Internati
o
nal
Journal of Ele
ctrical
and Computer
Engineering
(IJE
CE)
V
o
l.
7, N
o
. 4
,
A
ugu
st
201
7
, pp
. 22
53
~
2
260
I
S
SN
: 208
8-8
7
0
8
,
D
O
I
: 10.115
91
/ij
ece.v7
i3.p
p22
53-
226
0
2
253
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
Virtual Laboratory for Line
Follower Robot Competition
Suw
as
on
o
1
,
Dwi
Priha
n
to
2
,
Iraw
an
Dw
i
Wah
y
on
o
3
, Andrew
Nafals
ki
4
1,2,3
Electrical En
gineer
ing, Universitas
Neger
i
Malang (UM)
, Malang, Indonesia
4
School of
Education
,
Univ
ersity of South
Austr
a
lia (UniSA), Ad
elaide SA, Australia
Article Info
A
BSTRAC
T
Article histo
r
y:
Received
May 21, 2017
Rev
i
sed
Jun
23,
201
7
Accepte
d J
u
l
2, 2017
Laborator
y
serv
es as an impor
tant f
aci
lit
y
for
experim
e
nt
an
d res
ear
ch
act
ivit
y.
Th
e li
m
itation of
tim
e
,
equipm
ent
,
an
d capa
c
it
y
in th
e exper
im
e
nt
and research u
ndertak
ing impede bot
h stud
ents and colleg
e students in
undertak
ing research for com
p
et
ition prep
arat
ion
,
parti
c
ul
arl
y
dealing with
line fo
llower
rob
o
t com
p
eti
tion w
h
ich r
e
quires
a
wide spac
e of
th
e room
with
various tr
ack
ty
pes
.
Unsettled
compe
tit
ion tr
ack in
fluen
ces
PID control
setting of
lin
e follower
robot. Th
is stud
y
aims at dev
e
lop
i
ng Virtual
Labora
t
or
y (V-
L
ab) for s
t
ud
ent
s
or coll
ege s
t
u
d
ents
who are
p
r
eparing
for
line follower ro
bot com
p
etition
with unsettled and change
able
tracks. Th
is
stud
y
conc
luded
that the tri
a
l da
ta sc
ore reached
98.5%, the material exper
t
score obtained
8
9
.7%,
learning
model
exper
t
score obtained
97.9%, and
th
e
averag
e score of
small group learning model and
field of 82
.4%, which th
e
averag
e s
c
or
e of
the
entir
e
as
pec
t
s
obtain
e
d 90
.8
%.
Keyword:
Lin
e
fo
llow
e
r ro
bo
t
PID control
Ro
bo
t co
m
p
eti
tio
n
Virtual la
bo
rat
o
ry
Copyright ©
201
7 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
ing
Autho
r
:
Suw
asono
,
Electrical Engi
neeri
n
g,
Uni
v
e
r
sitas Ne
geri
Malang
Jalan
Sem
a
r
a
ng
5
,
Malan
g
651
45
, East Jav
a
, In
don
esia
Em
a
il: Su
wason
o
.ft@u
m
.ac.id
1.
INTRODUCTION
On
robo
t co
mp
etitio
n
,
a fi
n
e
an
d
stab
le Li
n
e Fo
llower (LF) rob
o
t
is req
u
i
red. A stab
ility o
n
th
e
m
o
v
e
m
e
n
t o
f
th
e rob
o
t influ
e
n
ces th
e accom
p
l
ish
m
en
t o
f
th
e obj
ect takin
g
an
d p
lacing
on
the co
m
p
etitio
n.
The m
o
re stable the robot
movem
e
nt results in the highe
r possibility
of accom
p
lish
m
ent. One pre
v
alent
mean
s to
im
p
r
o
v
e
th
e
stab
ility o
f
th
e
robo
t is b
y
u
s
ing
PID con
t
ro
l [1
].
Track i
n
stallment for L
F
robot testing
requires
a wide
space of t
h
e room
. Meanwhile, the existi
ng
lab
o
rato
ry is no
t feasib
le to
b
e in
stalled
v
a
riou
s typ
es o
f
LF robo
t track. Th
us, it is n
ecessary to
p
r
o
v
i
d
e
vari
ous
t
y
pes
o
f
vi
rt
ual
t
r
ac
k i
n
a
f
o
rm
of
vi
rt
ual
l
a
b
o
rat
o
ry
t
o
obt
ai
n
pa
ram
e
t
e
r val
u
e
of
PI
D LF
r
o
bot
[
2
]
.
Vi
rt
ual
l
a
bo
rat
o
ry
or
com
m
onl
y
k
n
o
w
n as
V-
Lab
i
s
a c
o
m
put
er t
ech
n
o
l
o
gy
de
vel
o
p
m
ent
as an
in
teractiv
e m
u
l
t
i
m
ed
ia o
b
j
ect to
si
m
u
lates la
b
o
ratory ex
p
e
ri
m
en
t
o
n
th
e co
m
p
u
t
er [3
].
V-Lab
is a co
mp
u
t
er
sim
u
l
a
t
i
on t
h
at
enabl
e
s a
n
e
x
peri
m
e
nt
fu
nct
i
on
of a l
a
bo
ra
t
o
ry
o
n
a c
o
m
put
e
r
. R
ece
nt
l
y
, a pre
f
era
b
l
e
vi
rt
ual
lab
o
rato
ry is an
offli
n
e v
i
rtu
a
l lab
o
r
at
o
r
y.
Ho
wev
e
r, it do
es no
t offer a lon
g
-d
istan
ce app
licatio
n
at th
e sam
e
t
i
m
e
[4]
.
In
ot
her
wo
rds
,
t
h
e
offl
i
n
e
vi
rt
ual
l
a
borat
ory
i
s
onl
y
l
i
m
i
t
e
d to o
n
e pa
rt
i
c
ul
ar ap
pl
i
cat
i
on i
n
on
e
roo
m
with
th
e in
itial d
a
ta req
u
i
red
t
o
b
e
in
pu
t in
each
co
m
p
u
t
er.
On
lin
e v
i
rt
u
a
l
lab
o
ratory, hen
ce, is
im
perat
i
v
e t
o
b
e
devel
ope
d. T
h
e o
n
l
i
n
e vi
rt
u
a
l
l
a
borat
o
ry
i
s
a com
put
er t
echn
o
l
o
gy
de
ve
l
opm
ent
i
n
a fo
rm
od
interactive m
u
ltimedia object
to sim
u
late la
boratory expe
rim
ent
on t
h
e
com
puter a
nd
accessible from
the
i
n
t
e
rnet
[5
-
6
]
.
Learni
ng
M
a
n
a
gem
e
nt
Sy
st
em
(LM
S
) i
s
em
pl
oy
ed wi
t
h
i
n
t
h
e
com
p
o
n
e
nt
o
f
onl
i
n
e
vi
rt
ual
lab
or
a
to
r
y [7
-8].
Th
is stud
y u
tilizes v
i
rtu
al labo
rat
o
ry (V-Lab) as
a learn
i
ng
med
i
a o
f
lin
e
fo
llo
wer rob
o
t
wh
ich
aim
s
at
pr
ovi
di
n
g
t
h
e st
ude
nt
s a
fe
asi
b
l
e
l
a
bo
rat
o
ry
fo
r
gene
rat
i
ng a
n
d si
m
u
l
a
ti
ng l
i
n
e
f
o
l
l
o
w
e
r r
o
b
o
t
on i
t
s
t
r
ac
k
an
d as a learn
i
n
g
m
e
d
ia in
reso
lv
i
n
g
issu
es
o
n
lin
e fo
llower rob
o
t
d
ealing with
Kp
,
Kd, and
Ki on
v
a
riou
s
co
m
p
etitio
n
track
s.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
JECE
Vo
l. 7
,
N
o
. 4
,
Aug
u
s
t 2
017
:
22
53-
22
60
2
254
2.
R
ESEARC
H M
ETHOD
Thi
s
st
udy
use
d
devel
opm
ent
l
earni
ng
resea
rch
m
ode
l in
Fig
u
re
1
[9-10
]
.
Howev
e
r, in this stu
d
y
, the
stag
es u
s
ed
are o
n
ly un
til th
e
n
in
th
stag
e. This was d
o
n
e
with
th
e con
s
id
eratio
n
th
at th
e d
e
v
e
l
o
p
m
en
t of th
e
Virtu
a
l Labo
rato
ry learn
i
ng
m
o
d
e
l d
e
v
e
l
o
ped
o
n
l
y
u
n
til the test p
r
o
t
o
t
y
p
e of th
e produ
ct.
Fi
gu
re
1.
Lea
r
ni
n
g
M
odel
De
vel
o
pm
ent
[1
0]
Here
, p
r
o
d
u
ct
devel
opm
ent
t
r
i
a
l
s
were co
nd
uct
e
d t
h
ro
u
gh t
h
ree st
a
g
es,
na
m
e
l
y
i
ndi
vi
d
u
a
l
t
e
st
, sm
all
gr
o
up t
e
st
, an
d
fi
el
d t
e
st
. The
i
ndi
vi
dual
t
e
st
phase
was car
ri
ed o
u
t
by
t
h
e
l
earni
n
g
m
e
dia expe
rt
s, m
a
teri
al
s
expe
rt
s, a
n
d l
earni
ng m
odel
exp
e
rt
s.
The
i
ndi
vi
dual
t
r
i
a
l
s
were
co
n
duc
t
e
d t
o
det
e
rm
ine t
h
e
feasi
b
i
l
i
t
y
of
teaching m
ater
i
als, instructional m
edia and
virt
ual la
boratory learni
ng
m
odel de
velope
d.
The sm
all group trial conduc
ted aim
e
d at observing
the
fe
asibility of learni
ng m
odel design
virtua
l
lab
o
rato
ry,
p
a
rticu
l
arly th
e feasib
ility o
f
l
earn
i
n
g
m
e
d
i
a b
a
sed
o
n
the web
an
d
LM
S e
m
p
l
o
y
ed
in
lin
e
fo
llower
co
m
p
etitio
n
learn
i
ng
.
W
i
t
h
in
t
h
e
sm
a
ll g
r
ou
p
tri
a
l, th
e au
t
h
ors ex
p
l
o
r
ed
inform
at
io
n
reg
a
rdin
g
all
pos
sible
obsta
cles faced by t
h
e stude
n
ts the m
o
m
ent
they try to use
the learni
ng m
e
dia bas
e
d
on
web and
LMS. In
add
itio
n, th
e au
tho
r
s also
tried
to
i
d
en
tify th
e weak
n
e
sses in
LM
S fro
m
v
a
ried
p
e
rsp
ectiv
es
based
on
t
h
e g
r
ou
p
of
st
ude
nt
s.
Field trials are an advance
d
stage after a s
m
all gr
o
u
p
trial co
nd
u
c
ted
.
At th
is stag
e, th
e d
e
v
e
lop
e
r
requested inform
ation from
stude
nts tha
t
am
ounte
d
t
o
at least
20 pe
ople in one
particular
place
si
m
u
ltan
e
o
u
s
ly
. Th
e tested produ
ct in
t
h
e
field
test is the produ
ct of
rev
i
sion
at th
e in
d
i
v
i
du
al (ex
p
e
rt
ev
alu
a
tion
)
and
sm
al
l g
r
ou
p
trial stag
e. Th
i
s
field
test is c
o
ndu
cted
to
d
e
termin
e wh
et
her or no
t th
e produ
ct
has bee
n
devel
ope
d.
The re
searc
h
i
n
st
r
u
m
e
nt
em
pl
oy
ed i
n
t
h
i
s
s
t
udy
i
s
a q
u
est
i
on
nai
r
e.
Q
u
es
t
i
onnai
r
e em
ploy
ed i
n
t
h
e
val
i
d
at
i
o
n p
r
oc
ess ex
pert
s
(m
at
eri
a
l
expe
rt
s,
m
e
di
a expert
s
, an
d l
ear
ni
n
g
m
odel
s
Vi
rt
ual
Lab
o
rat
o
ry
e
x
pert
s
)
,
and al
so t
o
i
d
ent
i
f
y
t
h
e st
ud
ent
s
'
respo
n
se
t
o
t
h
e l
earni
n
g
m
odel
and t
h
e devel
o
pe
d L
earni
ng M
a
na
g
e
m
e
nt
Sy
st
em
. Quest
i
on
nai
r
es em
pl
oy
ed i
n
t
h
i
s
st
udy
was i
n
t
h
e
form
of a closed
ques
tionn
aire wh
ere altern
ativ
e
answ
ers
have
b
een p
r
ovi
ded t
hus t
h
e res
p
on
dent
s
were
only requi
red t
o
c
h
oose the ans
w
er. T
h
e calcula
tion of
the questionna
ire score wa
s
calculate
d from
the answe
r
score
for ea
ch
question.
The a
n
swe
r
s t
o
the
que
stionnaire
used a
Like
rt sc
ale cons
isting
of four cate
g
ories of choice.
The
dat
a
a
n
al
y
s
i
s
t
echni
que
s
i
n
t
h
i
s
st
udy
w
e
re
usi
n
g t
h
e
f
o
rm
ul
a perc
ent
a
ge,
w
h
ere
t
h
e
res
u
l
t
s
o
f
th
ese calcu
latio
n
s
were
u
s
ed to
see th
e feasib
ility o
f
th
e
asp
ects of learn
i
ng
assessed
.
Equ
a
tio
n
1
is u
s
ed
to
d
e
term
in
e th
e
p
e
rcen
tag
e
of
elig
ib
ility o
f
th
e assessed
ind
i
cato
r
[8
]. Tab
l
e 1 shows
th
e classificatio
n is
feasib
ility lev
e
l criteria [9
].
i
x
x
P
x
10
0%
(1
)
whe
r
e:
P
=
Perce
n
tage sc
ore
x
=
R
e
spo
n
d
ent
a
m
ount
i
n
one
i
t
e
m
i
x
=
to
tal o
f
id
eal
valu
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
70
8
Virtu
a
l Lab
o
rato
ry fo
r Lin
e
Fo
llo
wer Rob
o
t
Co
mp
etitio
n
(S
u
w
a
s
o
n
o
)
2
255
Tab
l
e
1
.
Feasibilit
y Lev
e
l Criteria [9
]
P
e
rcent
a
ge
(%)
Qualifi
cat
ion
Note
80-100
60-79
50-59
0-49
Valid
S
u
fficien
tl
y v
ali
d
Insufficien
tly
V
a
lid
Invalid
No Revision
No Revision
Revision
Suggested to
be
altered
2.1
Virtual Lab Arc
h
itectur
e
The vi
rtual lab was created
using LMS
with the suppo
r
t of Mo
od
le as an
in
teractive learning m
edia
as shown i
n
Figure
2.
Students can us
e Internet-c
onnec
ted de
vices to access V-La
b, the
n
it re
qui
res a
registration ac
count as m
e
m
b
er/teacher /
t
u
tor with differe
n
t
features
a
rra
nge
d
by the se
rve
r
a
nd st
ore
d
in the
dat
a
base
.
2.
2
Vi
rtu
a
l
L
a
b M
o
del
Th
e
v
i
rtual lab m
o
d
e
l is sho
w
n
in Figure
3
.
In
M
o
od
le, t
h
ere is an in
teracti
o
n b
e
t
w
een in
stru
ctor and
stu
d
e
n
t
b
y
d
i
fferen
tiatin
g
the in
teractio
n
with
in
, in
wh
ic
h
th
e in
stru
ct
o
r
as th
e facil
itato
r an
d
p
r
ov
id
er o
f
l
earni
n
g
m
a
t
e
r
i
al
and co
nsul
t
a
t
i
on o
n
l
i
n
e t
o
t
h
e st
ude
nt
s. Whi
l
e
t
h
e st
u
d
e
nt
s o
n
l
y
serv
e as users w
h
o are
requ
ired
to
b
e
reg
i
stered
in
a v
i
rtu
a
l lab
wh
ich
is ab
le to
in
teract with
b
o
t
h
on
lin
e wi
th
th
e in
stru
ct
o
r
and
o
f
flin
e.
Fi
gu
re
2.
Vi
rt
u
a
l
Lab
Arc
h
i
t
e
ct
ure
Fi
gu
re
3.
Vi
rt
u
a
l
Lab M
odel
2.
3
Vi
rtu
a
l
L
a
b M
a
teri
al
T
h
e
ma
te
r
i
a
l
p
r
ov
id
ed
in
V
L
ab
ar
e
:
1.
Lin
e
fo
llower ro
bo
t
g
e
n
e
rating
2.
Lin
e
fo
llower ro
bo
t trou
b
lesho
o
ting
.
3.
The
det
e
rm
i
n
at
i
on
of
K
p
,
Ki
an
d K
d
pa
ra
m
e
t
e
rs on
PI
D
co
nt
rol
base
d
o
n
t
r
ac
k l
e
vel
of
di
f
f
i
c
ul
t
y
f
r
om
begi
nne
r t
o
a
d
vance
d
l
e
vel
.
4.
Quest
i
ons
an
d
Ans
w
e
rs
rega
r
d
i
n
g t
h
e
r
o
bot
l
i
ne f
o
l
l
o
wer.
The
det
e
rm
i
n
at
i
on
of
K
p
,
Ki
and
K
d
param
e
t
e
rs o
n
t
h
e
PI
D co
nt
r
o
l
of t
h
e LF r
o
bot
i
s
p
r
esent
e
d i
n
Fi
gu
re
4
base
d
o
n
t
h
e Zi
e
g
l
e
r
-
Ni
c
hol
s
Osci
l
l
at
i
on m
e
t
hod
on
t
h
e
PI
D
r
o
b
o
t
i
c
PI
D
LF
p
a
ram
e
t
e
r search
[1
0-
1
1
]
. Th
is m
e
th
o
d
can
sh
orten th
e search
time p
a
ram
e
ters
for
usi
n
g si
m
p
le fo
rm
ul
as and
pr
ocess o
f
t
r
i
a
l
and
err
o
r
only on t
h
e sea
r
ch pa
ra
m
e
ters Kp [
1
0]
.
In
t
h
e sec
o
nd
m
e
t
hod
o
f
Zi
e
g
l
e
r-
Ni
ch
ol
s,
t
h
e
fi
rst
t
h
i
n
g
t
o
do
i
s
t
o
ge
ne
rat
e
Ti
=0
an
d
Td=
0
. T
h
e
n
,
onl
y
by
usi
n
g pr
o
p
o
r
t
i
onal
c
ont
rol
act
i
o
n
, t
h
e val
u
e i
s
i
n
creased
fr
om
zero t
o
a c
r
i
t
i
cal val
u
e Kc
r,
he
re t
h
e
o
u
t
p
u
t i
n
itially
h
a
s a
con
tinuo
u
s
o
s
cillatio
n
.
Fro
m
o
s
cillati
n
g
ou
tpu
ts co
ntin
u
o
u
s
ly, critical streng
th
en
in
g of
Kcr an
d
Pcr p
e
riod
s can
b
e d
e
termin
ed
. Fo
r
co
n
tinuo
us
o
s
cillatio
n
s
with
th
e Pcr
p
eri
o
d
Kp, Ti, Td
ad
ju
stm
en
t
are del
i
v
ere
d
b
a
sed o
n
Ta
bl
e 2 [1
0-
1
1
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
JECE
Vo
l. 7
,
N
o
. 4
,
Aug
u
s
t 2
017
:
22
53-
22
60
2
256
RO
BO
T
PO
SI
T
I
O
N
ON
LI
N
E
SE
T
PO
I
N
T
PO
SI
T
I
O
N
TR
A
C
ER
PI
D
C
O
N
T
RO
LLER
PU
L
S
E
PWM
DR
I
V
E
R
MOT
OR
MO
TO
R
DC
WH
E
E
L
SE
N
SO
R
TR
A
C
ER
AC
T
U
AL
RO
BO
T
PO
SI
T
I
O
N
‐
+
Fi
gu
re
4.
PI
D
C
ont
r
o
l
of
LF
M
e
t
h
o
d
B
y
Zi
egl
e
r a
n
d
Ni
ch
ol
s
Tabl
e 2.
B
a
si
c C
ont
r
o
l
of
Zi
e
g
l
e
r-
Ni
ch
ol
s
B
a
sed o
n
Kcr
a
n
d
Pc
r
Ty
pe of
c
o
nt
r
o
l
l
e
r
Kp
Ti
Td
P 0.
50
Kc
r
∞
0
PI
0.
45
Kc
r
0.
83
Pc
r
0
PID
0.
60
Kc
r
0.
50
Pc
r
0.
12
5
Pcr
3.
R
ESU
LTS AN
D ANA
LY
SIS
V-La
b i
n
t
e
rfa
c
e
i
s
p
r
ese
n
t
e
d i
n
Fi
gu
re
5.
V
-
Lab al
s
o
pr
o
v
i
d
es a
q
u
est
i
o
n
n
ai
re
fo
r a
pi
l
o
t
st
udy
base
d
on
W
a
l
t
e
r
Di
c
k
a
n
d
L
o
u
C
a
r
e
y
'
s l
earni
ng
d
e
vel
o
pm
ent
m
odel, the
questionnaires
are
address
ed for a le
arni
ng
media experts
enrolled i
n
a
V-Lab as a
teacher, a
questionn
aire for a m
a
terial expe
rts e
n
rolled in a
V-La
b as
a
teacher, for the
learni
ng m
odel expe
rt
s e
n
rolled in the
V-La
b as
teachers,
questionnaire
s for the sm
all groups
enr
o
l
l
e
d i
n
t
h
e
V-La
b a
s
st
u
d
e
n
t
s
, a
n
d
quest
i
o
n
n
ai
res
fo
r field
trials enro
lled
in th
e
V-Lab
as stud
en
ts.
Fi
gu
re 5.
V
-
La
b Int
e
r
f
ace
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
70
8
Virtu
a
l Lab
o
rato
ry fo
r Lin
e
Fo
llo
wer Rob
o
t
Co
mp
etitio
n
(S
u
w
a
s
o
n
o
)
2
257
Med
i
a exp
e
rt v
a
lid
ation
d
a
ta were
ob
tain
ed fro
m
th
e
m
e
d
i
a Virtu
a
l Laborato
r
y
wh
ich
was lo
gg
ed
in
as a teacher or supe
rvisor
through a we
b questionnaire
onl
i
ne followe
r c
o
mm
unity consisted of t
w
o t
u
tors.
Th
e v
a
lid
ation
resu
lts
are
shown
in
Tab
l
e 3
.
Tabl
e
3. L
ear
ni
ng
M
e
di
a E
x
pe
rt
s Tri
a
l
s
Dat
a
No.
Asse
ss
me
nt Aspe
c
t
s
Asse
ss
me
nt Total
Ave
r
a
g
e Pe
rc
e
n
ta
ge
1. Learn
i
ng
media
effectiven
ess
8 assessment asp
ects
100 %
2.
Learn
i
ng m
e
di
a
attr
act
ivenes
s
5 as
s
e
s
s
m
ent as
p
ects
97.5 %
3.
Learn
i
ng m
e
di
a
effic
i
enc
y
4 as
s
e
s
s
m
ent as
p
ects
96.9 %
Total
17 assessment as
pects
98.5 %
Accord
ing
to
Tab
l
e 1
on
th
e feasib
ility lev
e
l crite
ria, th
e resu
lts ob
tain
ed
fro
m
th
e lea
r
n
i
n
g
m
e
d
i
a
expe
rts as a whole stated tha
t
the l
earning
media used in the learning is
very good. T
h
e avera
g
e score of the
wh
ol
e aspect
o
f
t
h
e assessm
ent
obt
ai
ne
d f
r
o
m
bot
h m
e
di
a
expe
rt
s am
oun
t
e
d t
o
98
.5%
. Hence
, i
t
can
be sai
d
t
h
at
t
h
e m
e
di
a
use
d
i
n
ba
si
c d
y
n
am
i
c
web
p
r
og
ram
m
i
ng l
e
a
r
ni
ng
usi
n
g
Vi
rt
ual
La
b
o
rat
o
r
y
m
odel
s
a
r
e
v
a
l
i
d
an
d
do
no
t
r
e
qu
ir
e r
e
v
i
si
o
n
.
The vali
dation data obtained from
web
m
e
dia Virt
ual Laboratory who
logged i
n
as a
teacher
or
supervisor of
t
h
e web
questi
onnaire
online
foll
owe
r
c
o
mm
unity as
m
u
ch as
four
teachers.
Acc
o
rding to the
Tab
l
e 4
wh
ich
refer to
th
e Tab
l
e 1
for
th
e criteria o
f
feasib
i
lity, th
e resu
lts o
f
bo
th
th
e overall
m
a
terial e
x
p
e
rts
stated
th
at th
e
mater
i
als d
e
v
e
lo
p
e
d
in
th
e
Vir
t
u
a
l Labo
r
a
t
o
r
y
d
e
sign
study
m
o
d
e
l d
e
f
i
ned
as ex
cellen
t
. Th
e
avera
g
e
perce
n
tage of the
overall assessm
e
n
t aspect
of
both m
aterial experts
obtained
89.7%.
Hence
,
it can
b
e
sai
d
th
at t
h
e m
a
teria
l
o
n
th
e
b
a
sic lin
e fo
llo
wer stand
a
rd of co
m
p
eten
ce
d
e
velop
e
d is v
a
lid and do
es
no
t
req
u
ire re
visio
n
.
Tab
el
4
.
Material Ex
p
e
rts Trials Data
No.
As
s
e
s
s
m
e
nt As
pects
Total
Average
P
e
rcen
t
a
ge
1. Learn
i
ng
media
material
10 Assessment aspects
83.75 %
2.
Learn
i
ng media
evalu
a
tion
3 Assessment as
pects
91.7 %
3.
Learn
i
ng m
e
di
a
effic
i
enc
y
and
ef
fect
ivenes
s
7 As
s
e
s
s
m
e
nt as
pects
93.75%
Tota
l
20
Asse
ss
me
nt aspects
89.7 %
The ex
pe
rt
eva
l
uat
i
on
of t
h
e l
earni
ng
desi
g
n
and m
odel
wa
s con
d
u
ct
ed t
o
enha
nce
Vi
rt
u
a
l
Labo
rat
o
ry
l
earni
n
g
m
ode
l
t
h
at
has
be
e
n
devel
o
p
e
d
.
The e
x
pert
val
i
dat
i
o
n
dat
a
of
l
earni
ng
m
odel
was
o
b
t
a
i
n
e
d
fr
om
Virtual La
bora
tory we
b in the
form
of a ques
tionnai
r
e of three teachers.
Ac
cording to the
Table 5
refe
rri
ng
t
o
Tab
l
e 1
on
th
e
feasib
ility lev
el criteria, th
e resu
lts ob
tain
ed
fro
m
th
e ex
p
e
rt o
f
t
h
e ov
erall learn
i
n
g
m
o
d
el
state
t
h
at
t
h
e desi
g
n
e
d Vi
rt
ual
Lab
o
rat
o
ry
l
earni
n
g
m
odel
m
eets
the assessm
ent criteria. The avera
g
e pe
rce
n
tage
obt
ai
ne
d wa
s 94
.8
%. He
nce,
i
t
can be sai
d
t
h
at
t
h
e desi
gn of t
h
e l
ear
ni
ng m
odel
of V
i
rt
ual
Labo
rat
o
ry
has
been
val
i
d
an
d req
u
i
r
e
no r
e
vi
si
o
n
. Tabl
e
6 sho
w
s t
h
e
resul
t
s
o
f
sm
al
l
grou
p t
r
i
a
l
s
t
o
UM
st
ude
nt
s of
Electrical En
g
i
n
eeri
n
g
Ed
u
cat
io
n
who
jo
in
ed
th
e tea
m
l
i
n
e fo
llower will b
e d
escri
b
ed. Th
e d
ata were tak
e
n
fr
om
10 st
ude
n
t
s.
Tabl
e
5.
Val
i
d
at
i
on
Dat
a
R
e
s
u
l
t
s
f
r
om
Lear
ni
n
g
M
odel
E
x
pert
s
o
n
Vi
rt
ua
l
Lab
o
rat
o
t
y
Asse
ss
me
nt Aspe
c
t
s
Object
ive (
%
)
Content(%)
Techno
log
y
(%)
Design (%)
Effectiven
ess
100
100
100
100
Attrac
tiven
ess
75
100
100
90
E
ffi
ci
e
n
cy
100
100
83.3
94.3
Tab
l
e 6
.
Sm
al
l
Gro
u
p
Trial
Resu
lt
Data
No.
As
s
e
s
s
m
e
nt As
pects
Total
Average
P
e
rcen
t
a
ge
1.
LMS
13 Assessment aspects
82.3%
2.
LMS Ma
te
ria
l
5 Asse
ssment as
pects
78.5 %
Tota
l
18
Asse
ss
me
nt aspects
80.4 %
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE
Vo
l. 7
,
N
o
. 4
,
Aug
u
s
t 2
017
:
22
53-
22
60
2
258
Based
on
th
e
resu
lt of d
a
ta
an
alysis, it is
d
i
scov
ered
tha
t
the avera
g
e t
o
tal scor
e
of the entire as
pe
cts of
assessm
en
t o
b
t
ain
e
d was
8
0
,4
%
referri
n
g
t
o
Tab
l
e
6
regard
i
n
g v
a
lid
ity
criteria.
In
this sm
al
l g
r
o
up trial,
therefore, t
h
e
developed LMS
can be
c
o
nfi
r
m
e
d
as val
i
d
.
Field trials are
an adva
nced
stag
e after a
sm
a
ll g
r
oup
trial was con
d
u
c
ted. In
th
is section
,
th
e resu
lts
o
f
field trials tested
to th
e
p
a
rticip
an
ts
o
f
lin
e
fo
llowe
r com
p
et
itio
n
as m
a
n
y
as
24
st
u
d
en
ts
will b
e
d
e
scrib
e
d
.
Th
e v
alid
ation
resu
lts are shown
in
Tab
l
e 7
.
After th
e
i
m
provem
e
nt
of t
h
e
LM
S, refer
r
i
n
g t
o
t
h
e sm
all
gr
o
u
p
trial resu
lts
d
a
ta (Tab
le 6), some p
r
ev
iou
s
asp
ects asse
ssm
ents are
consi
d
e
r
ed
valid
(r
ange 60
-79
%
). The f
ield
trials av
erag
e
p
e
rcen
tag
e
is
presen
te
d in
Ta
ble 7. T
h
e res
u
lts indicated th
at the m
e
dia is
confirm
e
d improve
d
and
i
t
can
be
c
onsi
d
ere
d
t
h
at
t
h
e ent
i
r
e
as
pe
ct
s of
t
h
e a
sses
s
m
e
nt
have
be
en
val
i
d
(ra
ng
e
8
0
-
1
00%
).
Tab
l
e 7
.
Field
Trial
Resu
lts Data
No.
As
s
e
s
s
m
e
nt As
pects
Total
Average
P
e
rcen
t
a
ge
1.
LMS
13 assessment as
pects
84.6%
2.
LM
S
M
a
teri
al
5 as
s
e
s
s
m
ent as
p
ects
84.2 %
Total
18 assessment as
pects
84.4 %
4.
RESULTS
A
N
D
DI
SC
US
S
ION
The
res
u
l
t
s
o
f
t
h
e m
a
t
e
ri
al
expe
rt
s, m
e
di
a ex
pert
s,
m
o
d
e
l
expe
rt
s,
sm
al
l
gr
ou
ps,
a
n
d
fi
el
d
were
an
alyzed
b
y
com
p
arin
g
th
e d
a
ta o
n
th
e
V-Lab
p
ilo
t pro
j
ect
[7
] as fo
llo
ws:
1.
M
e
di
a
Ex
pe
rt
The as
pect of a
ssessm
ent on
media attractiveness
obtai
ne
d 9
7
.5%. Th
is resu
lt was
ob
tain
ed
du
e to
lack of
an
im
a
tio
n
.
Wh
ile th
e
m
ed
i
a effici
ency obtained
96.9%
.
This num
b
er was obt
ai
ned
due t
o
l
ack
of
com
p
l
e
t
e
ness.
Aft
e
r
i
m
prove
m
e
nt
was c
o
nd
uct
e
d,
th
ere is
a 2
.
5
%
in
crease on
th
e resu
lt.
2.
M
a
t
e
ri
al
Expe
r
t
The as
pect of assessm
ent regarding m
a
te
rial obt
ain
e
d
8
3
.76
%
. Th
is resu
lt was
ob
tain
ed
si
n
ce
th
e
lan
g
u
a
g
e
u
tilizatio
n
o
n
t
h
e med
ia rem
a
in
s in
ad
equ
a
te. The ev
alu
a
tion
asp
ect ob
tain
ed
9
1
.7% wh
ich
was
obt
ai
ne
d
d
u
e t
o
f
eed
bac
k
pr
o
cess.
Wh
ile the efficien
cy asp
ect ob
tain
ed
9
3
.75
%
wh
ich was
ob
tain
ed
d
u
e
t
o
m
o
t
i
v
at
i
on.
Aft
e
r
i
m
prove
m
e
nt
on
t
h
e
m
e
di
a wa
s
co
ndu
cted
, it ob
tained
3
%
p
e
rcen
t
a
g
e
in
crease.
3.
M
odel
E
x
pert
s
The attractiveness aspect
o
b
t
a
i
n
ed
75%
due t
o
t
h
e l
ack
ness
on t
h
e o
b
jectives of the m
edia. The efficiency
asp
ect resu
lted
on
8
3
.3
%
sin
ce th
e flexib
ility re
m
a
in
s in
sign
ifican
t
.
After th
e i
m
p
r
o
v
e
m
e
n
t
was
conducted, it increase
d
7%
.
4
.
Sm
a
ll Group
Trial
In
sm
all g
r
o
u
p
trial, LMS o
b
t
ain
e
d
8
2
.3% wh
ich
was
d
u
e
t
o
th
e av
ailab
ility
o
f
tu
to
rial.
Wh
ile LM
S
Material o
b
t
ain
e
d
78
.5
% which
was
d
u
e
t
o
th
e
m
i
n
o
r
u
tilizatio
n
of p
i
ctu
r
e. After th
e
i
m
p
r
ov
em
en
t
was
co
ndu
cted
, it ob
tain
ed 6% in
crease.
Th
e results o
f
im
p
r
ov
emen
t o
n
field trial are
pres
ent
e
d i
n
Ta
bl
e 7
.
In ge
ne
ral
, t
h
e
expe
ri
m
e
nt
al
dat
a
val
i
d
at
i
o
n
of m
e
di
a expert
s, m
a
t
e
ri
al
expe
rt
s, sm
al
l gro
u
p
t
ri
a
l
s
,
an
d f
ield tr
ials
as show
n in
Fig
u
r
e
6
.
Fig
u
re
6
.
Trial
s
Resu
lts
Diagra
m
0,00%
20,00%
40,00%
60,00%
80,00%
100,00%
120,00%
Media
Learning
Learning
Material
Learning
Model
S
mall
Group
Field
Test
Re
s
u
l
t
s
of
V
‐
Lab
Ro
b
o
t
LF
Compe
t
ition
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
70
8
Virtu
a
l Lab
o
rato
ry fo
r Lin
e
Fo
llo
wer Rob
o
t
Co
mp
etitio
n
(S
u
w
a
s
o
n
o
)
2
259
It
obt
ai
ned
98
.
5
% o
f fi
nal
da
t
a
for m
e
di
a expe
rt
s,
89
.7%
fo
r m
a
t
e
ri
al
expe
rt
s,
94
.8 %
fo
r l
earni
ng
m
odel
expe
rt
s,
8
0
.
4
%
f
o
r
sm
all
gr
ou
p t
ri
a
l
s
,
an
d
8
4
.4%
f
o
r
fi
eld trials. Th
e av
erag
e
resu
lt
ob
tain
ed fro
m
th
e en
tire
expe
ri
m
e
nt
s perf
orm
e
d i
s
9
0
.
8
%. B
a
s
e
d
o
n
Ta
bl
e
1
on
t
h
e cri
t
e
ri
a
of
val
i
d
i
t
y
, t
h
e
ove
ral
l
desi
gn
of
t
h
e
l
earni
n
g
m
odel
of
Vi
rt
ual
La
bo
rat
o
ry
as we
l
l
as t
h
e com
p
one
nt
s o
f
l
ear
n
i
ng m
odel
i
n
t
h
e f
o
rm
of Le
arni
n
g
M
a
nagem
e
nt
S
y
st
em
and l
ear
ni
n
g
t
o
ol
s t
h
at
have
bee
n
de
v
e
l
ope
d a
r
e
val
i
d
a
n
d
d
o
n
o
t
re
qui
re a
revi
si
o
n
.
5.
CO
NCL
USI
O
N
Virtual La
bora
tory is a com
b
ination
of
face
-to-
face learni
ng a
n
d online
l
earning pos
se
ssing dive
rse
learn
i
ng
setting
s
.
Th
e
d
esi
gn
ed Virt
u
al Lab
o
ratory refe
rs to
t
h
e learnin
g
setting
th
at classifies in
to
fou
r
qua
drants learning settings
, nam
e
ly
(1) Live Sync
hronous,
(2) Vi
rtual Synchronous
, (3) Sel
f
-paced
asy
n
ch
ro
n
o
u
s
,
and
(4
) C
o
l
l
a
bo
rat
i
v
e asy
n
c
h
r
o
no
us. B
a
se
d o
n
t
h
e
p
r
oc
ess of
de
vel
o
p
m
ent
and a
n
al
y
s
i
s
of
trials
resu
lt
i
n
d
a
ta
th
at h
a
s been
co
ndu
cted,
it
can
b
e
d
r
awn
th
at
th
e d
e
v
e
lo
p
e
d
Virtu
a
l Labo
ratory
is feasib
le
to
u
s
e for sim
u
latin
g
th
e lin
e
fo
llower
robo
t co
m
p
etitio
n
.
Ho
wev
e
r, fu
rt
h
e
r d
e
v
elop
m
en
t, su
ch
as t
h
e con
t
ro
l
param
e
t
e
r co
ul
d
be
devel
ope
d
f
o
r
gai
n
i
n
g
m
o
re
real
resul
t
.
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I
S
SN
:
2
088
-87
08
I
J
ECE
Vo
l. 7
,
N
o
. 4
,
Aug
u
s
t 2
017
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22
53-
22
60
2
260
BIOGRAP
HI
ES OF
AUTH
ORS
Suwasono, is a
lecturer
in Electrical Eng
i
neer
in
g, Universitas N
e
geri M
a
lang
. H
e
finished
his
bachelor program in Electr
i
cal Engineeri
ng, I
K
IP Bandung, and his master degree from
Ele
c
tri
cal
Engi
neering
,
Unive
rsitas Gajah
Ma
da Yog
y
ak
a
r
ta. His resea
r
ch inter
e
st is
management of vocational
and engi
neer
ing educ
ation
,
es
pec
i
al
l
y
for both ele
c
tri
cal eng
i
ne
ering
and informatics.
Dwi P
r
ihanto, le
cturer and r
e
s
ear
cher in El
ec
tric
a
l
Engine
ering
,
Univers
i
t
a
s
Negeri M
a
lang, was
graduated from IKIP Surabay
a
for his bachelor
and from Univ
ersitas Negeri
Malang for his
m
a
s
t
er degree
. His
recent s
t
udy is
us
uall
y ab
out tea
c
hing an
d learning for
vocat
ional and
ele
c
tri
cal
eng
i
ne
ering educ
ation
,
Irawan Dwi W
a
h
y
ono
was fin
i
shed his b
achelor
from
El
ec
tr
ica
l
Eng
i
nee
r
in
g, Universi
tas
Brawijay
a
Malang in 2001. He h
a
s got a m
a
ster
degree on netwo
r
king com
putati
on from
In
stitut
Teknologi Sepu
luh September (ITS)
Surabay
a
. N
o
waday
s
, his res
earch
are more f
o
cusses on the
advanced n
e
twor
king based
comp
utation
.
Since 2003, And
rew Nafalski has
been a Professor
of Electrical Engineer
ing University
of South
Australia
. He
was a v
i
siting
pr
ofessor at v
a
rio
u
s universiti
es s
u
ch as Kan
a
z
a
w
a Universit
y
,
Toronto Univers
i
ty
, C
a
mbridge
and New York
University
. B
e
tween 25 Februar
y
2000
and 30
March 2006
,
Andrew was Professor and H
ead
of
School of Electrical
and Informatio
n
Engineering, University
of So
uth Australi
a.
His m
a
jor rese
arch in
ter
e
sts are re
la
ted to
ele
c
trom
agnet
i
cs
, m
a
gneti
c m
a
teria
l
s
and m
eas
urem
ents
, engin
eering inform
a
t
i
c
s
as
well as
innovativ
e meth
ods in engin
eering education
.
H
i
s
teaching
areas cover an
aly
s
is
and design
of
electrical circuits and
dev
i
ces, electromagnetic
compatibility
and
information
technolog
y
.
He has
published over 3
00 scholarly
works in the above
fields. He has r
eceived numero
u
s national and
intern
ation
a
l aw
ards
for exce
llen
ce in r
e
s
earch
, t
each
ing, eng
i
ne
e
r
ing educ
ation
a
nd com
m
unit
y
se
rvic
e.
Evaluation Warning : The document was created with Spire.PDF for Python.