ac
to
r
s
(
E
FAS)
h
av
e
a
g
r
ea
ter
p
o
te
n
tial
to
s
u
p
p
o
r
t
th
e
im
p
lem
e
n
tatio
n
o
f
AI
in
th
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
,
b
u
t
s
u
cc
ess
s
till
d
e
p
en
d
s
o
n
th
e
a
b
ilit
y
to
s
tr
en
g
t
h
en
in
te
r
n
al
f
ac
to
r
s
an
d
in
teg
r
ate
i
n
ter
n
al
s
tr
en
g
t
h
s
with
ex
ter
n
al
o
p
p
o
r
tu
n
ities
to
cr
ea
te
o
p
tim
al
s
y
n
er
g
y
.
Fig
u
r
e
1
illu
s
tr
ates
th
at
AI
-
b
a
s
ed
lear
n
in
g
s
tr
ateg
ies
s
ig
n
if
i
ca
n
tly
o
u
tp
er
f
o
r
m
tr
ad
itio
n
al
m
eth
o
d
s
in
ter
m
s
o
f
s
tu
d
en
t
en
g
ag
em
e
n
t,
p
er
s
o
n
aliza
tio
n
,
an
d
lear
n
i
n
g
o
u
tco
m
es
with
in
th
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
.
T
h
is
in
teg
r
ated
SW
OT
-
b
ased
p
er
s
p
ec
tiv
e
also
ec
h
o
es
th
e
s
tr
ateg
y
m
o
d
el
p
r
o
p
o
s
ed
b
y
Mu
r
taza
et
a
l.
[
4
7
]
,
wh
e
r
e
s
u
cc
ess
in
d
ig
ital
tr
an
s
f
o
r
m
atio
n
in
ed
u
ca
tio
n
d
ep
en
d
s
o
n
a
b
alan
ce
b
etwe
en
ex
p
lo
itin
g
e
x
ter
n
al
o
p
p
o
r
tu
n
iti
es
an
d
r
ein
f
o
r
cin
g
in
ter
n
al
ca
p
ab
ilit
ies.
T
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
c
o
n
tr
ib
u
te
to
en
r
ich
in
g
t
h
is
f
r
am
ewo
r
k
in
th
e
co
n
tex
t o
f
AI
ad
o
p
tio
n
in
h
i
g
h
er
ed
u
ca
tio
n
in
I
n
d
o
n
esia.
T
ab
le
4
.
C
o
m
p
a
r
is
o
n
o
f
lear
n
i
n
g
asp
ec
ts
b
etwe
en
tr
ad
itio
n
al
an
d
AI
-
b
ased
d
ig
ital le
ar
n
i
n
g
No
A
sp
e
c
t
Tr
a
d
i
t
i
o
n
a
l
l
e
a
r
n
i
n
g
(
sc
o
r
e
1
–
5)
AI
-
b
a
se
d
l
e
a
r
n
i
n
g
(
sc
o
r
e
1
–
5)
1
S
t
u
d
e
n
t
e
n
g
a
g
e
me
n
t
3
5
2
P
e
r
so
n
a
l
i
z
a
t
i
o
n
o
f
l
e
a
r
n
i
n
g
2
5
3
Le
a
r
n
i
n
g
o
u
t
c
o
mes
3
4
.
5
Fig
u
r
e
1
.
Vis
u
al
co
m
p
ar
ativ
e
an
aly
s
is
b
etwe
en
tr
ad
itio
n
al
a
n
d
AI
-
b
ased
lear
n
in
g
4.
CO
NCLU
SI
O
N
T
h
e
co
m
p
a
r
is
o
n
b
etwe
en
i
n
ter
n
al
an
d
e
x
ter
n
al
f
ac
t
o
r
s
h
ig
h
lig
h
ts
th
o
s
e
ex
ter
n
al
o
p
p
o
r
tu
n
ities
p
r
o
v
id
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s
ig
n
if
ica
n
t
ad
v
an
tag
e
s
f
o
r
th
e
Dep
ar
tm
en
t
o
f
I
n
f
o
r
m
atics
E
n
g
in
ee
r
in
g
in
im
p
le
m
en
tin
g
AI
-
b
ased
ed
u
ca
tio
n
.
Op
p
o
r
tu
n
ities
s
u
ch
as
th
e
g
r
o
win
g
d
em
an
d
f
o
r
A
I
-
b
ased
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n
in
g
,
co
llab
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r
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with
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a
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8
S
tr
a
teg
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f a
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tellig
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3005
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r
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atio
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o
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atio
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ev
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m
en
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ter
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ar
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ical
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f
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r
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ar
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ter
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l
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ac
u
lty
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tu
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t
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ills
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ev
elo
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i
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ased
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r
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lu
m
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d
i
n
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r
ea
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r
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u
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ased
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s
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co
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t,
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h
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ay
co
n
s
tr
ain
th
e
g
en
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th
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in
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.
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tu
r
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esear
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h
s
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o
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u
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titativ
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m
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eth
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cr
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ased
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ra
l
stu
d
i
e
s
in
I
n
fo
rm
a
ti
c
s
a
t
AMIKOM
Un
iv
e
rsity
.
As
a
lec
tu
re
r
i
n
De
p
a
rtme
n
t
o
f
In
f
o
rm
a
ti
c
s,
F
a
c
u
lt
y
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
UIN
S
u
l
tan
M
a
u
lan
a
Ha
sa
n
u
d
d
i
n
Ba
n
te
n
,
S
e
ra
n
g
,
I
n
d
o
n
e
sia
,
h
is
re
se
a
rc
h
fo
c
u
se
s
o
n
d
a
tab
a
se
s,
AI,
m
a
c
h
i
n
e
lea
rn
in
g
,
a
n
d
a
p
p
li
c
a
ti
o
n
d
e
v
e
lo
p
m
e
n
t.
He
a
lso
writes
a
c
a
d
e
m
ic an
d
p
ra
c
ti
c
a
l
b
o
o
k
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
h
m
a
d
.
ta
b
ra
n
i
@u
in
b
a
n
ten
.
a
c
.
i
d
.
Re
z
a
S
y
a
fr
ija
l
is
a
lec
tu
re
r
i
n
th
e
De
p
a
rtme
n
t
o
f
In
f
o
rm
a
ti
c
s,
F
a
c
u
lt
y
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
UIN
S
u
lt
a
n
M
a
u
lan
a
Ha
sa
n
u
d
d
in
Ba
n
ten
,
S
e
ra
n
g
,
In
d
o
n
e
sia
.
He
e
a
rn
e
d
h
is
b
a
c
h
e
lo
r’s
d
e
g
re
e
in
I
n
fo
rm
a
ti
c
s
(S
.
Ko
m
.
)
a
n
d
m
a
ste
r’s
d
e
g
re
e
in
Co
m
p
u
ter
S
c
ien
c
e
fro
m
Un
iv
e
rsitas
Bu
d
i
Lu
h
u
r
,
Ja
k
a
rta.
He
h
a
s
b
e
e
n
tea
c
h
in
g
a
t
t
h
e
sc
h
o
o
l
lev
e
l
sin
c
e
2
0
0
7
a
n
d
a
t
th
e
u
n
i
v
e
rsity
lev
e
l
si
n
c
e
2
0
1
5
,
c
o
v
e
r
in
g
c
o
u
rse
s
su
c
h
a
s
in
tr
o
d
u
c
ti
o
n
t
o
p
r
o
g
ra
m
m
in
g
,
a
lg
o
r
it
h
m
s
a
n
d
p
r
o
g
ra
m
m
in
g
.
He
c
a
n
b
e
c
o
n
t
a
c
ted
a
t
e
m
a
il
:
re
z
a
.
sy
a
friza
l@u
in
b
a
n
ten
.
a
c
.
i
d
.
S
u
ta
n
t
o
re
c
e
iv
e
d
h
is
M
.
Ko
m
.
d
e
g
re
e
in
Co
m
p
u
ter
S
c
ien
c
e
wit
h
th
e
In
f
o
rm
a
ti
c
s
En
g
i
n
e
e
rin
g
S
t
u
d
y
P
ro
g
ra
m
fro
m
S
TM
IK
Eres
h
a
J
a
k
a
rta
wit
h
th
e
t
h
e
sis
“
D
e
v
e
lo
p
m
e
n
t
o
f
m
u
lt
i
c
rit
e
ria
d
e
c
isio
n
m
a
k
in
g
(
M
CDM
)
fo
r
re
c
o
m
m
e
n
d
e
r
sy
ste
m
f
o
r
g
o
o
d
s/se
rv
ice
s
p
r
o
v
id
e
rs
a
t
Ba
n
ten
P
ro
v
in
c
e
o
ffice
”
.
In
a
d
d
it
io
n
,
h
e
a
lso
se
rv
e
d
a
s
d
e
a
n
o
f
t
h
e
De
p
a
rtme
n
t
o
f
In
fo
rm
a
ti
c
s
En
g
in
e
e
rin
g
,
F
a
c
u
lt
y
o
f
Co
m
p
u
ter
S
c
ien
c
e
,
Un
i
v
e
r
sitas
Ba
n
ten
Ja
y
a
,
Ba
n
ten
,
In
d
o
n
e
sia
sin
c
e
2
0
2
2
u
n
ti
l
n
o
w.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
s
u
t
a
n
to
@u
n
b
a
ja.ac
.
id
.
Dr
.
Ek
o
Wa
h
y
u
Wi
b
o
wo
,
M
.
S
i.
re
c
e
iv
e
d
th
e
d
o
c
t
o
ra
l
d
e
g
r
e
e
in
Ed
u
c
a
ti
o
n
a
l
Tec
h
n
o
l
o
g
y
fro
m
Un
i
v
e
rsitas
Ne
g
e
ri
Ja
k
a
rta
in
2
0
2
0
.
He
o
b
tain
e
d
a
B.
S
c
.
in
S
tatisti
c
s
fro
m
Un
iv
e
rsitas
Bra
wijay
a
in
1
9
9
8
a
n
d
a
n
M
.
S
c
.
in
S
tatisti
c
s
fro
m
th
e
In
stit
u
t
P
e
rtan
ian
B
o
g
o
r
i
n
2
0
0
9
.
Cu
rre
n
t
ly
,
h
e
se
rv
e
s
a
s
a
s
so
c
iate
p
ro
fe
ss
o
r
a
t
th
e
M
a
th
e
m
a
ti
c
s
S
tu
d
y
P
r
o
g
ra
m
a
t
UIN
S
u
lt
a
n
M
a
u
lan
a
Ha
sa
n
u
d
d
i
n
Ba
n
ten
I
n
d
o
n
e
sia
.
His
re
se
a
rc
h
in
t
e
re
sts
in
c
lu
d
e
m
a
th
e
m
a
ti
c
s,
sta
ti
stics
,
d
a
ta
sc
ien
c
e
,
a
n
d
re
s
e
a
rc
h
a
n
d
d
e
v
e
lo
p
m
e
n
t.
He
c
a
n
b
e
c
o
n
tac
ted
at
e
m
a
il
:
e
k
o
.
wib
o
wo
@
u
in
b
a
n
ten
.
a
c
.
id
.
S
y
ifa
Am
a
r
a
Dhes
ti
y
a
n
i
is
a
stu
d
e
n
t
a
t
De
p
a
rtme
n
t
o
f
C
o
m
p
u
ter
E
n
g
in
e
e
rin
g
,
Telk
o
m
Un
i
v
e
rsity
,
Ba
n
d
u
n
g
,
In
d
o
n
e
sia
.
S
h
e
is
c
u
rre
n
tl
y
u
n
d
e
rtak
i
n
g
a
n
i
n
tern
sh
ip
i
n
th
e
fiel
d
o
f
c
o
m
p
u
ter
e
n
g
in
e
e
rin
g
d
u
rin
g
th
is
se
m
e
ste
r.
S
h
e
h
a
s
a
u
th
o
re
d
two
jo
u
r
n
a
ls
in
t
h
e
field
o
f
in
fo
rm
a
ti
c
s
a
n
d
is
c
u
rre
n
t
ly
se
rv
in
g
a
s
a
lab
a
ss
istan
t
a
t
th
e
Ne
t
wo
rk
Lab
o
ra
to
r
y
o
f
Telk
o
m
Un
iv
e
rsity
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sy
ifaa
m
d
h
@s
tu
d
e
n
t.
tel
k
o
m
u
n
i
v
e
rsity
.
a
c
.
i
d
.
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