I
A
E
S
I
n
t
e
r
n
at
io
n
al
Jou
r
n
al
of
A
r
t
if
ic
ia
l
I
n
t
e
ll
ig
e
n
c
e
(
I
J
-
A
I
)
V
ol
.
10
, N
o.
2
,
J
une
2021
, pp.
273
~
283
I
S
S
N
:
2252
-
8938
,
D
O
I
:
10.11591/
ij
a
i.
v
10
.i
2
.pp
273
-
283
273
Jou
r
n
al
h
om
e
page
:
ht
tp
:
//
ij
ai
.
ia
e
s
c
or
e
.c
om
H
yb
r
i
d
D
S
S
f
or
r
e
c
om
m
e
n
d
at
i
o
n
s of
h
al
al
c
u
l
i
n
ar
y t
ou
r
i
sm
We
st
S
u
m
at
r
a
M
ar
d
is
on
, A
gu
n
g R
am
ad
h
an
u
, L
ar
is
s
a N
avi
a R
an
i,
S
of
ik
a
E
n
ggar
i
Department of Information
Systems, C
omputer Science Facul
ty, Universitas
Putra Indonesia YP
TK
Padang
, Wes
t
Sumatra
, Indo
nesia
A
r
t
ic
le
I
n
f
o
A
B
S
T
R
A
C
T
A
r
ti
c
le
h
is
to
r
y
:
R
e
c
e
iv
e
d
M
a
r
3
, 20
20
R
e
vi
s
e
d
D
e
c
9
, 20
20
A
c
c
e
pt
e
d
M
a
r
2
0
, 20
21
Decision
support
system
(DSS)
is
a
system
that
design
to
support
m
anagers
in
deciding
on
multiple
criteria
and
multiple
attributes.
This
study
co
mbines
two
methods
in
the
DSS,
that
are
analytical
hierarchy
process
(AHP)
method
and
simple
additive
weighting
(SAW)
method.
This
combination
of
t
wo
DSS
method
named
hybrid
DSS.
The
AHP
method
is
using
to
find
the
we
ighti
ng
or
priorities
of
criteria
in
DSS
and
then
the
value
will
use
by
SAW
method
using to find the decision. The decision of this DSS is the recommend
ation of
halal
culinary
tourism
in
West
Sumatra
Indonesia.
The
purpose
of
thi
s
study
is
to
provide
updates
fr
om
previous
studies,
related
to
adding
indica
tors
of
halal
culinary
tourism
and
other
information
updates.
The
num
ber
of
potential
culinary
tourism
attractions
and
tourism,
the
problems
that
exist
in
the
real
field,
is
still
lack
of
culinary
information
in
West
Sumatra
.
As
a
result,
many
tourists
find
it
difficult
to
find
the
best
and
economi
cal
c
ulinary.
The
SAW
and
AHP
methods
become
the
hybrid
DSS
method
that
will
be
able
to
classify
and
provide
information
on
halal
tourism
in
West
S
umatra
that is prec
is
e, accurate,
consist
ent, and
validated
.
K
e
y
w
o
r
d
s
:
A
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy pr
oc
e
s
s
H
a
la
l
c
ul
in
a
r
y
H
ybr
id
D
S
S
S
im
pl
e
a
ddi
ti
ve
w
e
ig
ht
in
g
T
our
is
m
This is an
open
acce
ss artic
le unde
r the
CC BY
-
SA
license.
C
or
r
e
s
pon
di
n
g A
u
th
or
:
A
gung R
a
m
a
dha
nu
D
e
pa
r
tm
e
nt
of
I
nf
or
m
a
ti
on S
ys
te
m
C
om
put
e
r
S
c
ie
nc
e
F
a
c
ul
ty
U
ni
ve
r
s
it
a
s
P
ut
r
a
I
ndone
s
ia
Y
P
T
K
P
a
d
a
ng
J
l.
R
a
ya
L
ubuk B
e
g
a
lu
ng,
P
a
da
ng, S
um
a
te
r
a
B
a
r
a
t,
I
ndone
s
ia
E
m
a
il
:
a
gung_r
a
m
a
dha
nu@
upi
ypt
k.a
c
.i
d
1.
I
N
T
R
O
D
U
C
T
I
O
N
C
ul
in
a
r
y
to
ur
is
m
is
now
a
ty
pe
o
f
to
u
r
is
m
th
a
t
ha
s
m
uc
h
im
p
a
c
t
on
th
e
de
ve
lo
pm
e
nt
of
a
r
e
gi
on.
O
ne
of
th
e
c
r
i
ti
c
a
l
va
lu
e
s
is
to
de
ve
lo
p
th
e
pos
s
ib
il
it
y
of
a
ut
he
nt
ic
r
e
gi
ona
l
f
oods
th
a
t
s
e
e
m
to
ha
ve
be
gun
t
o
be
di
s
pl
a
c
e
d
by
f
or
e
ig
n
pr
oduc
ts
or
e
th
ni
c
c
ui
s
in
e
or
ie
nt
e
d.
F
or
th
is
r
e
a
s
on,
a
n
e
f
f
or
t
m
us
t
be
m
a
de
to
in
c
r
e
a
s
e
th
is
e
c
onomi
c
pot
e
nt
ia
l
by
pr
ovi
di
ng
to
uc
h
or
s
uppor
t
to
be
a
bl
e
to
a
tt
r
a
c
t
lo
c
a
l
or
f
or
e
ig
n
to
ur
is
ts
to
e
nj
oy
th
e
a
ut
he
nt
ic
r
e
gi
ona
l
c
ui
s
in
e
[
1]
.
D
u
r
in
g
th
is
ti
m
e
,
w
h
e
n
di
s
c
us
s
in
g
a
nd
s
how
in
g
th
e
lo
c
a
ti
on
of
th
e
c
ul
in
a
r
y
c
e
nt
e
r
,
of
te
n,
th
e
in
f
or
m
a
ti
on
obt
a
in
e
d
is
onl
y
li
m
i
te
d
to
th
e
s
tr
e
e
t
na
m
e
a
nd
th
e
di
r
e
c
ti
on
or
c
ha
r
a
c
te
r
is
ti
c
s
of
th
e
r
e
gi
on. T
he
c
la
r
it
y
of
th
e
c
ul
i
na
r
y
c
e
nt
e
r
l
oc
a
ti
on
is
not
m
a
ppe
d
c
or
r
e
c
tl
y
[
2]
.
S
tr
a
te
gi
c
,
in
e
xpe
ns
iv
e
,
a
nd
c
onve
ni
e
nt
f
ood
pl
a
c
e
s
a
r
e
one
of
th
e
f
in
a
l
c
om
pone
nt
s
in
de
te
r
m
in
in
g
th
e
de
s
ir
e
d
c
ul
in
a
r
y
lo
c
a
ti
on.
C
ul
in
a
r
y
to
ur
is
m
is
now
a
n
e
xc
it
in
g
th
in
g
in
to
ur
is
t
c
it
ie
s
s
uc
h
a
s
P
a
da
ng,
w
he
r
e
P
a
da
ng
is
a
c
it
y
a
nd,
a
t
th
e
s
a
m
e
ti
m
e
,
th
e
c
a
pi
ta
l
of
th
e
pr
ovi
nc
e
of
W
e
s
t
S
um
a
tr
a
,
I
ndone
s
ia
.
A
s
th
e
la
r
ge
s
t
c
it
y
in
t
he
pr
ovi
nc
e
of
W
e
s
t
S
um
a
tr
a
,
P
a
da
ng
is
f
il
le
d w
it
h
va
r
io
us
tr
ib
e
s
. W
it
h
th
os
e
v
a
r
io
us
ty
pe
s
of
e
th
ni
c
it
y
be
twe
e
n
e
th
ni
c
gr
oups
a
nd
c
ul
tu
r
e
s
,
f
ood
a
ppe
ti
te
is
s
ig
ni
f
ic
a
nt
in
de
te
r
m
in
in
g
th
e
lo
c
a
ti
on
a
nd
pl
a
c
e
to
e
a
t
in
th
e
c
it
y
of
P
a
da
ng.
U
ti
li
z
a
ti
on
of
th
e
m
ul
ti
-
a
tt
r
ib
ut
e
de
c
is
io
n
m
a
ki
ng
(
M
A
D
M
)
m
e
th
od
c
a
n
be
u
s
e
d
to
he
lp
pe
opl
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
10
, N
o.
2, J
une
20
21
:
273
–
283
274
m
a
ke
de
c
i
s
io
ns
qui
c
kl
y,
pr
e
c
is
e
ly
,
a
nd
c
on
s
is
te
nt
ly
[3
]
,
[
4]
.
M
A
D
M
is
s
pe
c
if
ic
a
ll
y
d
e
s
ig
ne
d
to
s
uppor
t
s
om
e
one
w
ho ha
s
t
o m
a
ke
i
ndi
vi
dua
l
de
c
is
io
n
s
[5
]
-
[
7]
.
M
A
D
M
is
a
br
a
nc
h
of
t
he
ope
r
a
ti
ons
r
e
s
e
a
r
c
h
m
ode
l
th
a
t
de
a
ls
w
it
h
de
c
is
io
n
m
a
ki
ng.
T
he
im
pl
e
m
e
nt
a
ti
on
of
th
is
m
e
th
od
is
u
s
e
d
to
f
in
d
th
e
be
s
t
opi
ni
o
n
f
r
om
s
e
ve
r
a
l
a
lt
e
r
na
ti
ve
s
,
w
hi
c
h
c
ont
r
a
di
c
t
e
a
c
h
ot
he
r
ba
s
e
d
on
th
e
de
c
i
s
io
n
c
r
it
e
r
ia
.
T
hi
s
m
ode
l
is
us
ua
ll
y
us
e
d
to
s
e
le
c
t
a
l
im
it
e
d
num
be
r
of
a
lt
e
r
na
ti
ve
s
.
D
e
c
is
io
n
s
uppor
t
s
ys
te
m
s
a
r
e
ve
r
y
w
e
ll
im
pl
e
m
e
nt
e
d
to
s
ol
ve
s
e
m
i
-
s
tr
uc
tu
r
e
d
pr
obl
e
m
s
.
I
n
c
onduc
ti
ng
a
n
a
s
s
e
s
s
m
e
nt
us
ua
ll
y
us
e
s
li
ngui
s
ti
c
pr
e
f
e
r
e
nc
e
s
.
T
hi
s
s
tu
dy
tr
ie
s
to
a
ppl
y
a
c
om
bi
na
ti
on
of
a
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy
pr
oc
e
s
s
(
A
H
P
)
[
8]
a
nd
s
im
pl
e
a
ddi
ti
ve
w
e
ig
ht
in
g
(
S
A
W
)
[
9
]
m
e
th
ods
in
m
a
ki
ng
ha
la
l
c
ul
in
a
r
y t
our
is
m
r
e
c
om
m
e
nda
ti
ons
i
n W
e
s
t
S
um
a
tr
a
.
T
he
A
H
P
m
e
th
od
w
a
s
de
ve
lo
pe
d
by
S
a
a
ty
a
nd
is
us
e
d
to
s
ol
ve
c
om
pl
e
x
pr
obl
e
m
s
w
he
r
e
th
e
r
e
is
ve
r
y
li
tt
le
da
ta
,
a
nd
s
t
a
ti
s
ti
c
a
l
in
f
or
m
a
ti
on
on
th
e
pr
obl
e
m
f
a
c
e
d.
A
H
P
m
e
th
od,
w
hi
c
h
is
of
te
n
a
ls
o
known
a
s
th
e
te
r
m
A
H
P
i
s
a
f
or
m
of
de
c
i
s
io
n
-
m
a
ki
ng
m
ode
l
w
it
h
m
ul
ti
pl
e
c
r
it
e
r
ia
[
10]
.
O
ne
of
A
H
P
'
s
r
e
li
a
bi
li
ti
e
s
is
th
a
t
it
c
a
n
c
a
r
r
y
out
s
im
ul
ta
ne
ous
a
nd
in
te
gr
a
te
d
a
n
a
ly
z
e
s
of
q
ua
li
ta
ti
ve
or
e
ve
n
qua
nt
it
a
ti
ve
p
a
r
a
m
e
te
r
s
.
T
he
le
a
di
ng
e
qui
pm
e
nt
of
th
is
m
ode
l
is
a
f
unc
ti
ona
l
hi
e
r
a
r
c
hy
w
i
th
th
e
pr
im
a
r
y
in
put
is
hum
a
n
pe
r
c
e
pt
i
on.
A
c
om
pl
e
x
a
nd
un
s
tr
uc
tu
r
e
d
pr
obl
e
m
is
br
oke
n
dow
n
in
to
gr
oups
,
a
nd
th
e
gr
oups
be
c
om
e
a
f
or
m
of
hi
e
r
a
r
c
hy
[
11]
.
T
he
pr
oc
e
s
s
c
a
r
r
ie
d
out
by
th
e
S
A
W
m
e
th
od
in
m
a
ki
ng
de
c
i
s
io
ns
is
known
a
s
th
e
w
e
ig
ht
e
d
s
um
m
e
th
od.
T
he
ba
s
ic
c
onc
e
pt
of
S
A
W
m
e
th
od
is
to
f
in
d
a
w
e
ig
ht
e
d
s
um
of
th
e
pe
r
f
or
m
a
nc
e
r
a
ti
ngs
f
or
e
a
c
h
a
lt
e
r
na
ti
ve
on
a
ll
a
tt
r
ib
ut
e
s
[
12]
.
O
n
th
e
is
s
ue
of
th
is
s
tu
dy
a
bo
ut
th
e
uns
ui
ta
bl
e
hous
e
,
r
e
nov
a
ti
on
a
s
s
is
ta
nc
e
is
di
s
ti
ngui
s
he
d
by
s
e
ve
r
a
l
a
s
s
e
s
s
m
e
nt
c
r
it
e
r
ia
,
na
m
e
ly
:
th
e
c
on
di
ti
on
of
th
e
hous
e
,
th
e
num
be
r
of
de
pe
nde
nt
s
pa
r
e
nt
s
,
w
or
ki
ng
pa
r
e
nt
s
,
th
e
num
be
r
of
in
c
om
e
pa
r
e
nt
s
,
th
e
s
ta
tu
s
of
th
e
c
hi
ld
.
B
a
s
e
d
on
th
e
a
s
s
e
s
s
m
e
nt
c
r
it
e
r
ia
de
te
r
m
in
e
d
a
bove
,
e
a
c
h
of
th
e
s
e
c
r
it
e
r
ia
c
a
n
b
e
w
e
ig
ht
e
d,
r
e
qui
r
e
s
a
pr
oc
e
s
s
of
nor
m
a
li
z
a
ti
on
of
th
e
de
c
is
io
n
m
a
tr
ix
to
a
s
c
a
le
th
a
t
c
a
n
c
om
pa
r
e
w
it
h a
ll
a
lt
e
r
na
ti
ve
s
r
a
ti
ng
a
va
il
a
bl
e
,
th
e
n
do
th
e
r
a
nki
ng
pr
oc
e
s
s
.
W
it
h
th
e
r
a
nki
ng
m
e
th
od,
it
i
s
e
xpe
c
te
d
th
a
t
th
e
a
s
s
e
s
s
m
e
nt
w
il
l
be
m
or
e
pr
e
c
is
e
be
c
a
us
e
it
is
ba
s
e
d
on
a
pr
e
de
te
r
m
in
e
d
c
r
it
e
r
io
n
a
nd
w
e
ig
ht
s
o
th
a
t
it
w
il
l
ge
t
m
or
e
a
c
c
ur
a
te
r
e
s
ul
ts
on
w
ho
w
il
l
r
e
c
e
iv
e
uns
ui
ta
bl
e
hous
e
r
e
nova
ti
on a
s
s
is
ta
nc
e
[
13
]
,
[
14]
.
R
e
c
a
pi
tu
la
ti
on
of
d
a
ta
c
ol
le
c
ti
on
us
e
d
th
e
m
e
th
od
of
di
r
e
c
t
in
te
r
vi
e
w
s
by
r
e
s
e
a
r
c
h
e
r
s
to
o
w
ne
r
s
of
r
e
s
ta
ur
a
nt
s
in
W
e
s
t
S
um
a
tr
a
.
T
he
da
ta
c
ol
le
c
te
d
w
e
r
e
ba
s
e
d
on
ni
ne
pr
e
de
te
r
m
in
e
d
e
va
lu
a
ti
on
c
r
it
e
r
ia
.
T
he
y
a
r
e
ha
la
l
c
e
r
ti
f
ic
a
te
s
is
s
u
e
d
by
M
aj
e
li
s
U
la
m
a
I
ndone
s
ia
(
M
U
I
)
/I
ndone
s
ia
U
la
m
a
C
om
m
it
te
e
ow
ne
d
by
r
e
s
ta
ur
a
nt
s
w
he
th
e
r
th
e
ir
s
ta
tu
s
is
th
e
r
e
,
is
be
in
g
pr
oc
e
s
s
e
d
or
not
.
T
he
ot
he
r
c
r
it
e
r
ia
a
r
e
a
va
il
a
bl
e
f
ood
a
nd
be
ve
r
a
ge
s
p
e
c
if
ic
a
ti
ons
,
f
a
vor
it
e
f
oods
,
f
a
vor
it
e
dr
in
ks
,
num
be
r
of
vi
s
it
or
s
pe
r
da
y,
f
ood
pr
ic
e
s
,
a
g
e
s
e
gm
e
nt
s
of
vi
s
it
or
s
,
f
a
c
il
it
ie
s
,
a
nd
onl
in
e
in
de
xe
s
.
T
he
num
be
r
of
r
e
s
ta
ur
a
nt
s
vi
s
it
e
d
by
r
e
s
e
a
r
c
he
r
s
w
a
s
a
s
m
uc
h
a
s
+
51
in
W
e
s
t
S
um
a
tr
a
.
E
a
c
h
r
e
s
ta
ur
a
nt
vi
s
it
e
d
ha
s
it
s
a
dva
nt
a
g
e
s
,
s
uc
h
a
s
th
e
G
r
il
le
d
F
is
h
H
a
r
u
R
e
s
ta
ur
a
nt
,
w
hi
c
h
s
pe
c
if
ic
a
ti
ons
a
r
e
G
ur
a
m
i
gr
il
le
d
f
is
h,
T
il
a
pi
a
gr
il
le
d
f
is
h,
C
or
a
l
s
e
a
gr
il
le
d
f
is
h.
W
he
r
e
a
s
th
e
f
ir
s
t
L
a
m
un
O
m
ba
k
R
e
s
t
a
ur
a
nt
lo
c
a
te
d
on
S
tr
e
e
t
S
.
P
a
r
m
a
n
N
o.
2
32
A
U
la
k
K
a
r
a
ng,
w
hi
c
h
ha
s
two
br
a
n
c
he
s
,
na
m
e
ly
S
tr
e
e
t
K
ha
ti
b
S
ul
a
im
a
n N
o.
99
a
nd
P
a
da
ng B
uki
tt
in
ggi
K
m
.
24,
ha
ve
di
f
f
e
r
e
nt
s
pe
c
if
ic
a
ti
ons
,
na
m
e
ly
S
na
ppe
r
F
is
h C
ur
r
y, f
r
ie
d c
hi
c
ke
n, pop
c
hi
c
ke
n, be
e
f
s
oup, s
pi
c
y a
nd s
our
m
e
a
t,
s
hr
im
p, a
nd othe
r
s
.
H
ybr
id
de
c
is
io
n
s
uppor
t
s
ys
te
m
(
H
D
S
S
)
w
it
h
th
e
m
e
th
od
of
a
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy
pr
oc
e
s
s
(
A
H
P
)
a
nd
s
im
pl
e
a
ddi
ti
ve
w
e
ig
ht
in
g
(
S
A
W
)
in
r
e
c
e
nt
ye
a
r
s
is
in
c
r
e
a
s
in
gl
y
be
in
g
us
e
d
in
r
e
s
e
a
r
c
h.
T
h
e
c
om
bi
na
ti
on
of
th
e
s
e
t
w
o m
e
th
ods
i
s
ve
r
y c
lo
s
e
ly
r
e
la
te
d t
o s
ol
ve
t
he
s
e
m
i
-
s
tr
u
c
tu
r
e
d pr
obl
e
m
i
n
t
he
de
c
is
io
n
-
m
a
ki
ng s
ys
te
m
[
15]
. T
he
a
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy pr
oc
e
s
s
m
e
th
od i
s
known a
s
a
hi
e
r
a
r
c
h
ic
a
l
pa
ir
w
is
e
c
om
pa
r
is
on c
r
it
e
r
io
n a
nd i
s
ve
r
y
c
ons
is
te
nt
in
de
te
r
m
in
in
g
pr
io
r
it
y
or
w
e
ig
ht
va
lu
e
s
us
in
g
t
he
c
ons
is
te
n
c
y
r
a
ti
o
f
or
m
ul
a
if
C
R
<
0.1,
th
e
n
th
e
pa
ir
w
is
e
c
om
pa
r
is
on va
lu
e
s
a
r
e
c
ons
i
s
te
nt
[
16
]
,
[
17]
. T
he
w
e
ig
ht
va
lu
e
w
il
l
be
us
e
d l
a
te
r
i
n t
he
s
um
of
t
he
pr
e
f
e
r
e
nc
e
va
lu
e
s
us
in
g
th
e
S
A
W
m
e
th
od
[
18
]
,
[
19]
.
T
he
S
A
W
m
e
th
od
is
known
a
s
th
e
w
e
ig
ht
in
g
s
um
th
r
ough
th
e
c
a
lc
ul
a
ti
on
of
th
e
nor
m
a
li
z
a
ti
on
m
a
tr
ix
,
a
nd
th
e
f
in
a
l
r
a
nki
ng
r
e
s
ul
ts
w
he
r
e
th
e
va
lu
e
of
th
e
hi
ghe
s
t
a
lt
e
r
na
ti
ve
i
s
c
ho
s
e
n a
s
t
he
be
s
t
s
ol
ut
io
n.
T
he
s
ol
ut
io
n
of
th
e
c
om
bi
na
ti
on
of
th
e
A
H
P
m
e
th
od
a
nd
S
A
W
us
e
d
in
pr
oc
e
s
s
in
g
ha
l
a
l
c
ul
in
a
r
y
to
ur
is
m
da
ta
in
W
e
s
t
S
um
a
tr
a
c
a
n
r
e
c
om
m
e
nd
s
e
ve
r
a
l
h
a
la
l
l
a
be
le
d
r
e
s
ta
ur
a
nt
s
[
20
]
,
[
21]
.
T
he
r
e
s
t
a
ur
a
nt
s
ha
ve
good f
ood a
nd dr
in
k
s
pe
c
if
ic
a
ti
ons
, m
a
ny vis
it
or
s
, c
om
pl
e
te
f
a
c
il
it
ie
s
, a
nd a
f
f
or
da
bl
e
pr
ic
e
s
. T
hi
s
H
D
S
S
s
ys
te
m
is
im
pl
e
m
e
nt
e
d
in
to
a
n
a
ndr
oi
d
m
obi
le
a
ppl
ic
a
ti
on
th
a
t
c
a
n
e
a
s
e
vi
s
it
or
s
of
W
e
s
t
S
um
a
tr
a
to
de
te
r
m
in
e
ha
la
l
c
ul
in
a
r
y t
o
ur
is
m
e
a
s
il
y.
T
he
pur
pos
e
of
t
hi
s
s
tu
dy i
s
t
o pr
ovi
de
r
e
c
om
m
e
nda
ti
ons
t
o t
ou
r
is
ts
i
n f
in
di
ng ha
la
l
f
ood in
a
s
pe
c
ia
l
pl
a
c
e
in
th
e
W
e
s
t
S
um
a
tr
a
a
r
e
a
of
I
ndone
s
ia
.
W
it
h
th
is
D
S
S
,
to
ur
is
ts
w
ho
a
r
e
not
f
a
m
il
ia
r
w
it
h
th
e
W
e
s
t
S
um
a
tr
a
r
e
gi
on
w
il
l
f
in
d
it
e
a
s
ie
r
to
f
in
d
ha
la
l
c
ui
s
in
e
in
th
e
a
r
e
a
.
T
he
r
e
c
om
m
e
nda
ti
on
is
obt
a
in
e
d
f
r
om
th
e
c
a
lc
ul
a
ti
on
us
e
d
in
th
e
D
S
S
m
e
th
od
by
us
in
g
a
c
om
bi
na
ti
on
of
th
e
A
H
P
a
nd
S
A
W
m
e
th
ods
s
o
it
is
c
a
ll
e
d
H
ybr
id
D
S
S
.
A
H
P
m
e
th
od
is
us
e
d
to
de
te
r
m
in
e
th
e
w
e
ig
ht
of
e
a
c
h
c
r
it
e
r
io
n
th
e
n
th
e
S
A
W
m
e
th
od
is
us
e
d
to
c
a
lc
ul
a
te
th
e
de
c
i
s
io
n.
T
he
da
t
a
in
th
is
s
tu
dy
w
e
r
e
ta
ke
n
f
r
om
a
ll
f
a
m
ous
ha
la
l
r
e
s
ta
ur
a
nt
s
lo
c
a
te
d
in
W
e
s
t
S
um
a
tr
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
H
y
br
id
D
SS f
or
r
e
c
om
m
e
ndat
io
ns
of
hal
al
c
ul
in
ar
y
t
our
i
s
m
W
e
s
t
Sum
at
r
a
(
M
ar
di
s
on
)
275
2.
R
E
S
E
A
R
C
H
M
E
T
H
O
D
T
o
gui
de
th
e
pr
e
pa
r
a
ti
on
of
th
e
s
tu
dy,
it
is
ne
c
e
s
s
a
r
y
to
h
a
ve
a
br
ig
ht
f
r
a
m
e
w
or
k
f
or
th
e
s
ta
ge
s
.
A
t
th
e
be
gi
nni
ng
w
e
do
is
de
te
r
m
in
e
th
e
de
f
in
it
io
n
o
f
th
e
pr
ob
le
m
.
N
e
xt
,
w
e
di
d
a
li
te
r
a
tu
r
e
r
e
vi
e
w
.
A
f
te
r
unde
r
s
ta
ndi
ng
th
e
pr
obl
e
m
s
a
nd
r
e
vi
e
w
in
g
th
e
li
te
r
a
tu
r
e
w
e
c
ol
le
c
t
da
ta
a
nd
in
f
or
m
a
ti
on
in
th
e
f
ie
ld
.
F
ur
th
e
r
m
or
e
,
th
e
da
ta
th
a
t
ha
s
be
e
n
c
ol
le
c
te
d
i
s
pr
oc
e
s
s
e
d
us
i
ng
a
H
D
S
S
w
it
h
th
e
A
H
P
a
nd
S
A
W
m
e
th
ods
.
A
f
te
r
th
e
r
e
s
ul
ts
a
r
e
obt
a
in
e
d,
im
pl
e
m
e
nt
a
nd
e
va
lu
a
te
th
e
s
ys
te
m
.
T
he
F
ig
ur
e
1
is
a
r
e
s
e
a
r
c
h
f
r
a
m
e
w
or
k
th
a
t
w
e
c
onduc
te
d.
F
ig
ur
e
1
.
R
e
s
e
a
r
c
h
f
r
a
m
e
w
or
k
1.
D
e
f
in
it
io
n a
nd gr
oup pr
obl
e
m
s
a.
G
r
oup
pr
obl
e
m
.
T
he
m
a
in
th
in
g
th
a
t
m
us
t
be
de
te
r
m
in
e
d
in
th
e
de
f
in
it
io
n
of
s
e
gm
e
nt
a
ti
on
a
nd
gr
oupi
ng
of
pr
obl
e
m
s
li
e
s
in
w
he
n
th
e
r
e
s
e
a
r
c
he
r
w
a
nt
s
to
m
a
ke
a
s
e
l
e
c
ti
on
a
nd
gr
oupi
ng
o
f
pr
obl
e
m
s
to
be
s
tu
di
e
d
be
c
a
u
s
e
w
it
h
th
a
t
it
c
a
n
he
lp
r
e
s
e
a
r
c
he
r
s
to
f
oc
us
a
nd
f
a
c
il
it
a
te
r
e
s
e
a
r
c
he
r
s
on
w
ha
t
pr
obl
e
m
s
th
e
y w
a
nt
t
o s
ol
ve
or
c
r
e
a
te
s
ol
ut
io
n
s
[
22]
.
b.
F
or
m
ul
a
ti
o
n
of
th
e
pr
obl
e
m
.
A
f
te
r
th
e
r
e
s
e
a
r
c
he
r
ha
s
gr
oup
e
d
th
e
pr
obl
e
m
,
w
ha
t
to
do
ne
xt
i
s
to
f
or
m
ul
a
te
th
e
pr
obl
e
m
by
in
s
e
r
ti
ng
it
in
to
th
e
pr
obl
e
m
c
lu
s
te
r
t
a
bl
e
,
to
c
r
e
a
te
s
om
e
c
or
e
pr
obl
e
m
it
e
m
s
th
a
t
w
il
l
be
f
or
m
e
d i
nt
o t
he
f
or
m
ul
a
ti
on o
f
t
he
pr
obl
e
m
[
23
]
.
c.
O
bj
e
c
ti
ve
.
B
a
s
e
d
on
th
e
f
or
m
ul
a
ti
on
of
th
e
pr
obl
e
m
s
,
th
e
obj
e
c
ti
ve
pha
s
e
is
us
e
f
ul
to
c
la
r
if
y
th
e
f
r
a
m
e
w
or
k t
a
r
ge
te
d f
r
om
t
hi
s
r
e
s
e
a
r
c
h. O
bj
e
c
ti
ve
s
a
r
e
w
ha
t
is
t
he
s
ol
ut
io
n t
ha
t
w
il
l
be
pr
oduc
e
d t
o s
ol
ve
th
e
pr
obl
e
m
s.
2.
L
it
e
r
a
tu
r
e
r
e
vi
e
w
I
n s
tu
dyi
ng l
it
e
r
a
tu
r
e
s
tu
di
e
s
, t
he
r
e
a
r
e
t
w
o s
ta
ge
s
:
a.
C
onduc
ti
ng
li
te
r
a
tu
r
e
s
tu
di
e
s
by
s
ta
r
ti
ng
f
r
om
th
e
c
om
pl
e
t
io
n
of
id
e
nt
i
f
ic
a
ti
on
a
nd
g
r
oupi
ng
o
f
pr
obl
e
m
s
,
th
e
th
in
g
done
is
to
lo
ok
f
or
li
te
r
a
c
y
jo
ur
na
ls
,
pr
oc
e
e
di
ngs
,
a
nd
books
a
bo
ut
th
e
A
H
P
m
e
th
od
a
nd t
he
S
A
W
m
e
th
od;
i
t
is
us
e
f
ul
t
o obta
in
r
e
f
e
r
e
nc
e
s
a
nd l
it
e
r
a
tu
r
e
t
ha
t
s
uppor
ts
t
he
r
e
s
e
a
r
c
h pr
oc
e
s
s
.
b.
F
ie
ld
s
tu
dy/
s
e
a
r
c
h da
ta
google
,
f
ie
ld
s
tu
di
e
s
/s
e
a
r
c
h da
ta
google
th
a
t
th
e
a
ut
hor
s
do, na
m
e
ly
:
−
O
bs
e
r
va
ti
on
a
nd
in
te
r
vi
e
w
,
n
a
m
e
ly
,
c
onduc
ti
ng
a
di
r
e
c
t
que
s
ti
on
a
nd
a
ns
w
e
r
w
it
h
one
of
th
e
r
e
s
e
a
r
c
h
s
ubj
e
c
ts
r
e
s
pon
s
ib
le
f
or
m
a
na
gi
ng t
he
r
e
s
e
a
r
c
h obje
c
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
10
, N
o.
2, J
une
20
21
:
273
–
283
276
−
S
e
a
r
c
hi
ng
in
f
or
m
a
ti
on
a
nd
r
a
nki
ng
th
e
r
e
s
e
a
r
c
h
obj
e
c
t,
th
is
i
s
th
e
pow
e
r
a
nd
e
f
f
or
t
of
r
e
s
e
a
r
c
he
r
s
to
obt
a
in
R
e
s
our
c
e
I
nf
or
m
a
ti
o
n
th
a
t
c
a
n
be
pr
oc
e
s
s
e
d
a
s
r
e
s
e
a
r
c
h
m
a
te
r
ia
l
to
m
a
ke
it
m
or
e
r
e
a
l
a
nd
c
om
pl
e
x.
3.
D
a
ta
c
ol
le
c
ti
on a
nd i
nf
or
m
a
ti
on
A
f
te
r
w
e
do
a
li
te
r
a
tu
r
e
r
e
vi
e
w
a
s
good
e
nough,
th
e
n
w
e
s
ho
ul
d
c
ol
le
c
t
th
e
da
ta
a
nd
in
f
or
m
a
ti
on
f
r
om
th
e
f
ie
ld
.
T
he
da
ta
a
nd
in
f
or
m
a
ti
on
th
a
t
w
e
c
ol
le
c
t
a
r
e
a
bout
ha
la
l
c
ul
in
a
r
y
to
ur
is
m
in
W
e
s
t
S
um
a
tr
a
I
ndone
s
ia
.
4.
C
r
e
a
te
s
ol
ut
io
n H
D
S
S
I
n c
r
e
a
te
s
ol
ut
io
n H
D
S
S
, t
he
r
e
a
r
e
t
hr
e
e
s
ta
ge
s
:
a.
D
e
s
ig
n
th
e
H
ybr
id
M
e
th
od
.
B
e
c
a
u
s
e
th
is
s
tu
dy
is
hybr
id
D
S
S
t
he
n
w
e
us
e
two
d
e
s
ig
ns
of
D
S
S
th
e
y
a
r
e
a
de
s
ig
n of
D
S
S
us
in
g A
H
P
M
e
th
od a
f
te
r
t
ha
t
c
ont
in
ue
d de
s
ig
n
of
D
S
S
us
in
g S
A
W
M
e
th
od.
−
A
H
P
M
e
th
od
.
T
he
A
H
P
M
e
th
od
is
a
n
a
c
r
onym
of
A
na
ly
ti
c
a
l
H
ie
r
a
r
c
hy
P
r
oc
e
s
s
M
e
th
od.
T
he
A
H
P
M
e
th
od
is
th
e
f
ir
s
t
m
e
th
od
us
e
d
to
de
s
ig
n
th
is
hybr
id
D
S
S
.
T
he
A
H
P
m
e
th
od
is
us
i
ng
to
f
in
d
th
e
w
e
ig
ht
in
g or
pr
io
r
it
ie
s
of
t
hi
s
hybr
id
D
S
S
.
−
S
A
W
M
e
th
od.
T
he
S
A
W
M
e
th
od
is
a
n
a
c
r
onym
of
S
im
pl
e
A
ddi
ti
ve
W
e
ig
ht
e
d
M
e
th
od.
T
he
S
A
W
M
e
th
od
is
th
e
s
e
c
ond
m
e
th
od
us
e
d
to
de
s
ig
n
hybr
id
D
S
S
.
T
he
S
A
W
m
e
th
od
us
in
g
th
e
w
e
ig
ht
in
g
o
r
pr
io
r
it
ie
s
t
ha
t
ha
ve
be
e
n f
ound by AH
P
m
e
th
od t
o f
in
d t
he
de
c
is
io
n of
hybr
id
D
S
S
.
b.
T
he
I
m
pl
e
m
e
nt
a
ti
on of
A
H
P
M
e
th
od:
T
o i
m
pl
e
m
e
nt
a
ti
on t
he
A
H
P
m
e
th
od w
e
ne
e
d 5
s
te
ps
, n
a
m
e
ly
:
−
C
r
e
a
te
a
hi
e
r
a
r
c
hy
s
tr
uc
tu
r
e
f
r
om
to
p
to
bot
to
m
.
T
he
hi
e
r
a
r
c
hy s
tr
uc
tu
r
e
is
f
r
om
to
p
to
bot
to
m
,
f
r
om
th
e
to
p hi
e
r
a
r
c
hy i
s
obj
e
c
ti
ve
s
t
he
be
lo
w
l
a
ye
r
i
s
c
r
it
e
r
ia
of
D
S
S
a
nd t
he
l
a
s
t
bot
to
m
l
a
ye
r
i
s
a
lt
e
r
na
ti
ve
s
t
ha
t
w
il
l
c
hoos
e
i
n t
he
D
S
S
.
−
M
a
ke
a
p
a
ir
w
is
e
c
om
pa
r
is
on
m
a
tr
ix
of
c
r
it
e
r
ia
.
T
he
va
lu
e
of
th
e
pa
ir
w
is
e
c
om
pa
r
is
on
of
c
r
it
e
r
ia
a
nd
th
e
v
a
lu
e
of
pa
ir
w
is
e
c
om
pa
r
is
on
c
a
m
e
f
r
om
th
e
he
a
d
or
pr
in
c
ip
a
l
or
e
xpe
r
t
a
bout
th
e
pr
obl
e
m
.
I
n
th
is
s
tu
dy,
th
e
c
r
it
e
r
ia
of
ha
la
l
c
ul
in
a
r
y
to
u
r
is
m
a
nd
th
e
va
lu
e
of
pa
ir
w
is
e
c
om
pa
r
is
on
c
a
m
e
f
r
om
I
ndone
s
ia
U
la
m
a
C
ounc
il
(
M
U
I
)
R
e
gi
on W
e
s
t
S
um
a
tr
a
.
−
C
a
lc
ul
a
ti
ng
th
e
w
e
ig
ht
in
g
of
m
a
tr
ix
be
twe
e
n c
r
it
e
r
ia
a
nd
pr
io
r
it
ie
s
.
C
a
l
c
ul
a
ti
ng
th
e
va
lu
e
in
a
w
a
y
u
s
in
g
th
e
pa
ir
w
is
e
c
om
p
a
r
is
on
ta
bl
e
.
E
a
c
h
va
lu
e
i
s
a
di
vi
de
w
it
h
th
e
s
um
m
in
g
of
e
ve
r
y
c
ol
um
n
a
t
th
a
t
va
lu
e
e
xi
s
t.
−
C
a
lc
ul
a
te
th
e
a
ddi
ti
on
m
a
tr
ix
f
or
e
a
c
h
r
ow
or
c
a
lc
ul
a
t
e
th
e
e
ig
e
nve
c
to
r
s
of
e
a
c
h
pa
ir
e
d
c
om
pa
r
is
on
m
a
tr
ix
. T
he
e
ig
e
nve
c
to
r
s
d
e
te
r
m
in
e
t
he
c
ons
is
t
e
nc
y r
a
ti
o.
−
T
hi
s
c
a
l
c
ul
a
ti
on i
s
done
t
o e
n
s
ur
e
t
ha
t
th
e
va
lu
e
of
t
he
C
on
s
is
te
nc
y R
a
ti
o (
C
R
)
≤ 0.1
c.
T
he
I
m
pl
e
m
e
nt
a
ti
on of
S
A
W
M
e
th
od
−
S
e
le
c
t
a
nd
D
e
te
r
m
in
e
C
r
it
e
r
ia
a
s
a
r
e
f
e
r
e
nc
e
f
or
D
e
c
is
io
n
M
a
ki
ng
.
T
he
c
r
it
e
r
ia
in
S
A
W
m
e
th
od
is
th
e
s
a
m
e
w
it
h A
H
P
m
e
th
od s
o t
ha
t
w
e
don’
t
ne
e
d t
o m
a
ke
ne
w
c
r
it
e
r
ia
.
−
D
e
te
r
m
in
e
th
e
r
a
ti
ng
o
f
e
a
c
h
a
lt
e
r
na
ti
ve
on
e
a
c
h
c
r
it
e
r
io
n
.
T
he
r
a
ti
ng
of
e
a
c
h
a
lt
e
r
na
ti
ve
w
e
us
e
th
e
pr
io
r
it
ie
s
va
lu
e
t
ha
t
th
e
r
e
s
ul
t
f
r
om
A
H
P
m
e
th
od.
−
M
a
ke
a
de
c
is
io
n
ba
s
e
d
on
c
r
it
e
r
ia
,
a
nd
th
e
n
nor
m
a
li
z
e
th
e
m
a
t
r
ix
ba
s
e
d
on
a
n
e
qua
ti
on
th
a
t
is
a
dj
us
te
d
to
th
e
ty
pe
of
a
tt
r
ib
ut
e
p
r
of
it
o
r
c
os
t
.
T
he
be
ne
f
it
c
r
it
e
r
ia
a
nd
c
os
t
c
r
it
e
r
ia
a
r
e
de
te
r
m
in
e
d
by
th
e
he
a
d
or
pr
in
c
ip
a
l
or
e
xpe
r
t
a
bout
t
he
pr
obl
e
m
. T
he
f
or
m
ul
a
t
ha
t
us
in
g t
o nor
m
a
li
z
e
t
he
m
a
tr
ix
of
c
r
it
e
r
ia
na
m
e
ly
:
B
e
ne
f
it
C
r
it
e
r
ia
:
C
os
t
C
r
it
e
r
ia
:
−
T
he
f
in
a
l
r
e
s
ul
t
is
obt
a
in
e
d
f
r
om
th
e
r
a
nki
ng
pr
oc
e
s
s
th
a
t
is
th
e
s
um
of
m
ul
ti
pl
ic
a
ti
on
m
a
tr
ix
nor
m
a
li
z
e
d
R
w
it
h
a
w
e
ig
ht
ve
c
t
or
s
o
th
a
t
th
e
g
r
e
a
te
s
t
va
lu
e
is
c
hos
e
n
a
s
th
e
be
s
t
a
lt
e
r
na
ti
ve
s
a
s
a
s
ol
ut
io
n
.
T
he
va
lu
e
t
o f
in
d t
he
de
c
is
io
n na
m
e
ly
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
H
y
br
id
D
SS f
or
r
e
c
om
m
e
ndat
io
ns
of
hal
al
c
ul
in
ar
y
t
our
i
s
m
W
e
s
t
Sum
at
r
a
(
M
ar
di
s
on
)
277
−
T
e
s
ti
ng
a
nd
e
v
a
lu
a
ti
on
m
e
th
ods
.
A
f
te
r
w
e
ge
t
th
e
de
c
i
s
io
n
a
s
to
th
e
s
ol
ut
io
n
of
th
e
pr
obl
e
m
th
e
n
w
e
te
s
ti
ng
th
a
t
de
c
is
io
n
in
th
e
r
e
a
l
w
or
ld
a
nd
e
va
lu
a
ti
ng
th
e
r
e
s
ul
t
of
te
s
ti
ng.
I
n
th
is
s
tu
dy
th
e
te
s
ti
ng
a
nd
e
va
lu
a
ti
on
doi
ng
to
to
ur
is
t
th
a
t
lo
oki
ng
f
or
ha
l
a
l
c
ul
in
a
r
y
in
W
e
s
t
S
um
a
tr
a
I
ndone
s
ia
a
nd
th
e
r
e
s
t
a
ur
a
nt
th
a
t
s
e
r
ve
s
ha
la
l
c
ul
in
a
r
y i
n W
e
s
t
S
um
a
tr
a
.
3.
R
E
S
U
L
T
A
N
D
D
I
S
C
U
S
S
I
O
N
T
hi
s
r
e
s
e
a
r
c
h
r
e
s
ul
te
d
in
a
de
c
is
io
n
s
uppor
t
s
y
s
te
m
f
or
s
e
l
e
c
ti
n
g
th
e
be
s
t
c
om
put
e
r
-
ba
s
e
d
li
br
a
r
ia
ns
.
T
he
s
y
s
te
m
bui
lt
us
e
d
th
e
hyb
r
id
M
A
D
M
m
ode
l,
w
hi
c
h
i
s
a
c
om
bi
na
ti
on
of
th
e
A
H
P
a
nd
S
A
W
m
e
th
ods
.
I
n
pr
oduc
in
g
th
e
be
s
t
a
lt
e
r
na
ti
ve
,
th
e
s
y
s
te
m
a
c
c
om
m
oda
te
s
th
e
in
vol
ve
m
e
nt
of
m
a
ny
de
c
is
io
n
-
m
a
ke
r
s
(
gr
oup
de
c
is
io
n
m
a
ki
ng)
.
A
H
P
m
e
th
od
i
s
u
s
e
d
f
or
w
e
ig
ht
in
g
a
nd
S
A
W
f
or
th
e
r
a
nki
ng
pr
oc
e
s
s
.
T
he
s
ys
te
m
s
te
p
s
to
pr
oduc
e
ha
la
l
c
ul
in
a
r
y t
our
is
m
r
e
c
om
m
e
nda
ti
ons
i
n W
e
s
t
S
um
a
tr
a
a
r
e
i
s:
3.1. De
t
e
r
m
in
in
g t
h
e
m
at
c
h
c
r
it
e
r
ia
r
at
in
g valu
e
3.1.1
.
H
al
al
c
e
r
t
if
ic
at
e
c
r
it
e
r
ia
(
C
1)
T
he
c
ul
in
a
r
y
in
dus
tr
y
ha
s
qui
te
hi
gh
pr
os
pe
c
ts
.
C
r
e
a
ti
on
a
nd
in
nova
ti
on
a
ls
o
ne
e
d
to
c
ont
in
ue
to
a
tt
r
a
c
t
lo
nge
r
a
nd
m
or
e
c
ons
um
e
r
in
te
r
e
s
t.
I
t
is
e
s
s
e
nt
ia
l
to
r
e
m
e
m
be
r
th
a
t
c
ons
um
e
r
s
te
nd
to
b
e
bor
e
d
w
it
h
f
ood or
dr
in
ks
[
24
]
. C
onc
e
r
ni
ng t
he
c
ons
um
pt
io
n of
ha
la
l
f
ood,
th
e
ha
la
l
pr
oc
e
s
s
of
f
ood a
nd dr
in
k i
s
r
e
qui
r
e
d
t
o
m
e
e
t
th
e
r
e
qui
r
e
m
e
nt
s
a
nd
pr
oc
e
dur
e
s
f
or
th
e
ha
la
l
gua
r
a
nt
e
e
s
ys
te
m
s
e
t
by
M
U
I
.
T
he
a
s
s
e
s
s
m
e
nt
of
ha
la
l
f
ood
c
e
r
t
if
ic
a
te
[
25]
is
ba
s
e
d
on
c
e
r
ti
f
ic
a
te
s
a
lr
e
a
dy
i
s
s
ue
d
b
y,
be
in
g
in
th
e
a
dm
in
is
tr
a
ti
on
pr
oc
e
s
s
,
be
in
g
s
ubm
it
te
d,
a
nd
none
a
t
a
ll
.
E
a
c
h
a
s
s
e
s
s
m
e
nt
ha
s
a
gr
a
de
a
nd
r
a
ti
ng
a
c
c
or
di
ng
to
th
e
s
pe
c
if
ie
d
a
s
s
e
s
s
m
e
nt
r
a
nge
[
26]
. A
s
s
how
n i
n
T
a
bl
e
1.
3.1.2.
C
r
it
e
r
ia
f
or
f
ood
an
d
b
e
ve
r
age
s
p
e
c
if
ic
at
io
n
s
(
C
2)
E
ve
r
y
c
ul
in
a
r
y
f
ood
a
nd
dr
in
k
P
a
da
ng
R
e
s
ta
ur
a
nt
is
ve
r
y
di
ve
r
s
e
.
B
e
s
id
e
s
m
a
ny
s
im
il
a
r
it
ie
s
,
e
a
c
h
r
e
g
io
n
in
W
e
s
t
S
um
a
tr
a
a
ls
o
ha
s
a
s
om
e
w
ha
t
di
f
f
e
r
e
nt
c
ui
s
in
e
va
r
ia
nt
c
om
pa
r
e
d
to
ot
he
r
r
e
gi
ons
.
L
ik
e
R
e
s
ta
ur
a
nt
A
,
th
e
r
e
a
r
e
ni
ne
ty
pe
s
of
f
ood
s
uc
h
a
s
F
r
ie
d
C
hi
c
ke
n,
R
e
nda
ng,
S
na
ppe
r
C
ur
r
y,
P
op
C
hi
c
k
e
n,
S
pi
c
y
S
our
M
e
a
t,
B
e
e
f
,
S
pi
na
c
h,
G
r
i
ll
e
d
F
is
h,
G
a
do
-
G
a
do
,
a
nd
f
our
ty
pe
s
of
dr
in
ks
s
uc
h
a
s
I
c
e
C
r
e
a
m
,
F
r
u
it
S
oup, I
c
e
J
ui
c
e
, a
nd S
w
e
e
t
te
a
. A
s
s
how
n i
n
T
a
bl
e
2.
T
a
bl
e
1. C
om
po
s
it
io
n of
ha
la
l
f
ood a
s
s
e
s
s
m
e
nt
C
e
r
t
i
f
i
c
a
t
e
G
r
a
de
R
a
t
i
ng
I
s
s
ue
d
V
e
r
y G
ood
3
B
e
i
ng pr
oc
e
s
s
e
d
G
ood
2
N
one
P
oor
1
T
a
bl
e
2.
C
om
po
s
it
io
n of
f
ood s
pe
c
if
ic
a
ti
ons
a
s
s
e
s
s
m
e
nt
N
um
be
r
of
f
ood s
pe
c
i
f
i
c
a
t
i
ons
G
r
a
de
R
a
t
i
ng
> 14
E
xc
e
l
l
e
nt
4
8
-
13
V
e
r
y G
ood
3
4
-
7
G
ood
2
1
-
3
P
oor
1
3.1.3.
F
avor
it
e
f
ood
c
r
it
e
r
ia
(
C
3)
W
e
s
t
S
um
a
tr
a
is
f
a
m
ous
f
or
it
s
c
ul
in
a
r
y
w
e
a
lt
h.
A
va
r
ie
ty
of
t
ypi
c
a
l
f
oods
of
W
e
s
t
S
um
a
tr
a
ha
ve
a
di
s
ti
nc
ti
ve
ta
s
te
th
a
t
is
popula
r
a
nd
w
or
ld
w
id
e
.
T
he
c
om
pl
e
te
m
e
nu
is
r
a
ngi
ng
f
r
om
R
e
nda
ng,
S
pi
c
y
S
ou
r
,
B
r
a
in
C
ur
r
y,
C
hi
li
S
hr
im
p,
a
nd
P
op
C
hi
c
ke
n.
W
it
h
de
li
c
io
us
f
l
a
vor
s
,
P
a
da
ng'
s
c
ul
in
a
r
y
to
ur
is
m
de
s
ti
na
ti
on
is
ne
ve
r
e
m
pt
y of
vi
s
it
or
s
. A
s
s
how
n
in
T
a
bl
e
3.
3.1.4.
F
avor
it
e
d
r
in
k
s
c
r
it
e
r
ia
(
C
4)
W
it
h a
va
r
ie
ty
of
f
a
vor
it
e
f
oods
, f
a
vor
it
e
dr
in
ks
a
r
e
a
ls
o va
r
io
u
s
ly
a
va
il
a
bl
e
r
a
ngi
ng f
r
om
hot
t
o
c
ol
d
dr
in
ks
. A
s
s
how
n i
n
T
a
bl
e
4.
T
a
bl
e
3. C
om
po
s
it
io
n of
f
a
vor
it
e
f
ood a
s
s
e
s
s
m
e
nt
N
um
be
r
of
f
a
vor
i
t
e
f
oods
G
r
a
de
R
a
t
i
ng
>4
V
e
r
y G
ood
4
2
-
3
G
ood
3
1
F
a
i
r
2
N
one
P
oor
1
T
a
bl
e
4. C
om
po
s
it
io
n of
f
a
vor
it
e
dr
in
k a
s
s
e
s
s
m
e
nt
N
um
be
r
of
f
a
vor
i
t
e
d
r
i
nks
G
r
a
de
R
a
t
i
ng
>
3
V
e
r
y G
ood
4
2
G
ood
3
1
F
a
i
r
2
N
one
P
oor
1
3.1.5.
C
r
it
e
r
ia
f
or
n
u
m
b
e
r
of
vi
s
it
or
s
p
e
r
d
ay (
C
5)
A
la
r
ge
num
be
r
of
vi
s
it
or
s
to
a
r
e
s
ta
ur
a
nt
w
il
l
de
te
r
m
in
e
c
us
to
m
e
r
s
'
tr
us
t
in
f
ood
a
nd
be
ve
r
a
ge
c
ui
s
in
e
i
n t
e
r
m
s
of
good ta
s
te
, c
om
f
or
t
pl
a
c
e
, a
nd
c
us
to
m
e
r
s
a
ti
s
f
a
c
ti
on. As
s
how
n i
n
T
a
bl
e
5.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
10
, N
o.
2, J
une
20
21
:
273
–
283
278
3.1.6.
F
ood
p
r
ic
e
c
r
it
e
r
ia
(
C
6)
T
he
pr
ic
e
of
f
ood
is
e
s
s
e
nt
ia
l
f
or
c
us
to
m
e
r
s
w
ho
w
il
l
vi
s
it
a
r
e
s
ta
ur
a
nt
.
B
a
s
e
d
on
th
e
da
ta
in
th
e
f
ie
ld
,
th
e
m
or
e
de
li
c
io
us
a
nd
ta
s
ty
a
f
ood
m
e
nu,
th
e
hi
ghe
r
th
e
pr
ic
e
is
.
M
or
e
ove
r
,
m
os
t
f
a
vor
it
e
f
ood
is
di
f
f
e
r
e
nt
f
r
om
o
th
e
r
t
ype
s
of
f
ood. As
s
how
n i
n
T
a
bl
e
6.
T
a
bl
e
5. C
om
po
s
it
io
n of
vi
s
it
or
s
pe
r
da
y a
s
s
e
s
s
m
e
nt
N
um
be
r
of
v
i
s
i
t
or
s
G
r
a
de
R
a
t
i
ng
>
1000
V
e
r
y G
ood
4
>
500
G
ood
3
>
300
F
a
i
r
2
< 300
P
oor
1
T
a
bl
e
6. C
om
po
s
it
io
n of
f
ood pr
ic
e
a
s
s
e
s
s
m
e
nt
F
ood
p
r
i
c
e
s
G
r
a
de
R
a
t
i
ng
10.000
–
20.000
V
e
r
y C
he
a
p
4
21.000
–
50.000
C
he
a
p
3
51.000
–
100.000
E
xpe
ns
i
ve
2
> 100.000
V
e
r
y E
xpe
ns
i
ve
1
3.1.7.
V
is
it
or
age
s
e
g
m
e
n
t
c
r
it
e
r
ia
(
C
7)
F
ood
r
e
s
ta
ur
a
nt
s
of
vi
s
it
or
a
ge
s
e
gm
e
nt
s
va
r
y
d
e
pe
ndi
ng
on
th
e
ta
s
te
s
of
e
a
c
h
vi
s
it
or
.
A
s
s
how
n
in
T
a
bl
e
7.
3.1.8.
F
ac
il
it
y c
r
it
e
r
ia
(
C
8)
F
ood r
e
s
ta
ur
a
nt
s
t
ha
t
ha
ve
c
om
pl
e
te
f
a
c
il
it
ie
s
s
u
c
h a
s
M
u
s
hol
la
(
pr
a
ye
r
r
oom
s
)
, t
oi
le
ts
, l
a
r
ge
pa
r
ki
ng
lo
ts
, a
nd t
he
pr
e
s
e
nt
pl
a
c
e
t
o e
a
t
f
ood or
dr
in
k on
th
e
f
lo
or
w
il
l
be
m
uc
h i
n de
m
a
nd by vis
it
or
s
, be
c
a
us
e
of
t
he
c
om
f
or
ta
bl
e
a
nd s
a
f
e
a
tm
os
phe
r
e
. A
s
s
how
n
n i
n
T
a
bl
e
8.
T
a
bl
e
7. C
om
po
s
it
io
n of
vi
s
it
or
a
ge
s
e
gm
e
nt
a
s
s
e
s
s
m
e
nt
V
i
s
i
t
or
a
ge
s
e
gm
e
nt
G
r
a
de
R
a
t
i
ng
A
l
l
A
ge
s
V
e
r
y G
ood
4
A
dul
t
G
ood
3
A
dol
e
s
c
e
nt
F
a
i
r
2
C
hi
l
dr
e
n
P
oor
1
T
a
bl
e
8. C
om
po
s
it
io
n of
f
a
c
il
it
y a
s
s
e
s
s
m
e
nt
s
F
a
c
i
l
i
t
y
G
r
a
de
R
a
t
i
ng
M
us
hol
l
a
, T
oi
l
e
t
s
, P
a
r
ki
ng L
ot
s
V
e
r
y G
ood
4
T
oi
l
e
t
s
, P
a
r
ki
ng L
ot
s
G
ood
3
P
a
r
ki
ng L
ot
s
F
a
i
r
2
N
one
P
oor
1
3.1.9.
O
n
li
n
e
i
n
d
e
x c
r
it
e
r
ia
(
C
9)
O
nl
in
e
I
nde
x
is
a
s
ta
r
-
s
ha
pe
d
r
a
ti
ng
of
a
va
lu
e
gi
ve
n
by
a
c
us
t
om
e
r
to
a
r
e
s
ta
ur
a
nt
w
it
h
a
c
om
pl
e
te
m
e
nu.
A
s
ta
r
r
a
ti
ng
is
be
ne
f
ic
ia
l
in
m
a
in
ta
in
in
g
th
e
be
s
t
s
e
r
vi
c
e
s
ta
nda
r
ds
.
I
t
a
ls
o
he
lp
s
R
e
s
ta
ur
a
nt
in
m
a
in
ta
in
in
g c
us
to
m
e
r
s
a
ti
s
f
a
c
ti
on u
s
in
g t
hi
s
s
y
s
te
m
s
e
r
vi
c
e
. A
s
s
how
n i
n
T
a
bl
e
9.
T
a
bl
e
9. C
om
po
s
it
io
n of
t
he
onl
in
e
i
nde
x a
s
s
e
s
s
m
e
nt
F
a
c
i
l
i
t
y
G
r
a
de
R
a
t
i
ng
5 S
t
a
r
E
xc
e
l
l
e
nt
6
4 S
t
a
r
V
e
r
y G
ood
5
3 S
t
a
r
F
a
i
r
4
2 S
t
a
r
P
oor
3
1 S
t
a
r
B
a
d
2
N
one
V
e
r
y B
a
d
1
3.2.
R
e
s
t
au
r
an
t
as
s
e
s
s
m
e
n
t
d
at
a
B
a
s
e
d
on
th
e
s
ur
ve
y
r
e
s
ul
ts
by
th
e
r
e
s
e
a
r
c
h
te
a
m
to
e
a
c
h
r
e
s
ta
ur
a
nt
ow
ne
r
in
W
e
s
t
S
um
a
tr
a
P
r
ovi
nc
e
,
th
e
da
ta
c
a
n
be
obt
a
in
e
d
f
or
pr
oc
e
s
s
in
g
us
in
g
th
e
H
y
br
id
M
A
D
M
m
e
th
od.
T
h
e
da
ta
obt
a
in
e
d
in
th
e
f
ie
ld
a
s
s
how
n i
n T
a
bl
e
10.
T
he
da
ta
obt
a
in
e
d i
n T
a
bl
e
10 ne
e
ds
t
o be
c
a
r
r
ie
d out a
s
a
c
onv
e
r
s
io
n pr
oc
e
s
s
ba
s
e
d on the
m
a
tc
hi
ng
c
r
it
e
r
ia
r
a
ti
ng
va
lu
e
.
D
a
ta
c
onve
r
s
io
n
is
m
a
tc
he
d
ba
s
e
d
on
th
e
r
a
nge
of
da
ta
in
to
a
r
a
ti
ng
va
lu
e
in
th
e
m
a
tc
h
r
a
ti
ng
va
lu
e
ta
bl
e
of
e
a
c
h
of
th
e
c
r
it
e
r
ia
.
T
he
c
onve
r
te
d
da
ta
va
lu
e
is
us
e
d
to
de
te
r
m
in
e
th
e
nor
m
a
li
z
a
ti
on
m
a
tr
ix
i
n t
he
f
if
th
s
te
p l
a
te
r
. T
he
r
e
s
ul
ts
of
t
he
c
onve
r
s
io
n va
lu
e
a
s
s
how
n i
n
T
a
bl
e
11
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
H
y
br
id
D
SS f
or
r
e
c
om
m
e
ndat
io
ns
of
hal
al
c
ul
in
ar
y
t
our
i
s
m
W
e
s
t
Sum
at
r
a
(
M
ar
di
s
on
)
279
T
a
bl
e
10. R
e
s
ta
ur
a
nt
a
s
s
e
s
s
m
e
nt
da
t
a
A
l
t
e
r
na
t
i
ve
s
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
C9
RM
-
A
Y
E
S
14
1
2
≥
1000
35.000
A
l
l
a
ge
M
, T
, P
S
t
a
r
5
RM
-
B
Y
E
S
7
1
1
≥
500
20.000
A
l
l
a
ge
P
S
t
a
r
4
RM
-
C
Y
E
S
7
1
1
≥
500
25.000
A
dol
e
s
c
e
nt
T
, P
S
t
a
r
4
RM
-
D
Y
E
S
4
2
1
≥
300
20.000
A
dul
t
M
, T
, P
S
t
a
r
4
RM
-
E
Y
E
S
14
2
3
≥
250
18.000
A
l
l
a
ge
M
, T
, P
S
t
a
r
4
RM
-
F
No
12
3
1
≥
100
15.000
A
dul
t
T
, P
S
t
a
r
3
RM
-
G
Y
E
S
5
2
3
≥
1000
25.000
A
l
l
a
ge
T
, P
S
t
a
r
4
RM
-
H
No
8
4
2
≥
300
20.000
A
l
l
a
ge
P
S
t
a
r
4
RM
-
I
Y
E
S
6
1
1
≥
1000
25.000
A
l
l
a
ge
M
, T
, P
S
t
a
r
5
T
a
bl
e
11. C
onv
e
r
s
io
n of
a
s
s
e
s
s
m
e
nt
da
ta
A
l
t
e
r
na
t
i
ve
s
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
C9
RM
-
A
3
4
2
3
4
3
4
4
6
RM
-
B
3
2
2
2
3
4
4
2
5
RM
-
C
3
2
2
2
3
3
2
3
5
RM
-
D
3
2
3
2
2
4
3
4
5
RM
-
E
3
4
3
4
1
4
4
4
5
RM
-
F
1
3
3
2
1
4
3
3
4
RM
-
G
3
2
3
4
4
3
4
3
5
RM
-
H
1
3
4
3
2
4
4
2
5
RM
-
I
3
2
2
2
4
3
4
4
6
3
.
3.
H
y
b
r
i
d
m
e
t
h
o
d
c
a
lc
u
l
at
i
o
n
p
r
oc
e
s
s
−
F
ir
s
t
S
te
p:
M
a
ki
ng
pa
ir
w
is
e
c
om
pa
r
is
on
m
a
tr
ix
c
r
it
e
r
ia
.
C
om
p
a
r
is
on
is
ba
s
e
d
on
th
e
"
ju
dgm
e
nt
"
of
th
e
de
c
is
io
n
-
m
a
ke
r
by a
s
s
e
s
s
in
g t
he
l
e
ve
l
of
i
m
por
ta
nc
e
of
a
n e
le
m
e
nt
c
om
pa
r
e
d t
o ot
he
r
e
le
m
e
nt
s
.
T
a
bl
e
12
th
is
is
obt
a
in
e
d f
r
om
t
he
pa
ir
e
d c
r
it
e
r
ia
,
na
m
e
ly
, ni
ne
pa
ir
e
d c
r
it
e
r
ia
, a
nd t
he
n gi
ve
n a
va
lu
e
a
c
c
or
di
ng
to
th
e
va
lu
e
of
th
e
pa
ir
w
is
e
c
om
pa
r
is
on
s
c
a
le
ba
s
e
d
on
T
a
bl
e
1
1
.
C
1
c
r
it
e
r
ia
a
r
e
pa
ir
e
d
w
it
h
C
2
w
it
h
a
va
lu
e
of
3,
a
nd
C
1
w
it
h C
3
w
it
h a
va
lu
e
of
5.
F
or
num
b
e
r
s
th
e
va
lu
e
of
1
i
s
obt
a
in
e
d
f
r
om
th
e
di
vi
s
io
n
pr
oc
e
s
s
;
f
or
e
xa
m
pl
e
,
th
e
c
r
it
e
r
ia
pa
ir
C
2
a
nd
C
1
w
it
h
a
va
lu
e
of
0.33
obt
a
in
e
d
f
r
om
th
e
di
vi
s
io
n
p
r
oc
e
s
s
,
na
m
e
ly
1/
3=
0.33.
T
a
bl
e
12. P
a
ir
w
is
e
c
om
p
a
r
is
on ma
tr
ix
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
C9
C1
1
3
5
7
3
2
4
5
6
C2
0,33
1
2
5
3
4
6
5
7
C3
0,2
0,5
1
3
5
2
3
7
5
C4
0,14
0,2
0,33
1
2
4
3
5
7
C5
0,33
0,33
0,2
0,5
1
4
5
2
3
C6
0,5
0,25
0,5
0,25
0,25
1
3
5
7
C7
0,25
0,17
0,33
0,33
0,2
0,33
1
3
5
C8
0,2
0,2
0,14
0,2
0,5
0,2
0,33
1
5
C9
0,17
0,14
0,2
0,14
0,33
0,14
0,2
0,2
1
T
ot
a
l
3,12
5,79
9,7
17,42
15,28
17,67
25,53
33,2
46
−
S
e
c
ond
S
te
p
:
C
a
lc
u
l
a
t
i
ng
t
he
va
lu
e
w
e
ig
h
t
m
a
t
r
ix
be
twe
e
n
c
r
it
e
r
ia
a
nd
p
r
i
o
r
i
t
y.
T
a
bl
e
1
3
th
is
is
obt
a
in
e
d
m
a
tr
ix
o
f
v
a
lu
e
w
e
ig
ht
be
twe
e
n
c
r
it
e
r
ia
a
nd
p
r
io
r
i
ti
e
s
ba
s
e
d
on
c
a
lc
ul
a
ti
on
f
r
om
T
a
bl
e
1
2.
T
he
c
r
it
e
r
ia
pa
ir
C
1
a
nd
C
2
w
it
h a
va
lu
e
of
0.3
21
obt
a
in
e
d
f
r
om
th
e
di
vi
s
io
n
pr
oc
e
s
s
w
it
h
th
e
s
um
s
c
or
e
on t
ha
t
c
ol
oum
, na
m
e
ly
1/
3
,12
=
0.
321
.
T
he
va
lu
e
w
e
ig
ht
in
g
m
a
tr
ix
be
twe
e
n
th
e
c
r
it
e
r
ia
a
nd
pr
io
r
it
y
in
T
a
bl
e
14
is
th
e
p
r
oc
e
s
s
of
de
te
r
m
in
in
g
th
e
pr
io
r
it
y
va
lu
e
or
w
e
ig
ht
of
e
a
c
h
c
r
it
e
r
io
n.
T
h
e
w
e
ig
ht
va
lu
e
is
us
e
d
la
te
r
in
th
e
m
ul
ti
pl
ic
a
ti
on
pr
oc
e
s
s
w
it
h
th
e
nor
m
a
li
z
a
ti
on
m
a
tr
ix
va
lu
e
in
s
te
p
s
ix
.
T
he
p
r
oc
e
s
s
of
de
te
r
m
in
in
g
th
e
w
e
ig
ht
in
g
m
a
tr
ix
of
va
lu
e
s
a
m
ong
c
r
it
e
r
ia
is
in
th
r
e
e
s
te
ps
.
F
ir
s
t,
e
a
c
h
va
lu
e
in
T
a
bl
e
14
is
di
vi
de
d
by
th
e
num
be
r
of
va
lu
e
s
pe
r
c
ol
um
n;
f
or
e
xa
m
pl
e
,
th
e
va
lu
e
0.321
is
obt
a
in
e
d
f
r
om
1/
3,12
=
0.321.
S
e
c
ond,
a
ll
th
e
c
r
it
e
r
ia
va
lu
e
s
of
e
a
c
h
r
ow
a
dde
d
r
e
s
ul
ts
in
th
e
T
ot
a
l
c
ol
um
n.
L
a
s
t
s
te
p,
th
e
va
lu
e
in
th
e
A
m
ount
c
ol
um
n
di
vi
de
d
by
m
a
ny
c
r
it
e
r
ia
w
il
l
pr
oduc
e
t
he
va
lu
e
i
n t
he
pr
io
r
it
y c
ol
um
n or
w
e
ig
ht
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
10
, N
o.
2, J
une
20
21
:
273
–
283
280
T
a
bl
e
13. M
a
tr
ix
of
va
lu
e
w
e
ig
ht
be
twe
e
n c
r
it
e
r
ia
a
nd pr
io
r
it
ie
s
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
C9
Q
t
y
P
r
i
or
i
t
y
C1
0,321
0,518
0,515
0,402
0,196
0,113
0,157
0,151
0,130
2,503
0,278
C2
0,106
0,173
0,206
0,287
0,196
0,226
0,235
0,151
0,152
1,732
0,192
C3
0,064
0,086
0,103
0,172
0,327
0,113
0,118
0,211
0,109
1,303
0,145
C4
0,045
0,035
0,034
0,057
0,131
0,226
0,118
0,151
0,152
0,948
0,105
C5
0,106
0,057
0,021
0,029
0,065
0,226
0,196
0,060
0,065
0,825
0,092
C6
0,160
0,043
0,052
0,014
0,016
0,057
0,118
0,151
0,152
0,763
0,085
C7
0,080
0,029
0,034
0,019
0,013
0,019
0,039
0,090
0,109
0,432
0,048
C8
0,064
0,035
0,014
0,011
0,033
0,011
0,013
0,030
0,109
0,320
0,036
C9
0,054
0,024
0,021
0,008
0,022
0,008
0,008
0,006
0,022
0,172
0,019
T
a
bl
e
14
.
T
ot
a
l
a
ddi
ti
on va
lu
e
C
r
i
t
e
r
i
a
P
r
i
or
i
t
y
A
m
ount
R
e
s
ul
t
C1
0,278
10,013
10,291
C2
0,192
6,415
6,607
C3
0,145
3,866
4,011
C4
0,105
2,389
2,494
C5
0,092
1,500
1,592
C6
0,085
1,504
1,589
C7
0,048
0,510
0,558
C8
0,036
0,277
0,312
C9
0,019
0,048
0,067
T
ot
a
l
27,521
−
T
hi
r
d
S
te
p
:
C
a
lc
ul
a
ti
ng t
he
s
um
of
e
a
c
h l
in
e
'
s
m
a
tr
ix
T
a
bl
e
15
th
is
i
s
a
ddi
ti
on
m
a
tr
ix
f
or
e
a
c
h
l
in
e
ba
s
e
d
on
c
a
lc
ul
a
ti
on
f
r
om
T
a
bl
e
1
3.
T
he
c
r
it
e
r
ia
pa
ir
C
1
a
nd
C
2
w
it
h
a
va
lu
e
of
0.
278
obt
a
in
e
d
f
r
om
th
e
m
ul
ti
pl
ic
a
ti
on
pr
oc
e
s
s
w
it
h
1
(
f
r
om
T
a
bl
e
12)
x0.278
(
f
r
om
T
a
bl
e
13)
, na
m
e
ly
1
x0.278=
0.
278
.
T
a
bl
e
15
. A
ddi
ti
on ma
tr
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or
e
a
c
h l
in
e
C
r
i
t
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r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
C9
Q
t
y
C1
0,278
0,834
1,391
1,947
0,834
0,556
1,113
1,391
1,669
10,013
C2
0,064
0,192
0,385
0,962
0,577
0,77
1,155
0,962
1,347
6,415
C3
0,029
0,072
0,145
0,434
0,724
0,29
0,434
1,014
0,724
3,866
C4
0,015
0,021
0,035
0,105
0,211
0,422
0,316
0,527
0,738
2,389
C5
0,03
0,03
0,018
0,046
0,092
0,367
0,458
0,183
0,275
1,500
C6
0,042
0,021
0,042
0,021
0,021
0,085
0,254
0,424
0,593
1,504
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0,012
0,008
0,016
0,016
0,01
0,016
0,048
0,144
0,24
0,510
C8
0,007
0,007
0,005
0,007
0,018
0,007
0,012
0,036
0,178
0,277
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0,003
0,003
0,004
0,003
0,006
0,003
0,004
0,004
0,019
0,048
T
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a
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ll
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pr
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n T
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te
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l
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p.
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p
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lc
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I
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H
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281
−
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e
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e
c
ond
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s
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t
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s
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hi
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3
s
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t
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is
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d
a
lt
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na
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.
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f
o
ur
th
hi
ghe
s
t
va
lu
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is
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V
4
s
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th
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t
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E
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h
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s
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s
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e
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th
a
lt
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.
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h
e
f
if
th
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ghe
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t
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s
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V
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s
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t
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h
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s
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iv
e
a
lt
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na
ti
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s
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s
ix
t
h
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6
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th
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. T
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7 s
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h a
s
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t
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ni
nt
h a
lt
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r
na
ti
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.
4.
C
O
N
C
L
U
S
I
O
N
A
f
te
r
a
na
ly
z
in
g
th
e
de
c
is
io
n
s
uppor
t
s
y
s
te
m
f
or
W
e
s
t
S
um
a
tr
a
ha
la
l
f
ood
r
e
c
om
m
e
nda
ti
on
us
in
g
th
e
hybr
id
M
A
D
M
m
e
th
od,
it
c
a
n
be
c
onc
lu
de
d
th
a
t:
D
S
S
a
ppl
ic
a
ti
ons
m
a
de
u
s
in
g
th
e
hybr
id
D
S
S
m
e
th
od
c
a
n
c
om
bi
ne
a
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy
pr
oc
e
s
s
(
A
H
P
)
a
nd
s
im
pl
e
a
ddi
ti
ve
w
e
ig
ht
in
g
(
S
A
W
)
m
e
th
ods
,
s
o
th
a
t
th
e
y
e
a
s
il
y
r
e
c
om
m
e
nd
ha
la
l
c
ul
in
a
r
y
to
ur
is
m
in
W
e
s
t
S
um
a
tr
a
.
B
y
im
pl
e
m
e
nt
in
g
a
na
ly
ti
c
a
l
hi
e
r
a
r
c
hy
pr
oc
e
s
s
(
A
H
P
)
m
e
th
od,
it
c
a
n
de
te
r
m
in
e
a
c
ons
i
s
te
nt
w
e
ig
ht
v
a
lu
e
of
e
a
c
h
c
r
it
e
r
io
n,
w
he
r
e
th
e
w
e
ig
ht
v
a
lu
e
w
il
l
be
us
e
d
in
th
e
s
um
of
pr
e
f
e
r
e
nc
e
va
lu
e
s
in
s
im
pl
e
a
ddi
ti
ve
w
e
i
ght
in
g
(
S
A
W
)
m
e
th
od.
B
y
us
in
g
a
de
c
is
io
n
s
uppor
t
s
ys
te
m
,
s
im
pl
e
a
ddi
ti
ve
w
e
ig
ht
in
g
(
S
A
W
)
m
e
th
od
c
a
r
r
ie
d
out
th
e
nor
m
a
li
z
a
ti
on
c
a
lc
ul
a
ti
on,
th
e
n
m
ul
ti
pl
ie
d
by
th
e
w
e
ig
ht
va
lu
e
(
W
)
th
a
t
ha
s
be
e
n
de
te
r
m
in
e
d
to
ge
t
th
e
pr
e
f
e
r
e
nc
e
va
lu
e
of
e
a
c
h
c
r
it
e
r
io
n.
F
ur
th
e
r
m
or
e
,
th
e
r
a
nki
ng
va
lu
e
is
obt
a
in
e
d
f
r
om
th
e
a
lt
e
r
na
ti
ve
s
by
a
ddi
ng
up
th
e
va
lu
e
of
th
e
pr
e
f
e
r
e
nc
e
.
T
hi
s
r
a
nki
ng
va
lu
e
de
te
r
m
in
e
s
th
e
W
e
s
t
S
um
a
tr
a
ha
la
l
c
ul
in
a
r
y
to
ur
is
m
r
e
c
om
m
e
nda
ti
ons
.
D
e
c
i
s
io
n
s
uppor
t
s
ys
te
m
s
us
in
g
th
e
hybr
id
M
A
D
M
m
e
th
od
in
r
e
a
l
te
r
m
s
c
a
n
b
e
a
ppl
ie
d
in
th
e
W
e
s
t
S
um
a
tr
a
ha
la
l
c
ul
in
a
r
y
to
ur
is
m
r
e
c
om
m
e
nda
ti
ons
.
F
or
r
e
s
e
a
r
c
he
r
s
w
ho
w
a
nt
to
de
v
e
lo
p
th
is
de
c
is
io
n
s
uppor
t
s
ys
t
e
m
,
it
c
a
n
be
de
ve
lo
pe
d
f
ur
th
e
r
by
c
om
bi
ni
ng
ot
he
r
D
S
S
m
e
th
ods
to
b
e
be
tt
e
r
a
nd
m
or
e
v
a
r
ie
d
by
c
om
pl
e
ti
ng
th
e
c
r
it
e
r
ia
f
or
ha
la
l
c
ul
in
a
r
y
to
ur
is
m
r
e
c
om
m
e
nda
ti
ons
in
W
e
s
t
S
um
a
tr
a
,
s
o
th
a
t
th
e
a
na
ly
s
i
s
r
e
s
ul
ts
a
r
e
s
h
a
r
pe
r
a
nd
v
al
id
.
A
C
K
N
O
WL
E
D
G
E
M
E
N
T
S
W
e
w
oul
d
li
ke
to
e
xpr
e
s
s
our
im
m
e
a
s
ur
a
bl
e
gr
a
ti
tu
de
to
M
r
.
H
.
H
e
r
m
a
n
N
a
w
a
s
a
nd
M
r
s
.
D
r
.
H
j.
Z
e
r
ni
M
e
lm
us
i,
M
.M
.,
A
k.
C
A
.
a
s
C
h
a
ir
m
a
n
of
th
e
F
ounda
ti
on
a
nd
f
ounde
r
of
th
e
Y
a
ya
s
a
n
P
e
ndi
di
ka
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
10
, N
o.
2, J
une
20
21
:
273
–
283
282
K
om
put
e
r
(
Y
P
T
K
)
P
a
da
ng
w
hi
c
h
ove
r
s
e
e
s
th
e
U
ni
ve
r
s
it
a
s
P
ut
r
a
I
ndone
s
ia
Y
P
T
K
P
a
da
ng
w
ho
h
a
s
pr
ovi
de
d
us
w
it
h
f
undi
ng
a
nd
s
uppor
t
f
or
th
is
r
e
s
e
a
r
c
h.
T
ha
nk
a
r
e
a
ls
o
gi
ve
n
to
a
ll
th
e
a
c
a
d
e
m
ic
s
of
th
e
U
ni
ve
r
s
it
a
s
P
ut
r
a
I
ndone
s
ia
Y
P
T
K
P
a
da
ng w
ho ha
ve
s
uppor
te
d
t
hi
s
r
e
s
e
a
r
c
h a
nd t
he
to
ur
is
m
o
f
f
ic
e
o
f
t
he
C
it
y of
P
a
da
ng
a
nd W
e
s
t
S
um
a
tr
a
P
r
ovi
nc
e
w
ho ha
ve
pe
r
m
it
te
d t
o c
a
r
r
y out t
hi
s
r
e
s
e
a
r
c
h.
R
E
F
E
R
E
N
C
E
S
[1]
J. Aslan Ceylan an
d A.
O. Ozcelik, “
Cuisine
culture of the
pearl
of Me
sopotamia: Mardin, Tur
key,”
J. Ethn.
Foods
,
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