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s.
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m
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n
d
re
sp
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si
b
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ti
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s.
K
ey
w
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d
s
:
AHP
An
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s
is
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v
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As
s
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m
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Mu
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Un
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d
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tg
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B
u
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in
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I
m
am
B
ar
d
jo
Stre
et
No
.
5
,
Sem
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a
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g
,
C
en
tr
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J
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5
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4
1
,
I
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d
o
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g
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ab
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h
im
awa
n
@
s
tu
d
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u
n
d
ip
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
E
m
p
lo
y
ee
p
er
f
o
r
m
a
n
ce
ap
p
r
a
is
al
i
s
a
cr
u
cial
asp
ec
t
o
f
h
u
m
an
r
eso
u
r
ce
m
an
a
g
em
en
t
th
at
in
v
o
lv
es
ev
alu
atin
g
em
p
lo
y
ee
s
'
wo
r
k
p
er
f
o
r
m
a
n
ce
ag
ain
s
t
p
r
ed
ef
i
n
ed
cr
iter
ia
[
1
]
.
T
r
a
d
itio
n
ally
,
p
er
f
o
r
m
an
ce
ap
p
r
aisal
s
y
s
tem
s
h
av
e
r
elied
o
n
q
u
an
titativ
e
m
etr
ics
an
d
s
u
b
jectiv
e
ev
alu
atio
n
s
[
2
]
.
Ho
wev
er
,
in
teg
r
atin
g
m
u
lti
-
cr
iter
ia
d
ec
is
io
n
m
a
k
in
g
(
M
C
DM
)
tech
n
iq
u
es
i
n
to
th
is
p
r
o
ce
s
s
en
h
a
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ce
s
th
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b
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n
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n
ess
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m
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co
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s
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f
o
r
m
an
ce
d
im
en
s
io
n
s
s
im
u
ltan
eo
u
s
ly
[
3
]
,
[
4
]
.
MCDM
is
a
s
y
s
tem
atic
ap
p
r
o
ac
h
th
at
ass
is
t
s
d
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io
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-
m
ak
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s
in
ev
alu
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g
m
u
ltip
l
e
co
n
f
lictin
g
cr
iter
ia
wh
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m
ak
in
g
d
ec
is
io
n
s
[
5
]
.
I
n
th
e
co
n
te
x
t
o
f
p
e
r
f
o
r
m
an
ce
ap
p
r
aisal,
MCDM
ca
n
h
elp
o
r
g
an
izatio
n
s
ass
ess
n
o
t
o
n
ly
q
u
an
titativ
e
o
u
tp
u
ts
b
u
t
also
q
u
alitativ
e
f
ac
to
r
s
s
u
ch
as
wo
r
k
b
eh
av
io
r
s
co
r
es
an
d
em
p
lo
y
ee
s
'
p
er
f
o
r
m
a
n
ce
tar
g
ets
[
6
]
.
T
h
e
u
s
e
o
f
MCDM
in
p
er
f
o
r
m
an
ce
ap
p
r
ais
al
o
f
f
er
s
s
ev
er
al
b
en
ef
its
,
s
u
ch
as
im
p
r
o
v
in
g
tr
a
n
s
p
ar
e
n
cy
an
d
p
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m
o
ti
n
g
ca
r
ee
r
ad
v
a
n
ce
m
en
t
b
y
in
v
o
l
v
in
g
m
u
ltip
le
s
tak
eh
o
ld
er
s
in
th
e
d
ec
is
io
n
-
m
a
k
in
g
p
r
o
ce
s
s
[
7
]
.
Fu
r
th
er
m
o
r
e,
MCDM
f
r
am
ewo
r
k
s
f
ac
ilit
ate
th
e
id
en
tific
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n
o
f
tr
ai
n
in
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n
ee
d
s
an
d
d
ev
elo
p
m
en
t
o
p
p
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r
tu
n
ities
,
th
er
eb
y
f
o
s
ter
in
g
a
cu
ltu
r
e
o
f
co
n
tin
u
o
u
s
im
p
r
o
v
e
m
en
t [
8
]
,
[
9
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
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:
2
5
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I
n
d
o
n
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J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
509
-
5
2
2
510
Desp
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its
b
en
ef
its
,
th
e
im
p
lem
en
tatio
n
o
f
MCDM
in
p
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f
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r
m
an
ce
ap
p
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eq
u
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ca
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co
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s
id
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n
o
f
v
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s
f
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to
r
s
,
in
clu
d
in
g
th
e
s
elec
tio
n
o
f
a
p
p
r
o
p
r
iate
cr
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ia,
s
ta
k
eh
o
ld
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r
in
v
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e
n
t,
an
d
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co
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o
f
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d
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-
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ak
in
g
p
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s
s
[
1
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-
[
1
2
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.
Or
g
an
izatio
n
s
m
u
s
t
also
en
s
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r
e
th
at
em
p
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in
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p
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to
en
h
an
ce
ac
ce
p
ta
n
ce
an
d
ef
f
ec
tiv
e
n
ess
[
1
3
]
.
Giv
e
n
th
e
co
m
p
lex
ities
in
v
o
lv
ed
i
n
em
p
lo
y
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p
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f
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r
m
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ap
p
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—
f
r
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m
v
ar
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s
in
wo
r
k
lo
ad
to
th
e
n
ee
d
f
o
r
tailo
r
ed
cr
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ia
—
ch
o
o
s
in
g
th
e
m
o
s
t e
f
f
ec
tiv
e
M
C
DM
m
eth
o
d
is
cr
u
cial
[
1
4
]
.
A
co
m
p
ar
ativ
e
ex
p
er
im
en
t
in
MCDM
in
v
o
lv
es
s
y
s
tem
atic
ally
ev
alu
atin
g
v
ar
i
o
u
s
d
ec
is
io
n
-
m
ak
i
n
g
tech
n
iq
u
es
u
n
d
er
th
e
s
a
m
e
c
o
n
d
itio
n
s
t
o
d
ete
r
m
in
e
t
h
eir
r
elativ
e
ef
f
ec
tiv
e
n
ess
,
ac
cu
r
a
cy
,
an
d
c
o
n
s
is
ten
cy
[
1
5
]
.
T
h
e
m
o
s
t
co
m
m
o
n
ly
u
s
ed
MCDM
m
eth
o
d
s
in
clu
d
e
s
im
p
le
ad
d
itiv
e
weig
h
tin
g
(
SAW
)
,
an
aly
tic
h
ier
ar
ch
y
p
r
o
ce
s
s
(
AHP)
,
an
d
th
e
tech
n
iq
u
e
f
o
r
o
r
d
er
o
f
p
r
ef
er
en
ce
b
y
s
im
ilar
ity
to
id
ea
l
s
o
lu
tio
n
(
T
OPSIS)
[
1
6
]
.
E
ac
h
m
et
h
o
d
e
m
p
lo
y
s
d
if
f
er
en
t
a
p
p
r
o
ac
h
es
to
p
r
io
r
i
tize
cr
iter
ia
an
d
alter
n
ativ
es,
wh
ich
ca
n
lead
t
o
d
if
f
er
en
t
o
u
tco
m
es d
e
p
en
d
i
n
g
o
n
th
e
c
o
n
tex
t a
n
d
th
e
s
tr
ateg
i
c
o
b
jectiv
es o
f
th
e
ass
ess
m
en
t
[
1
7
]
-
[
1
9
]
.
I
n
a
co
m
p
ar
ativ
e
e
x
p
e
r
im
e
n
t,
d
ec
is
io
n
-
m
ak
er
s
ev
alu
ate
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
ese
m
eth
o
d
s
wh
en
ap
p
lied
to
s
p
ec
if
ic
d
atasets
an
d
d
ec
is
io
n
c
o
n
tex
ts
,
an
al
y
zin
g
th
e
s
tr
en
g
th
s
,
wea
k
n
ess
es,
a
n
d
p
o
ten
tial
b
iases
in
h
er
en
t
in
ea
ch
tech
n
i
q
u
e
[
2
0
]
,
[
2
1
]
.
Su
ch
s
tu
d
ies
o
f
ten
u
s
e
s
tati
s
tical
a
n
aly
s
i
s
tes
ts
l
ik
e
an
aly
s
is
o
f
v
ar
ian
ce
(
ANOV
A)
o
r
th
e
Frie
d
m
an
te
s
t
to
v
alid
ate
an
d
co
m
p
ar
e
th
e
r
esu
lts
,
en
s
u
r
in
g
th
at
th
e
r
es
ea
r
ch
is
r
o
b
u
s
t
an
d
r
eliab
le
[
2
2
]
.
T
h
is
co
m
p
ar
ativ
e
e
x
p
er
im
e
n
t
ap
p
r
o
ac
h
in
MCDM
lay
s
th
e
g
r
o
u
n
d
wo
r
k
f
o
r
a
d
ee
p
er
a
n
aly
s
is
th
at
gu
id
es
d
ec
is
io
n
-
m
ak
e
r
s
in
m
ak
in
g
in
f
o
r
m
ed
ch
o
ices
ab
o
u
t
t
h
e
m
o
s
t
ef
f
ec
tiv
e
an
d
r
elev
a
n
t
MCDM
m
eth
o
d
s
ac
co
r
d
in
g
to
th
e
s
p
ec
if
ic
n
ee
d
s
o
f
th
e
r
esear
ch
[
2
3
]
,
[
2
4
]
.
T
h
is
ar
ticle
f
o
cu
s
es
o
n
a
co
m
p
ar
ativ
e
ex
p
er
im
en
t
ap
p
r
o
ac
h
b
y
co
m
p
ar
in
g
th
e
SAW
,
AH
P,
an
d
T
OPSIS
m
eth
o
d
s
to
d
eter
m
in
e
th
e
ef
f
ec
tiv
e
n
ess
an
d
r
elev
an
ce
o
f
th
e
m
eth
o
d
s
ap
p
lied
in
a
n
e
m
p
lo
y
ee
p
er
f
o
r
m
an
ce
ap
p
r
aisal
s
y
s
tem
.
T
h
e
s
tu
d
y
aim
s
to
p
r
o
v
id
e
in
s
ig
h
ts
in
to
MCDM
m
eth
o
d
s
th
at
ca
n
b
e
im
p
lem
en
te
d
to
en
h
an
ce
p
er
f
o
r
m
a
n
ce
a
p
p
r
aisal
s
y
s
tem
s
in
o
r
g
an
izatio
n
al
en
v
ir
o
n
m
en
ts
[
2
5
]
.
T
h
e
f
o
llo
win
g
s
ec
tio
n
s
ar
e
s
t
r
u
ctu
r
ed
as
f
o
llo
ws.
I
n
s
ec
tio
n
2
,
th
e
m
eth
o
d
o
lo
g
y
o
f
th
is
s
tu
d
y
is
p
r
esen
ted
.
I
t
is
s
tar
ted
with
t
h
e
v
ar
ia
b
le
id
e
n
tific
atio
n
a
n
d
f
o
llo
wed
b
y
th
e
th
r
ee
MCDM
m
eth
o
d
s
:
SAW
,
AHP,
an
d
T
OPSIS.
I
n
s
ec
tio
n
3
,
th
e
m
a
in
r
esu
lts
r
eg
a
r
d
in
g
t
h
e
ev
alu
atio
n
o
f
th
o
s
e
th
r
ee
M
C
DM
m
e
th
o
d
s
ar
e
p
r
esen
ted
.
I
t
is
th
en
f
o
llo
wed
b
y
th
e
d
is
cu
s
s
io
n
r
elate
d
to
th
e
m
an
ag
er
ial
in
s
ig
h
ts
.
Fin
ally
,
s
ec
tio
n
4
co
n
clu
d
es th
e
s
tu
d
y
an
d
p
r
o
v
i
d
es r
ec
o
m
m
en
d
atio
n
s
b
ased
o
n
th
e
p
r
esen
te
d
s
tu
d
y
.
2.
ME
T
H
O
D
T
h
e
m
eth
o
d
o
lo
g
y
u
s
ed
in
th
is
s
tu
d
y
ad
o
p
ts
a
co
m
p
ar
ativ
e
e
x
p
er
im
en
t
a
p
p
r
o
ac
h
b
y
c
o
m
p
a
r
in
g
th
r
e
e
m
u
lti
-
cr
iter
ia
d
ec
is
io
n
-
m
ak
in
g
m
eth
o
d
s
b
ased
o
n
th
e
s
am
e
d
ataset
[
2
6
]
.
C
o
m
p
ar
ativ
e
ex
p
er
im
en
ts
ca
n
h
elp
id
en
tify
th
e
d
if
f
er
en
ce
s
a
n
d
s
im
ilar
ities
b
etwe
en
th
e
co
m
p
ar
ed
m
eth
o
d
s
,
lea
d
in
g
to
a
co
n
clu
s
io
n
[
2
7
]
.
T
h
is
ap
p
r
o
ac
h
in
v
o
lv
es
s
ev
er
al
p
r
o
ce
s
s
es,
in
clu
d
in
g
v
ar
iab
le
i
d
en
tific
atio
n
,
d
ata
co
llectio
n
,
d
ata
an
al
y
s
is
,
an
d
test
in
g
.
I
n
th
is
s
ec
tio
n
,
a
n
AN
OVA
test
is
co
n
d
u
cted
to
e
v
al
u
ate
th
e
r
esu
lts
f
r
o
m
th
e
co
m
p
ar
i
s
o
n
o
f
th
e
t
h
r
ee
m
eth
o
d
s
[
2
8
]
.
T
h
is
s
tu
d
y
f
o
c
u
s
es
o
n
s
elec
tin
g
an
ef
f
ec
tiv
e
a
n
d
r
ele
v
an
t
d
ec
is
io
n
-
m
ak
in
g
m
eth
o
d
f
o
r
u
s
e
in
an
em
p
lo
y
ee
p
er
f
o
r
m
a
n
ce
a
p
p
r
a
is
al
s
y
s
tem
b
y
c
o
m
p
ar
i
n
g
th
e
m
eth
o
d
s
u
s
ed
an
d
s
u
p
p
o
r
ti
n
g
th
e
f
i
n
d
in
g
s
b
y
r
ev
iewin
g
s
ev
er
al
s
im
ilar
s
tu
d
i
es
as
r
ef
er
en
ce
s
to
en
s
u
r
e
th
e
r
esear
ch
is
r
elev
an
t.
T
h
e
r
e
ar
e
f
o
u
r
s
tag
es
in
th
e
r
esear
ch
: id
en
tific
atio
n
v
ar
iab
l
e,
d
ata
co
llectio
n
,
d
ata
an
aly
s
i
s
,
an
d
test
in
g
[
2
9
]
.
Fig
u
r
e
1
s
h
o
ws
th
e
r
esear
c
h
s
tag
es
in
th
e
co
m
p
a
r
ativ
e
ex
p
er
im
en
t
a
p
p
r
o
ac
h
,
in
t
h
e
v
ar
iab
l
e
id
en
tific
atio
n
s
tag
e,
th
e
v
ar
iab
les
u
s
ed
in
th
is
ap
p
r
o
ac
h
ar
e
t
h
e
SAW
,
AHP,
an
d
T
OPSIS
m
eth
o
d
s
.
I
n
th
e
d
at
a
co
llectio
n
s
tag
e,
th
e
d
ata
is
b
a
s
ed
o
n
em
p
l
o
y
ee
in
f
o
r
m
atio
n
,
SKP
d
ata,
an
d
em
p
l
o
y
ee
p
e
r
f
o
r
m
an
ce
s
co
r
es.
I
n
th
e
d
ata
an
aly
s
is
s
tag
e,
th
e
d
ata
is
p
r
o
ce
s
s
ed
ac
co
r
d
i
n
g
to
th
e
ca
lcu
latio
n
s
o
f
ea
ch
m
eth
o
d
.
I
n
th
e
test
in
g
s
tag
e,
th
e
r
esu
lts
o
f
th
e
ca
lcu
l
atio
n
s
f
o
r
th
e
th
r
ee
m
eth
o
d
s
a
r
e
s
u
b
jecte
d
to
a
o
n
e
-
way
AN
OVA
test
to
o
b
tain
o
p
tim
al
r
esu
lts
[
3
0
]
.
Fig
u
r
e
1
.
R
esear
ch
s
tag
es in
c
o
m
p
ar
ativ
e
e
x
p
er
im
e
n
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
ffective
meth
o
d
s
fo
r
emp
lo
ye
e
p
erfo
r
ma
n
ce
a
s
s
ess
men
t
(
A
g
a
th
a
B
e
n
y
Hima
w
a
n
)
511
2
.
1
.
Va
ri
a
ble
i
dentif
ica
t
io
n
I
n
a
co
m
p
ar
ativ
e
e
x
p
er
im
e
n
t,
th
e
id
en
tific
atio
n
o
f
v
a
r
iab
les
is
a
cr
u
cial
f
ir
s
t
s
tep
to
en
s
u
r
e
th
at
th
e
an
aly
s
is
is
ac
cu
r
ate
an
d
r
elev
an
t.
Key
v
ar
iab
les
ar
e
d
ef
in
e
d
to
co
m
p
ar
e
th
e
p
er
f
o
r
m
an
ce
o
f
d
if
f
er
en
t
m
eth
o
d
s
o
r
tech
n
iq
u
es
u
n
d
e
r
s
im
ilar
c
o
n
d
itio
n
s
.
Fo
r
i
n
s
tan
ce
,
in
a
c
o
m
p
ar
ativ
e
s
tu
d
y
o
f
MCDM
m
eth
o
d
s
lik
e
SAW
,
AHP,
an
d
T
OPSIS,
th
e
v
a
r
iab
les
ty
p
ically
in
clu
d
e
th
e
cr
iter
i
a
u
s
ed
f
o
r
ev
al
u
atio
n
,
t
h
e
d
ata
s
et
b
ein
g
an
aly
ze
d
,
an
d
th
e
s
p
ec
if
ic
m
etr
ics
o
r
in
d
icato
r
s
th
at
w
ill
b
e
m
ea
s
u
r
ed
[
3
1
]
.
C
lear
ly
id
en
tif
y
in
g
th
es
e
v
ar
iab
les
h
elp
s
in
estab
lis
h
in
g
a
s
tr
u
ctu
r
ed
f
r
am
ewo
r
k
f
o
r
th
e
ex
p
er
im
en
t,
all
o
win
g
f
o
r
p
r
ec
is
e
co
m
p
a
r
is
o
n
s
an
d
en
s
u
r
in
g
th
at
an
y
o
b
s
er
v
ed
d
i
f
f
er
en
ce
s
in
o
u
tco
m
es a
r
e
d
u
e
t
o
th
e
m
eth
o
d
s
th
em
s
elv
es r
ath
er
th
an
ex
ter
n
al
f
ac
to
r
s
.
2
.
1
.
1
.
Sim
ple
a
dd
it
iv
e
weig
h
t
ing
T
h
e
SAW
m
eth
o
d
f
i
n
d
s
th
e
b
est
alter
n
ativ
e
o
f
all
alter
n
a
tiv
e
ev
alu
atio
n
in
d
ices
[
3
2
]
.
T
h
e
b
asic
co
n
ce
p
t
o
f
th
e
SAW
m
eth
o
d
is
to
f
in
d
th
e
weig
h
ted
s
u
m
o
f
th
e
p
er
f
o
r
m
an
ce
r
an
k
i
n
g
s
f
o
r
ea
ch
o
p
tio
n
.
T
h
e
SAW
m
eth
o
d
r
eq
u
ir
es
n
o
r
m
alizin
g
th
e
d
ec
is
io
n
m
atr
ix
t
o
a
s
ca
le
th
at
ca
n
b
e
co
m
p
ar
ed
with
all
o
th
er
alter
n
ativ
e
o
r
d
e
r
s
.
T
h
e
SAW
m
eth
o
d
h
as
s
ev
er
al
s
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3
8
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b
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n
t
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bs
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P
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I
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5
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6
mo
n
t
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F
u
n
c
t
i
o
n
a
l
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
ffective
meth
o
d
s
fo
r
emp
lo
ye
e
p
erfo
r
ma
n
ce
a
s
s
ess
men
t
(
A
g
a
th
a
B
e
n
y
Hima
w
a
n
)
513
T
ab
le
2
s
h
o
ws
th
e
weig
h
ts
o
f
ea
ch
cr
iter
io
n
b
ased
o
n
th
e
2
0
1
9
g
o
v
er
n
m
en
t
r
eg
u
latio
n
.
T
h
e
cr
iter
ia
f
o
r
ass
ess
in
g
em
p
lo
y
ee
p
e
r
f
o
r
m
an
ce
ar
e
s
er
v
ice,
ac
c
o
u
n
tab
i
lity
,
co
m
p
ete
n
ce
,
h
a
r
m
o
n
y
,
l
o
y
alty
,
ad
a
p
tab
ilit
y
,
co
llab
o
r
atio
n
,
a
n
d
em
p
l
o
y
ee
wo
r
k
g
o
als
[
4
0
]
.
T
h
e
ass
ess
m
en
t
p
ar
am
eter
s
f
o
r
ea
c
h
cr
i
ter
io
n
ar
e
d
if
f
e
r
en
t.
T
ab
le
4
s
h
o
ws
th
e
ass
ess
m
en
t
p
ar
am
eter
s
f
o
r
th
e
s
er
v
ice
cr
i
ter
ia,
h
ar
m
o
n
io
u
s
,
lo
y
al,
ad
ap
tiv
e,
co
llab
o
r
ativ
e,
an
d
SKP.
T
ab
le
5
s
h
o
ws
th
e
ass
es
s
m
en
t
p
ar
am
eter
s
f
o
r
th
e
ac
co
u
n
tab
le
s
tan
d
ar
d
s
.
T
ab
le
6
s
h
o
ws
th
e
ass
es
s
m
en
t
p
ar
am
eter
s
f
o
r
th
e
co
m
p
ete
n
cy
cr
iter
ia.
T
ab
le
7
s
h
o
ws
th
e
ca
lcu
latio
n
r
esu
lts
o
f
th
e
SKP
s
co
r
es
f
o
r
ea
ch
em
p
lo
y
ee
.
T
ab
le
4
.
Par
am
eter
s
o
f
s
er
v
ice
cr
iter
ia,
h
ar
m
o
n
y
,
lo
y
alty
,
ad
ap
tiv
e,
co
llab
o
r
ativ
e,
an
d
SKP
P
a
r
a
me
t
e
r
s
C
a
t
e
g
o
r
y
9
1
–
100
V
e
r
y
g
ood
7
6
–
90
G
o
o
d
6
1
-
75
En
o
u
g
h
5
1
-
60
Le
ss
0
-
50
B
a
d
T
ab
le
5
.
Acc
o
u
n
tab
le
cr
iter
ia
p
ar
am
eter
s
P
r
e
sen
c
e
%
C
a
t
e
g
o
r
y
9
1
–
100
1
8
1
–
90
2
7
1
-
80
3
6
1
-
70
4
0
–
60
5
T
ab
le
6
.
C
o
m
p
ete
n
ce
cr
iter
ia
p
ar
am
eter
s
C
o
m
p
e
t
e
n
c
e
%
C
a
t
e
g
o
r
y
9
1
–
100
1
8
1
–
90
2
7
1
–
80
3
6
1
-
70
4
0
-
60
5
T
ab
le
7
.
C
alcu
latio
n
o
f
e
m
p
l
o
y
ee
SKP
v
alu
e
Emp
l
o
y
e
e
Ta
r
g
e
t
(
%)
R
e
a
l
i
z
a
t
i
o
n
S
K
P
v
a
l
u
e
P1
1
0
0
85
.
67
85
.
67
P2
1
0
0
85
.
72
85
.
72
P3
1
0
0
86
86
P4
1
0
0
85
.
58
85
.
58
P5
1
0
0
85
.
69
85
.
69
P6
1
0
0
85
.
72
85
.
72
P7
1
0
0
85
.
73
85
.
73
P8
1
0
0
85
.
68
85
.
68
P9
1
0
0
85
.
55
85
.
55
P
1
0
1
0
0
85
.
81
85
.
81
P
1
1
1
0
0
85
.
64
85
.
64
P
1
2
1
0
0
85
.
69
85
.
69
P
1
3
1
0
0
86
86
P
1
4
1
0
0
87
.
02
87
.
02
P
1
5
1
0
0
86
.
47
86
.
47
P
1
6
1
0
0
85
.
68
85
.
68
T
h
e
g
lo
b
al
atm
o
s
p
h
er
ic
m
o
n
ito
r
in
g
s
tatio
n
in
So
r
o
n
g
h
as
1
6
f
u
n
ctio
n
al
em
p
lo
y
e
es
wh
o
s
e
p
er
f
o
r
m
an
ce
ass
ess
m
en
ts
wer
e
ca
r
r
ied
o
u
t.
E
m
p
l
o
y
ee
p
er
f
o
r
m
an
ce
ev
alu
atio
n
is
b
ased
o
n
SKP
v
alu
es
a
n
d
em
p
lo
y
ee
wo
r
k
b
e
h
av
io
r
v
alu
es.
T
h
e
em
p
lo
y
ee
p
er
f
o
r
m
a
n
c
e
is
ca
lcu
lated
b
y
u
s
in
g
th
e
f
o
r
m
u
la
as f
o
llo
ws:
=
∗
0
.
6
+
ℎ
∗
0
.
4
(
7
)
wh
er
ea
s
th
e
SKP ac
h
iev
em
en
t
is
ca
lcu
lated
b
y
u
s
in
g
th
e
f
o
r
m
u
la
as f
o
llo
ws:
SKP
=
Real
i
zat
i
o
n
T
ar
g
e
t
×
100
(
8
)
T
h
e
r
esu
lts
ar
e
s
h
o
wn
in
T
ab
le
7
.
As
s
h
o
wn
in
T
ab
le
7
,
th
e
ca
lcu
latio
n
r
esu
lts
o
f
th
e
S
KP
s
co
r
es
f
o
r
ea
ch
em
p
lo
y
ee
ar
e
b
ased
o
n
(
8
)
.
2
.
3
.
Da
t
a
a
na
ly
s
is
T
h
e
d
ata
an
aly
s
is
em
p
lo
y
ed
in
th
is
s
tu
d
y
in
v
o
lv
es
ex
am
in
i
n
g
an
d
in
ter
p
r
etin
g
th
e
co
llec
ted
d
ata
to
id
en
tify
d
if
f
er
en
ce
s
a
n
d
s
im
i
lar
ities
b
e
twee
n
th
e
m
eth
o
d
s
b
ein
g
e
v
alu
ated
,
c.
f
.
[
4
1
]
.
I
n
th
e
co
n
tex
t
o
f
a
co
m
p
ar
ativ
e
s
tu
d
y
o
f
MCD
M
tech
n
iq
u
es,
th
e
d
ata
an
al
y
s
is
in
clu
d
es
ap
p
ly
in
g
ea
c
h
m
eth
o
d
t
o
th
e
s
am
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
509
-
5
2
2
514
d
ataset,
f
o
llo
wed
b
y
a
s
y
s
tem
atic
ev
alu
atio
n
o
f
th
e
o
u
tco
m
es.
I
t
p
r
o
v
id
es
cr
u
cial
i
n
s
ig
h
t
s
i
n
to
th
e
s
tr
en
g
th
s
an
d
wea
k
n
ess
es
o
f
ea
ch
tech
n
iq
u
e
in
v
o
l
v
ed
in
th
e
s
tu
d
y
,
h
elp
in
g
to
d
r
aw
co
n
clu
s
io
n
s
,
co
n
s
is
ten
cy
,
an
d
ef
f
ec
tiv
en
ess
in
th
e
d
ec
is
io
n
-
m
ak
in
g
,
cf
.
[
4
2
]
.
T
h
is
s
tag
e
is
co
n
d
u
cte
d
to
en
s
u
r
e
th
at
th
e
e
x
p
er
im
en
t'
s
f
in
d
in
g
s
ar
e
r
o
b
u
s
t
an
d
r
eliab
le
,
lead
i
n
g
to
i
n
f
o
r
m
ed
d
ec
is
io
n
s
[
4
3
]
.
I
n
th
is
s
tag
e,
th
e
co
llected
d
ataset
is
an
aly
ze
d
u
s
in
g
th
e
SAW
,
AHP,
an
d
T
OPSIS m
eth
o
d
s
.
2
.
3
.
1
.
SAW
m
et
ho
d
I
n
th
e
SAW
m
eth
o
d
,
th
e
f
ir
s
t s
tep
is
to
g
r
o
u
p
th
e
ex
is
tin
g
cr
iter
ia
in
to
two
ty
p
es o
f
attr
ib
u
tes:
b
en
ef
it
an
d
c
o
s
t
[
4
4
]
.
T
h
e
d
is
tr
ib
u
ti
o
n
o
f
ch
ar
ac
ter
is
tics
o
n
ea
ch
cr
iter
io
n
is
s
h
o
wn
in
T
ab
le
8
.
Me
an
wh
ile,
th
e
em
p
lo
y
ee
a
p
p
r
aisal d
ata
an
d
t
h
e
n
o
r
m
alize
d
d
ata
ar
e
s
h
o
wn
in
T
ab
les 9
an
d
1
0
,
r
esp
ec
tiv
el
y
.
Af
ter
n
o
r
m
alizin
g
em
p
lo
y
ee
d
ata,
th
e
r
an
k
in
g
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t.
T
h
e
p
r
ef
e
r
en
c
e
v
alu
e
is
o
b
tain
ed
b
y
m
u
ltip
ly
in
g
ea
c
h
cr
iter
io
n
weig
h
t
with
th
e
n
o
r
m
alize
d
v
alu
e
[
4
5
]
.
T
h
en
,
a
weig
h
ted
s
u
m
m
atio
n
o
f
all
c
r
iter
ia
is
p
er
f
o
r
m
e
d
.
T
h
e
r
an
k
i
n
g
r
esu
lts
ca
n
b
e
s
ee
n
in
T
ab
le
1
1
.
Of
th
e
1
6
e
m
p
lo
y
ee
s
at
PAG
So
r
o
n
g
Statio
n
,
it
was
f
o
u
n
d
th
at
P1
5
em
p
lo
y
ee
s
r
an
k
e
d
f
ir
s
t
with
a
p
r
ef
er
en
ce
v
alu
e
o
f
0
.
9
8
2
2
2
4
,
th
e
s
ec
o
n
d
r
an
k
was
o
cc
u
p
ied
b
y
P1
4
em
p
lo
y
ee
s
with
a
p
r
ef
er
en
ce
v
alu
e
o
f
0
.
9
8
0
8
7
4
a
n
d
th
e
th
ir
d
r
an
k
was
o
cc
u
p
ied
b
y
P2
em
p
lo
y
ee
s
with
a
p
r
ef
er
en
ce
v
alu
e
0
.
9
7
8
1
3
.
T
ab
le
8
.
Ass
ess
m
en
t
cr
iter
ia
an
d
weig
h
t
C
o
d
e
A
t
t
r
i
b
u
t
e
W
e
i
g
h
t
C1
B
e
n
e
f
i
t
1
0
%
C2
C
o
s
t
5%
C3
C
o
s
t
5%
C4
B
e
n
e
f
i
t
5%
C5
B
e
n
e
f
i
t
5%
C6
B
e
n
e
f
i
t
5%
C7
B
e
n
e
f
i
t
5%
C8
B
e
n
e
f
i
t
6
0
%
T
ab
le
9
.
E
m
p
lo
y
ee
a
p
p
r
aisal d
ata
C1
C2
C3
C4
C5
C6
C7
C8
P1
86
1
1
81
80
80
84
85
.
7
P2
85
1
1
87
82
84
87
85
.
7
P3
90
1
2
85
85
83
84
86
P4
87
1
2
86
80
82
83
85
.
6
P5
86
2
2
86
81
84
84
85
.
7
P6
85
1
2
87
82
88
86
85
.
7
P7
84
1
3
88
83
86
80
85
.
7
P8
83
1
3
84
84
81
84
85
.
7
P9
87
1
3
86
85
82
83
85
.
6
P
1
0
85
1
2
83
84
84
86
85
.
8
P
1
1
86
4
4
82
83
84
87
85
.
6
P
1
2
88
3
3
84
82
85
88
85
.
7
P
1
3
80
1
1
86
81
86
89
86
P
1
4
82
1
1
84
80
87
84
87
P
1
5
82
1
1
82
86
90
86
86
.
5
P
1
6
86
1
1
80
82
82
81
85
.
7
T
ab
le
1
0
.
N
o
r
m
aliza
tio
n
o
f
e
m
p
lo
y
ee
v
alu
e
C1
C2
C3
C4
C5
C6
C7
C8
P1
0
.
96
1
1
81
80
80
84
85
.
7
P2
0
.
94
1
1
87
82
84
87
85
.
7
P3
1
1
0
.
5
85
85
83
84
86
P4
0
.
97
1
0
.
5
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7
T
ab
le
1
1
.
R
an
k
in
g
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s
in
g
SAW
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eth
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d
Emp
l
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y
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k
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9
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2
2
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1
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6
0
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7
9
0
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0
6
5
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
ffective
meth
o
d
s
fo
r
emp
lo
ye
e
p
erfo
r
ma
n
ce
a
s
s
ess
men
t
(
A
g
a
th
a
B
e
n
y
Hima
w
a
n
)
515
2
.
3
.
2
.
AH
P
m
e
t
ho
d
C
alcu
latio
n
s
u
s
in
g
th
e
AH
P
m
eth
o
d
in
th
e
em
p
lo
y
ee
p
er
f
o
r
m
an
ce
ass
ess
m
en
t
s
y
s
tem
wer
e
ca
r
r
ied
o
u
t
to
d
eter
m
in
e
th
e
r
esu
ltin
g
co
m
p
a
r
is
o
n
f
r
o
m
t
h
e
th
r
e
e
te
ch
n
iq
u
es,
n
am
ely
t
h
e
AHP,
S
AW
,
an
d
T
OPSIS
m
eth
o
d
s
.
I
n
th
e
AHP
m
eth
o
d
,
th
e
f
ir
s
t
s
tep
is
to
d
eter
m
in
e
th
e
co
m
p
a
r
is
o
n
m
atr
ix
b
e
twee
n
cr
iter
ia
[
4
6
]
.
T
h
e
cr
iter
ia
co
m
p
ar
is
o
n
m
atr
ix
ca
n
b
e
s
ee
n
in
T
ab
le
1
2
,
an
d
th
e
ca
lcu
latio
n
r
esu
lts
o
f
p
r
io
r
ity
s
ee
n
in
T
ab
le
1
3
.
Ob
tain
in
g
an
alter
n
ativ
e
r
a
n
k
in
g
r
eq
u
ir
es
th
e
co
n
s
is
ten
cy
in
d
ex
v
al
u
e
(
C
I
)
,
t
h
e
in
d
e
x
r
atio
v
alu
e
(
R
I
)
,
an
d
th
e
co
n
s
is
ten
cy
r
atio
v
alu
e
(
C
R
)
.
I
f
th
e
C
R
v
alu
e
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g
es
f
r
o
m
0
t
o
0
.
1
,
th
en
h
ier
a
r
ch
ical
co
n
s
is
ten
cy
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ac
ce
p
tab
le,
b
u
t
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v
alu
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m
o
r
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an
0
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1
,
t
h
en
it
is
co
n
s
id
er
ed
in
co
n
s
is
ten
t
[
4
7
]
.
T
h
e
C
R
v
alu
e
in
th
is
ca
lcu
latio
n
is
0
.
0
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wh
ich
m
ea
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th
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th
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ier
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h
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tab
le.
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h
e
alter
n
ativ
e
r
an
k
in
g
is
d
o
n
e
to
f
in
d
th
e
h
ig
h
est
s
co
r
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ased
o
n
th
e
em
p
lo
y
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er
f
o
r
m
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ce
ap
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tem
.
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ter
o
b
tain
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g
th
e
alter
n
ativ
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alu
e
s
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th
e
last
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is
to
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eter
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in
e
th
e
alter
n
ativ
e
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an
k
in
g
r
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lts
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y
m
u
ltip
ly
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g
th
e
v
alu
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o
f
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c
h
cr
iter
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o
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ain
s
t
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ch
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r
io
r
it
y
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al
u
e
o
f
t
h
e
cr
it
er
ia
m
atr
ix
.
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h
e
r
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lts
ca
n
b
e
s
ee
n
in
T
a
b
le
1
4
.
T
h
e
f
ir
s
t
r
a
n
k
was
o
b
tain
ed
b
y
s
ix
em
p
lo
y
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s
with
t
h
e
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am
e
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e
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en
ce
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alu
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f
0
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2
8
3
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.
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1
em
p
l
o
y
ee
s
r
ec
eiv
ed
th
e
lo
west sco
r
e
with
a
p
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e
o
f
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2
3
5
0
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ab
le
1
2
.
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r
iter
ia
co
m
p
ar
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o
n
m
atr
ix
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
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1
3
3
3
3
3
3
0
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2
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1
1
1
1
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1
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1
1
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1
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1
1
1
1
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1
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7
7
7
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7
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1
To
t
a
l
7
.
98
16
16
16
16
16
16
2
.
04
T
ab
le
1
3
.
T
h
e
r
esu
lt o
f
ca
lcu
la
tin
g
p
r
io
r
ity
v
alu
e
a
n
d
eig
e
n
v
alu
e
C
r
i
t
e
r
i
a
Ei
g
e
n
v
a
l
u
e
P
r
i
o
r
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t
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u
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c
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0
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0
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3
9
1
4
4
0
T
ab
le
1
4
.
R
an
k
in
g
u
s
in
g
AHP
m
eth
o
d
Emp
l
o
y
e
e
R
e
s
u
l
t
R
a
n
k
P1
0
.
2
8
3
7
1
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0
.
2
8
3
7
1
P3
0
.
2
7
1
9
2
P4
0
.
2
7
1
9
2
P5
0
.
2
6
0
0
4
P6
0
.
2
7
1
9
2
P7
0
.
2
6
4
1
3
P8
0
.
2
6
4
1
3
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0
.
2
6
4
1
3
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1
0
0
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2
7
1
9
2
P
1
1
0
.
2
3
5
0
6
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1
2
0
.
2
4
4
6
5
P
1
3
0
.
2
8
3
7
1
P
1
4
0
.
2
8
3
7
1
P
1
5
0
.
2
8
3
7
1
P
1
6
0
.
2
8
3
7
1
2
.
3
.
3
.
T
O
P
SI
S
m
et
ho
d
C
alcu
latio
n
s
u
s
in
g
th
e
T
OPS
I
S
m
eth
o
d
in
th
e
p
er
f
o
r
m
an
c
e
ass
es
s
m
en
t
s
y
s
tem
ar
e
ca
r
r
ied
o
u
t
t
o
d
eter
m
in
e
wh
ich
wa
y
h
as
th
e
ac
cu
r
ac
y
an
d
p
r
ec
is
io
n
o
f
u
s
e
in
s
o
lv
in
g
p
r
o
b
lem
s
[
4
8
]
.
I
n
t
h
e
T
OPSIS
m
eth
o
d
,
th
e
f
ir
s
t
s
tep
is
to
d
eter
m
i
n
e
t
h
e
weig
h
t
cr
iter
ia
a
n
d
d
e
ter
m
in
e
th
e
v
alu
e
o
f
ea
ch
alter
n
ativ
e.
Af
ter
s
elec
tin
g
th
e
r
eq
u
ir
em
en
ts
an
d
v
al
u
e
o
f
ea
ch
o
p
tio
n
,
th
e
n
cr
ea
te
a
n
o
r
m
alize
d
d
ec
is
io
n
m
at
r
ix
wh
ich
ca
n
b
e
s
ee
n
in
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
509
-
5
2
2
516
T
ab
le
1
5
.
T
h
e
n
ex
t
s
tep
is
to
cr
ea
te
a
weig
h
ted
n
o
r
m
alize
d
d
ec
is
io
n
m
atr
ix
b
y
m
u
ltip
ly
i
n
g
ea
ch
a
lter
n
ativ
e
n
o
r
m
alize
d
d
ec
is
io
n
m
atr
ix
ag
ain
s
t
th
e
weig
h
t
o
f
ea
ch
cr
iter
i
o
n
[
4
9
]
.
T
h
e
r
esu
lts
ca
n
b
e
s
ee
n
in
T
ab
le
1
6
.
T
h
e
n
ex
t
s
tep
is
d
eter
m
in
in
g
t
h
e
d
is
tan
ce
b
etwe
en
th
e
alter
n
ativ
e
v
alu
es
a
n
d
th
e
i
d
ea
l
s
o
lu
tio
n
m
atr
ix
s
h
o
wn
in
T
ab
les 1
7
an
d
1
8
.
T
h
e
last
s
tep
is
to
d
eter
m
in
e
t
h
e
p
r
e
f
er
en
c
e
v
alu
e
o
r
r
an
k
in
g
in
T
ab
le
1
9
.
T
ab
le
1
5
.
Valu
es in
d
eter
m
in
i
n
g
th
e
n
o
r
m
alize
d
d
ec
is
io
n
m
a
tr
ix
W
e
i
g
h
t
[x
1
]
[x
2
]
[x
3
]
[x
4
]
[x
5
]
[x
6
]
[x
7
]
[x
8
]
V
a
l
u
e
3
4
0
.
6
3
7
6
6
.
4
8
0
7
4
1
8
.
8
3
1
7
6
1
3
3
7
.
8
7
1
3
3
3
0
.
0
8
1
8
3
3
7
.
1
5
8
7
3
3
9
.
1
3
1
2
4
3
4
3
.
4
1
5
7
Emp
l
o
y
e
e
C
r
i
t
e
r
i
a
C1
C2
C3
C4
C5
C6
C7
C8
P1
0
.
2
5
2
4
6
8
0
.
1
5
4
3
0
3
0
.
1
1
3
2
2
8
0
.
2
3
9
7
3
6
0
.
2
4
2
3
6
4
0
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2
3
7
2
7
7
0
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2
4
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6
9
1
7
0
.
2
4
9
4
6
4
P2
0
.
2
4
9
5
3
2
0
.
1
5
4
3
0
3
0
.
1
1
3
2
2
8
0
.
2
5
7
4
9
5
0
.
2
4
8
4
2
3
0
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2
4
9
1
4
1
0
.
2
5
6
5
3
7
9
0
.
2
4
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6
1
P3
0
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2
6
4
2
1
0
.
1
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4
3
0
3
0
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2
2
6
4
5
5
0
.
2
5
1
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7
5
0
.
2
5
7
5
1
2
0
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2
4
6
1
7
5
0
.
2
4
7
6
9
1
7
0
.
2
5
0
4
2
5
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0
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5
5
4
0
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1
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4
3
0
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0
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2
2
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4
5
5
0
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2
5
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4
.
ANO
VA
t
esting
ANOV
A
test
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wh
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s
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ei
n
g
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al
u
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[
5
0
]
.
B
y
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al
y
zin
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th
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c
e
am
o
n
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m
u
ltip
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g
r
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u
p
s
,
AN
OVA
h
elp
s
id
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e
d
if
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ap
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.
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th
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tex
t
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f
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p
ar
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g
MCDM
tech
n
iq
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a
o
n
e
-
way
ANO
VA
test
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n
a
s
s
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s
wh
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d
s
lik
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SAW
,
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lied
to
th
e
s
am
e
d
at
aset.
T
h
is
s
ta
tis
tica
l
te
s
t
is
cr
u
cial
f
o
r
v
alid
atin
g
th
e
ef
f
ec
tiv
en
ess
an
d
r
eliab
il
ity
o
f
ea
c
h
m
eth
o
d
u
n
d
e
r
th
e
s
am
e
co
n
d
itio
n
s
,
en
s
u
r
in
g
th
at
c
o
n
clu
s
io
n
s
d
r
a
wn
f
r
o
m
t
h
e
co
m
p
ar
ativ
e
s
tu
d
y
ar
e
r
o
b
u
s
t a
n
d
ac
cu
r
ate
[
5
1
]
.
T
h
e
f
o
r
m
u
la
f
o
r
th
e
o
n
e
-
way
ANOV
A
te
s
t
is
p
r
im
ar
ily
b
ased
o
n
p
ar
titi
o
n
i
n
g
th
e
to
tal
v
a
r
ian
ce
in
to
b
etwe
en
-
g
r
o
u
p
v
a
r
ian
ce
an
d
with
in
-
g
r
o
u
p
v
ar
ian
ce
.
T
h
e
f
o
r
m
u
la
ca
lcu
lates
th
e
F
-
r
atio
,
wh
ich
is
th
e
r
atio
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
ffective
meth
o
d
s
fo
r
emp
lo
ye
e
p
erfo
r
ma
n
ce
a
s
s
ess
men
t
(
A
g
a
th
a
B
e
n
y
Hima
w
a
n
)
517
th
ese
two
v
ar
ian
ce
s
to
d
eter
m
in
e
if
th
e
m
ea
n
s
o
f
d
if
f
er
en
t
g
r
o
u
p
s
ar
e
s
ig
n
if
ican
tly
d
if
f
er
en
t.
T
h
e
f
o
r
m
u
la
is
st
ated
as f
o
llo
ws:
=
ℎ
(
9
)
wh
er
e
F
is
th
e
ANOV
A
s
tatis
t
ic
v
alu
e,
MS
b
etw
ee
n
is
th
e
th
e
m
ea
n
s
q
u
ar
e
b
etwe
en
g
r
o
u
p
s
,
an
d
MS
w
ith
in
is
th
e
m
ea
n
s
q
u
a
r
e
with
in
g
r
o
u
p
s
.
T
h
e
cr
iter
ia
is
s
h
o
wn
in
T
ab
l
e
2
0
.
T
ab
le
1
8
.
T
h
e
d
is
tan
ce
b
etwe
e
n
alter
n
ativ
e
v
al
u
es a
n
d
th
e
i
d
ea
l so
lu
tio
n
C
a
t
e
g
o
r
y
Emp
l
o
y
e
e
V
a
l
u
e
D+
P1
0
.
0
0
3
4
0
3
5
2
P2
0
.
0
0
2
9
2
9
3
4
P3
0
.
0
0
6
0
8
8
3
7
P4
0
.
0
0
6
5
0
0
8
P5
0
.
0
1
0
0
1
7
4
9
P6
0
.
0
0
6
3
2
7
5
P7
0
.
0
1
1
7
7
7
3
7
P8
0
.
0
1
1
8
6
0
7
P9
0
.
0
1
1
7
4
2
1
3
P
1
0
0
.
0
0
6
3
4
8
3
6
P
1
1
0
.
0
2
8
8
6
5
9
2
P
1
2
0
.
0
1
9
3
2
1
8
5
P
1
3
0
.
0
0
3
5
7
8
7
1
P
1
4
0
.
0
0
2
7
2
6
4
3
P
1
5
0
.
0
0
2
7
2
4
5
3
P
1
6
0
.
0
0
3
3
8
0
4
5
D
-
P1
0
.
0
2
8
7
6
9
6
4
P2
0
.
0
2
8
7
9
2
3
7
P3
0
.
0
2
5
9
7
7
3
5
P4
0
.
0
2
5
8
6
9
2
3
P5
0
.
0
1
9
2
6
0
6
8
P6
0
.
0
2
5
8
7
5
0
3
P7
0
.
0
2
3
9
0
9
0
6
P8
0
.
0
2
3
8
6
7
9
7
P9
0
.
0
2
3
9
5
0
6
6
P
1
0
0
.
0
2
5
8
4
5
2
9
P
1
1
0
.
0
0
2
1
9
9
6
3
P
1
2
0
.
0
0
9
9
7
6
6
6
P
1
3
0
.
0
2
8
7
7
7
7
3
P
1
4
0
.
0
2
8
8
5
9
8
8
P
1
5
0
.
0
2
8
8
2
7
0
6
P
1
6
0
.
0
2
8
7
6
6
8
5
T
ab
le
1
9
.
Dete
r
m
in
in
g
t
h
e
p
r
e
f
er
en
ce
v
al
u
e
A
l
t
e
r
n
a
t
i
v
e
P
r
e
f
e
r
e
n
c
e
R
a
n
k
P1
0
.
8
9
4
2
1
2
5
P2
0
.
9
0
7
6
5
5
3
P3
0
.
8
1
0
1
2
8
7
P4
0
.
7
9
9
1
7
2
10
P5
0
.
6
5
7
8
5
1
14
P6
0
.
8
0
3
5
0
9
8
P7
0
.
6
6
9
9
7
6
12
P8
0
.
6
6
8
0
3
4
13
P9
0
.
6
7
1
0
2
2
11
P
1
0
0
.
8
0
2
8
0
7
9
P
1
1
0
.
0
7
0
8
0
6
16
P
1
2
0
.
3
4
0
5
1
8
15
P
1
3
0
.
8
8
9
3
9
7
6
P
1
4
0
.
9
1
3
6
8
3
1
P
1
5
0
.
9
1
3
6
4
9
2
P
1
6
0
.
8
9
4
8
4
5
4
T
ab
le
2
0
.
ANOV
A
test
in
g
cr
it
er
ia
A
l
p
h
a
t
e
s
t
i
n
g
c
r
i
t
e
r
i
a
5%
P
-
V
a
l
u
e
<
0
.
05
Th
e
r
e
i
s
a
si
g
n
i
f
i
c
a
n
t
d
i
f
f
e
r
e
n
c
e
P
-
V
a
l
u
e
>
0
.
05
N
o
d
i
f
f
e
r
e
n
c
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
509
-
5
2
2
518
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
co
m
p
ar
is
o
n
b
etwe
en
th
e
SAW
,
AHP,
an
d
T
OPSIS
m
eth
o
d
s
was
co
n
d
u
cted
u
s
in
g
th
e
s
am
e
d
ataset
with
in
th
e
co
n
te
x
t
o
f
an
em
p
lo
y
ee
p
e
r
f
o
r
m
an
ce
a
p
p
r
aisal
s
y
s
tem
[
5
2
]
.
T
h
e
d
ata
s
et
in
clu
d
ed
cr
iter
ia
s
u
ch
as
s
er
v
ice,
ac
co
u
n
ta
b
ilit
y
,
co
m
p
ete
n
ce
,
alig
n
m
en
t,
lo
y
alty
,
ad
ap
tab
ilit
y
,
c
o
llab
o
r
atio
n
,
an
d
ac
h
iev
em
en
t
o
f
tar
g
ets.
3
.
1
.
Co
m
pa
riso
n bet
wee
n SAW,
AH
P
,
a
nd
T
O
P
SI
S
m
et
ho
d
T
h
e
co
m
p
a
r
is
o
n
r
esu
lts
b
et
wee
n
th
e
SAW
,
AHP,
an
d
T
OPSIS
m
eth
o
d
s
in
th
e
em
p
lo
y
ee
p
er
f
o
r
m
an
ce
ass
ess
m
en
t
ca
n
b
e
s
ee
n
in
Fig
u
r
e
2
[
5
3
]
.
I
n
Fig
u
r
e
2
,
it
ca
n
b
e
s
ee
n
th
at
t
h
e
b
est
em
p
lo
y
ee
b
ased
o
n
ca
lcu
latio
n
u
s
in
g
th
e
SAW
m
eth
o
d
was
g
iv
en
to
P1
5
,
wh
o
r
an
k
e
d
f
i
r
s
t
with
a
v
alu
e
r
an
g
e
o
f
0
.
9
8
2
2
2
.
Dif
f
er
en
t
r
esu
lts
wer
e
o
b
tain
e
d
wh
en
ca
lc
u
latin
g
em
p
lo
y
ee
p
er
f
o
r
m
an
ce
ass
ess
m
en
t
u
s
in
g
th
e
AHP
m
eth
o
d
.
T
h
e
f
ir
s
t r
an
k
is
g
iv
en
to
em
p
l
o
y
ee
s
P1
,
P2
,
P1
3
,
P1
4
,
P1
5
,
a
n
d
P1
6
b
ec
au
s
e
th
ey
h
av
e
th
e
s
am
e
v
alu
es.
T
OPSIS
m
eth
o
d
,
th
e
f
ir
s
t
r
a
n
k
was
g
i
v
en
t
o
P1
4
em
p
l
o
y
ee
with
a
p
r
ef
er
e
n
ce
v
alu
e
o
f
0
.
9
1
3
6
8
.
T
h
er
e
is
d
if
f
er
en
t
c
o
m
p
ar
e
d
t
o
th
e
SAW
m
eth
o
d
an
d
th
e
T
OPSIS
m
eth
o
d
in
d
eter
m
in
in
g
th
e
b
est
em
p
lo
y
ee
;
in
th
e
SAW
m
eth
o
d
,
th
e
b
est
em
p
lo
y
ee
was
g
iv
en
to
P1
5
,
wh
ile
in
th
e
T
OPSIS
m
eth
o
d
,
th
e
b
est
em
p
lo
y
ee
was
ass
ig
n
ed
to
P1
4
.
Ho
we
v
er
,
b
ased
o
n
th
e
ass
ess
m
en
t
o
f
wo
r
k
b
eh
av
i
o
r
b
etwe
en
P
1
4
a
n
d
P1
5
i
n
th
e
ac
co
u
n
tab
le
o
r
atten
d
a
n
ce
ca
t
eg
o
r
y
,
P1
5
h
as
a
n
atten
d
a
n
ce
p
er
ce
n
tag
e
o
f
1
0
0
%
wh
e
r
ea
s
P1
4
h
as
th
e
9
5
%
atten
d
an
ce
p
er
ce
n
ta
g
e.
I
n
ad
d
itio
n
,
P1
5
h
as
th
e
p
o
s
itio
n
as
th
e
o
b
s
er
v
atio
n
f
ield
co
o
r
d
i
n
ato
r
with
a
lar
g
e
r
wo
r
k
lo
ad
t
h
an
P1
4
,
an
d
h
is
wo
r
k
in
g
h
o
u
r
is
also
lo
n
g
e
r
th
an
P1
4
.
T
h
e
SAW
m
eth
o
d
h
as
b
ee
n
p
r
o
v
e
d
to
b
e
th
e
m
o
s
t
ef
f
ec
ti
v
e
an
d
r
elev
an
t
ap
p
r
o
ac
h
f
o
r
ev
alu
atin
g
em
p
lo
y
ee
p
er
f
o
r
m
a
n
ce
in
th
is
co
n
tex
t.
T
h
e
p
r
ef
er
en
ce
v
alu
es
ca
lcu
lated
u
s
in
g
SAW
s
h
o
wed
a
h
ig
h
lev
el
o
f
ac
cu
r
ac
y
,
alig
n
i
n
g
well
with
th
e
ex
p
ec
ted
o
u
tco
m
es f
o
r
t
h
e
g
iv
en
d
ataset.
T
h
is
m
eth
o
d
d
ir
ec
tly
ag
g
r
eg
ates th
e
weig
h
ted
s
co
r
es
o
f
ea
c
h
cr
ite
r
io
n
,
p
r
o
v
id
in
g
a
s
tr
aig
h
t
f
o
r
war
d
an
d
tr
an
s
p
a
r
en
t
r
a
n
k
in
g
s
y
s
tem
.
T
h
e
SAW
m
eth
o
d
co
n
s
is
ten
tly
r
a
n
k
ed
em
p
lo
y
ee
s
b
ased
o
n
t
h
eir
p
er
f
o
r
m
a
n
ce
c
r
iter
ia
with
o
u
t
o
v
er
lap
p
i
n
g
s
co
r
es,
ac
cu
r
ately
r
e
f
lectin
g
v
a
r
iatio
n
s
in
wo
r
k
lo
a
d
s
an
d
r
esp
o
n
s
ib
ilit
ies.
Pre
f
er
en
ce
v
alu
es
in
th
e
SAW
m
eth
o
d
wer
e
clo
s
ely
alig
n
ed
with
th
e
d
at
aset,
s
h
o
win
g
th
at
th
is
m
et
h
o
d
e
f
f
ec
tiv
ely
ca
p
tu
r
e
d
th
e
n
u
an
ce
s
o
f
ea
ch
em
p
lo
y
ee
'
s
p
er
f
o
r
m
an
ce
.
SAW
’
s
s
im
p
le
ca
lcu
latio
n
p
r
o
c
ess
f
ac
ilit
ated
q
u
ick
ev
alu
atio
n
s
an
d
m
in
im
ized
co
m
p
lex
ity
,
m
ak
in
g
it
a
p
r
ac
t
ical
ch
o
ice
f
o
r
o
r
g
an
izatio
n
al
s
ettin
g
s
[
5
4
]
.
T
h
e
AHP
m
eth
o
d
was
f
o
u
n
d
to
b
e
less
p
r
ec
is
e
in
th
i
s
s
p
ec
if
ic
ca
s
e
d
u
e
to
th
e
n
atu
r
e
o
f
its
p
air
wis
e
co
m
p
ar
is
o
n
s
an
d
c
o
m
p
lex
weig
h
tin
g
s
tr
u
ctu
r
e.
Alth
o
u
g
h
AHP
allo
ws
f
o
r
d
etailed
co
m
p
ar
is
o
n
an
d
r
an
k
in
g
o
f
cr
iter
ia
b
ased
o
n
th
eir
r
elativ
e
im
p
o
r
tan
ce
.
I
n
s
o
m
e
in
s
tan
ce
s
,
AHP
as
s
ig
n
ed
eq
u
al
r
an
k
s
to
em
p
lo
y
ee
s
d
esp
ite
d
if
f
er
e
n
c
es
in
wo
r
k
lo
ad
an
d
p
er
f
o
r
m
an
ce
,
r
e
d
u
cin
g
its
ef
f
ec
tiv
en
ess
in
d
is
tin
g
u
is
h
in
g
b
etwe
en
to
p
an
d
b
o
tto
m
p
e
r
f
o
r
m
e
r
s
[
5
5
]
.
T
h
e
p
air
wis
e
co
m
p
ar
is
o
n
p
r
o
ce
s
s
in
AHP
is
m
o
r
e
tim
e
-
i
n
ten
s
iv
e
an
d
r
eq
u
i
r
es
ex
ten
s
iv
e
in
p
u
t
f
r
o
m
d
ec
is
io
n
-
m
a
k
e
r
s
,
w
h
i
c
h
m
a
y
n
o
t
b
e
s
u
it
a
b
l
e
f
o
r
s
c
e
n
a
r
i
o
s
r
e
q
u
i
r
i
n
g
q
u
i
c
k
d
e
c
is
i
o
n
-
m
a
k
i
n
g
.
T
h
e
r
el
ia
n
c
e
o
n
s
u
b
je
c
t
i
v
e
j
u
d
g
m
e
n
t
s
f
o
r
a
s
s
i
g
n
i
n
g
r
e
l
at
i
v
e
w
e
i
g
h
ts
i
n
t
r
o
d
u
c
e
d
p
o
t
e
n
t
i
al
b
i
a
s
,
m
a
k
i
n
g
it
l
es
s
o
b
j
ec
t
i
v
e
co
m
p
a
r
e
d
t
o
S
AW
.
T
h
e
T
OPSIS
m
eth
o
d
,
w
h
ile
u
s
ef
u
l
f
o
r
cr
ea
tin
g
a
v
is
u
al
g
ap
an
aly
s
is
b
etwe
en
ea
ch
em
p
lo
y
ee
an
d
a
n
id
ea
l
s
o
lu
tio
n
,
s
h
o
wed
lim
itatio
n
s
wh
en
ap
p
lied
to
th
is
d
at
aset.
T
OPSIS
r
an
k
in
g
s
d
id
n
o
t
ac
cu
r
ately
r
ef
lect
th
e
r
elativ
e
wo
r
k
lo
ad
s
an
d
r
e
s
p
o
n
s
ib
ilit
ies
o
f
th
e
em
p
lo
y
ee
s
,
lead
in
g
to
p
o
ten
tially
m
is
lead
in
g
r
esu
lts
[
5
6
]
.
T
h
is
m
eth
o
d
was
h
ig
h
ly
s
en
s
itiv
e
to
th
e
weig
h
tin
g
s
ass
ig
n
ed
to
cr
iter
ia,
wh
ich
in
f
lu
e
n
ce
d
th
e
f
in
al
r
an
k
in
g
s
s
ig
n
if
ican
tly
,
m
a
k
in
g
it
ch
alle
n
g
in
g
to
m
ain
tain
co
n
s
is
ten
cy
ac
r
o
s
s
d
if
f
er
en
t
co
n
tex
ts
.
T
O
PS
I
S
in
v
o
lv
es
m
o
r
e
co
m
p
lex
ca
lcu
latio
n
s
co
m
p
ar
e
d
to
SAW
,
wh
ich
ca
n
in
cr
ea
s
e
th
e
lik
elih
o
o
d
o
f
e
r
r
o
r
s
d
u
r
in
g
im
p
lem
en
tatio
n
.
Fig
u
r
e
2
.
C
o
m
p
a
r
is
o
n
c
h
a
r
t o
f
SAW
,
AHP,
an
d
T
OPSIS
m
et
h
o
d
0
0,2
0,4
0,6
0,8
1
P1
P2
P3
P4
P5
P6
P7
P8
P9
P10
P11
P12
P13
P14
P15
P16
Pref
e
re
n
ce
Valu
e
E
m
p
loy
e
e
S
A
W
A
H
P
T
O
PSIS
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