Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
21
,
No.
3
,
Ma
rch
202
1
,
pp. 1
868~
1876
IS
S
N: 25
02
-
4752, DO
I: 10
.11
591/ijeecs
.v2
1
.i
3
.
pp
1868
-
1876
1868
Journ
al h
om
e
page
:
http:
//
ij
eecs.i
aesc
or
e.c
om
Develop
ment of
an inv
entory ma
nagemen
t system
usin
g
associati
on rul
e
Ti
nuke
O
. O
l
adel
e
1
, Roseli
n
e Oluw
as
e
un Ogu
nd
ok
u
n
2
, Adek
an
mi
Ade
yink
a Ade
gun
3
, Emm
an
uel
Ab
idem
i
Ad
e
niyi
4
, Ay
obam
i T
ayo Ajan
aku
5
1
Depa
rtment of
Com
pute
r
Scie
n
ce
,
Univer
si
t
y
of
Ilori
n
,
I
lo
rin
,
Ni
ger
ia
2,3,4,5
Depa
rtment
of
Com
pute
r
Sci
enc
e
,
La
ndm
ark
Univer
sit
y
Om
u
Aran,
Nig
eri
a
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
A
pr
2
0
, 202
0
Re
vised N
ov 1, 20
20
Accepte
d
Ja
n 7
, 2021
Stores
today
st
il
l
m
ake
use
of
m
a
nual
appr
oa
che
s
to
kee
pi
ng
inv
en
tor
y
whi
ch
coul
d
be
cumbersom
e.
Having
a
computer
ized
in
vent
or
y
s
y
st
em
would
m
ake
inve
ntor
y
m
anagem
ent
m
ore
e
ffic
i
ent
and
eff
ec
t
ive
.
In
thi
s
cha
pt
er,
an
Inve
ntor
y
Mana
gement
S
y
stem
using
As
socia
ti
on
Rule
was
deve
lope
d
whic
h
will
ensure
pro
per
re
cor
d
k
eeping
and
ke
ep
it
ems
in
stoc
ks
updat
ed.
AN
GU
LAR
JS
,
a
Java
Scrip
t
fra
m
ework,
was
used
for
th
e
imple
m
ent
at
ion
of
the
s
y
st
em,
PH
P
(h
y
p
ert
ex
t
pre
-
proc
essor)
was
used
for
the
ba
c
kend
of
th
e
s
y
stem
develop
m
ent
as
well
as
the
da
ta
b
ase
m
a
nage
m
ent
,
HTML
was
used
al
ongside
CS
S
f
or
the
s
y
stem
in
t
erf
ace
design
an
d
NoS
QL
dat
ab
ase
was
the
dat
ab
ase
used
f
or
thi
s
re
se
arc
h
.
In
con
cl
usion
,
a
computer
ize
d
inve
nto
r
y
s
y
stem
tha
t
h
ad
bee
n
improved
using
the
associa
ti
on
ru
le
m
et
h
od
was
the
re
sulti
ng
produc
t
useful
for
creat
ing
tr
ansa
ct
ion
s,
updating
i
te
m
s
in
stock
,
re
cor
d
k
ee
ping
,
gene
ra
ti
ng
r
epor
ts
for
decision
m
aki
ng
,
and la
stl
y
,
th
e
s
y
st
em
will
m
ake t
h
e
st
ore
s m
ore
eff
ecti
v
e.
Ke
yw
or
d
s
:
Aprio
ri alg
or
it
hm
Data m
anag
em
ent syst
em
Data m
ining
Inve
nto
ry
syst
em
Stor
es
This
i
s an
open
acc
ess arti
cl
e
un
der
the
CC
B
Y
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
Ogu
ndokun,
R
os
el
ine
Oluwas
eun
Dep
a
rtm
ent o
f C
om
pu
te
r
Scie
nce
Lan
dm
ark
Univers
it
y Om
u
A
ran
Kw
a
ra S
ta
te
,
Ni
ger
ia
Em
a
il
: og
undo
kun.r
os
el
ine@l
m
u.
edu
.
ng
1.
INTROD
U
CTION
Inve
nto
ry
m
anag
em
ent
syst
e
m
is
a
co
m
pu
te
r
-
base
d
syst
em
m
eant
fo
r
st
al
kin
g
i
nvent
ory
intensit
ie
s
[1
-
5]
,
re
qu
isi
ti
on
(
dem
and
s),
transacti
ons
,
and
sup
plies.
This
ca
n
as
w
el
l
be
us
e
d
i
n
the
m
anu
fact
ur
i
ng
bu
si
ne
sses
to
br
in
g
ab
out
a
wo
r
k
re
quest
,
in
vo
ic
e
of
re
source
s
tog
et
he
r
with
diff
e
ren
t
int
err
el
at
e
d
m
anu
fact
ur
i
ng
recor
ds
.
Inve
ntory
m
anag
em
ent
so
ft
war
e
is
an
in
strum
ent
that
is
us
e
d
f
or
co
nsoli
dati
ng
inv
e
ntory
inform
ation
[6
-
10]
that
pr
evio
usl
y
was
collected
in
hard
cop
ie
s
f
or
m
at
or
spreads
he
et
s.
T
o
m
ai
ntain
acco
un
t
rec
ords
c
om
petentl
y,
firm
ow
ne
rs
a
r
e
re
qu
i
red
to
i
m
ple
m
ent
an
e
xcell
ent
in
ven
t
ory
m
anag
em
ent
syst
e
m
.
Stock
i
n
busi
ness
c
onsti
tutes
a
huge
par
t
of
t
he
in
ve
st
m
ent
wh
ic
h
ha
s
to
be
orga
ni
zed
in
seq
uen
ce
t
o
m
axim
iz
e
to
yi
eld
fi
nan
ci
al
gai
n.
Inve
ntorie
s
are
un
depen
da
ble
an
d
i
nco
m
petent
e
xcep
t
t
hey
are
well
coor
din
at
ed
[11]
.
Data
Mi
ning
is
a
co
nce
pt
w
hi
ch
al
so
re
fer
s
to
as
knowle
dg
e
disco
ve
ry
in
database
(
KDD)
is
one
of
the
fastest
-
gr
owin
g
fiel
ds
in
com
pu
te
r
sci
ence
w
hich
m
e
et
s
the
rap
idly
increasin
g
ne
eds
of
inf
or
m
at
ion
an
d
knowle
dge
dis
cov
e
ry.
Data
m
ining
ope
rates
with
m
ulti
d
isc
ipli
nar
y
do
m
ai
ns
su
ch
as
database
te
c
hnol
og
y
,
inf
or
m
at
ion
r
et
rieval,
patte
rn
rec
ogniti
on,
m
achine
l
earn
i
ng,
sta
ti
sti
cs,
arti
fici
al
intel
li
gen
ce,
dat
a
visu
al
iz
at
ion
,
a
nd
hi
gh
-
perfor
m
ance
com
pu
t
ing
[12
,
13]
.
A
sso
ci
at
ion
te
ch
niques
functi
on
by
obta
inin
g
a
set
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Develo
pm
e
nt
of
a
n i
nve
nto
ry
man
ag
e
me
nt s
yst
em usin
g as
so
ci
atio
n
r
ule
(
Tinu
ke
O.
Oladel
e
)
1869
of
r
obus
t
ass
oc
ia
ti
on
ru
le
s
tha
t
will
com
e
up
with
sp
eci
fic
de
sign
s
in
an
unsu
pe
r
vised
kn
owle
dge
syst
e
m
[1
4,
15]
.
Ma
rk
et
ba
sk
et
in
vestiga
ti
on
op
e
rates
with
ass
ociat
ion
r
ule
w
hich
assist
s
in
m
a
king
bette
r
in
ven
t
ory
m
anag
em
ent syst
e
m
s.
The
a
utho
rs
use
d
A
NGUL
A
RJS,
P
HP,
H
TML
,
CSS
,
a
nd
N
oSQL
da
ta
base
f
or
the
desi
gn
an
d
i
m
ple
m
entat
io
n
of
the
i
nv
e
nt
or
y
m
anag
em
e
nt
syst
em
.
HTML
was
us
e
d
m
ai
nl
y
in
desi
gn
i
ng
the
i
nter
face
of
the
in
ve
nto
ry
s
yst
e
m
and
str
uc
turing
it
t
o
be
well
def
in
ed
.
CSS
was
al
s
o
us
e
d
al
on
gs
ide
HTML
in
the
desig
n
of
the
in
ve
ntor
y
syst
e
m
.
AN
GU
L
ARJS
wa
s
us
ed
for
the
entire
de
velo
pm
ent
of
the
ap
plica
ti
on
w
hile
PH
P
was
a
ppli
ed
f
or
t
he
de
velo
pme
nt
of
t
he
e
ntir
e
bac
kend
of
t
he
syst
em
fo
r
t
he
d
at
abase
m
anag
em
ent
an
d
APIs.
NoSQL
databa
se
is
the
database
that
was
m
ade
us
e
of
i
n
stori
ng
al
l
the
data
that
w
as
util
iz
ed
du
r
ing
the
dev
el
op
m
ent
of
the
i
nv
e
nt
ory
syst
e
m
.
Last
ly
,
the
data
m
ining
a
pp
ro
ac
h
[16
-
18]
wa
s
us
e
d
to
im
pr
ove
the
inv
e
ntory
m
an
agem
ent
syst
e
m
and
the
a
ppro
ac
h
us
ed
is
the
a
sso
ci
at
io
n
ru
le
w
hic
h
w
as
al
so
us
e
d
f
or
th
e
disco
ver
y
of
in
te
resti
ng
relat
ion
s
betwee
n
va
riables
a
nd
al
so
us
e
d
for
pr
e
dicti
ng
the
de
m
and
for
good
s
f
uture.
Apr
io
ri alg
or
it
hm
w
as also
use
d for the
ass
oc
ia
ti
on
rule a
ppr
oac
h
[19
-
22]
.
Aprio
ri
is
a
f
undam
ental
al
gorithm
for
m
ining
rec
urrin
g
it
e
m
set
s
in
e
nor
m
ou
s
databa
se
s,
nu
m
ero
us
var
ia
nts
of
the
Aprio
ri
co
nce
ntrate
on
m
aking
bette
r
the
c
om
petency
of
t
he
earli
est
al
gorithm
as
well
as
the
dev
el
op
m
ent
of
the
al
gorithm
fo
r
oth
e
r
in
ves
ti
gated
subj
e
ct
area.
Ma
ny
ex
cel
le
nt
publica
ti
on
s
su
m
m
ari
ze
this
top
ic
, f
or
e
xam
ple
[23
-
29, 17]
an
d
s
om
e relat
ed wor
ks
a
re
discuss
e
d
as
foll
ow
s:
Pr
a
gya,
Ma
da
n
&
Nup
ur
[30]
researc
he
d
the
a
p
ri
or
i
al
go
rith
m
wh
ic
h
was
de
velo
ped
in
j
a
va
an
d
was
an
ass
ociat
ion
dr
i
ving
m
ining
app
li
cat
ion.
T
heir
m
et
ho
d
co
uld
be
ap
plied
to
m
anag
e
m
erch
an
disin
g
de
a
li
ng
s
wh
ic
h
deliver
m
erch
ants
with
detai
ls
co
nce
rn
i
ng
t
he
forec
ast
ing
of
pro
duct
sal
es
tre
nd
s
as
well
as
co
ns
um
er
at
ti
tud
es.
A
pr
i
or
i
al
gorithm
was
e
nh
a
nce
d
in
the
as
pect
of the
tim
e
co
m
plexity
,
nu
m
ber
o
f
database
s
sc
ann
e
d,
us
a
ge
of
m
e
mo
ry
,
a
nd
t
he
cur
i
os
it
y
of
the
ru
le
s
ov
e
r
the
cl
assic
al
a
pr
ior
i
al
go
rithm
.
The
rec
urred
it
e
m
set
s
rev
eal
e
d
reli
es
on
the
value
of
fact
ur
es
s
uch
as
s
uppo
r
t
and
the
nu
m
ber
of
tra
ns
act
ion
s
bein
g
rea
d
at
a
par
ti
cula
r
tim
e,
therefore
,
the
i
m
ple
m
entat
io
n
tim
e
of
the
al
gorithm
reli
es
on
t
he
transact
ion
al
data
gr
oup
a
nd
the m
ini
m
u
m
s
upport
value
.
Kh
a
rwar,
Kapadia,
Pr
a
j
a
pati,
&
Pate
l
[31]
util
iz
ed
associ
at
ion
r
ule
m
ining
usual
ly
to
identify
th
e
su
pe
rm
ark
et
or
m
anag
e
m
ent
of
in
ven
t
or
y
strat
egy.
Asso
ci
at
ion
ru
le
m
ining
was
ap
pl
ie
d
for
we
b
us
a
ge
m
ining
.
W
e
b
usa
ge
m
ining
and
ass
ociat
ion
ru
le
m
ining
w
ere
m
erg
ed
to
enh
a
nce
the
s
ubsta
nce
of
the
se
rv
e
log
data.
T
he
a
uthors
m
ade
use
of
t
he
Aprio
r
i
al
gorithm
as
well
as g
e
ner
at
ed
ass
ociat
io
n
Rule
f
ro
m
ser
ve
r
lo
g
wh
ic
h
w
as
us
e
fu
l
in
m
any
app
li
cat
ion
s
s
uc
h
as
cache
f
or
web
pa
ges,
m
a
rk
et
in
g,
ta
rg
et
e
d
a
dv
e
rtisi
ng
,
and
a
lot m
or
e
.
Oladip
upo
&
Oyel
ade
[
19]
e
xam
ined
edu
c
at
ion
al
data
m
ining
with
the
us
e
of
the
ass
ociat
ion
ru
l
e
m
ining
m
et
ho
d
f
or
rec
ogniz
ing
st
ud
e
nts’
f
ai
lure
patte
r
ns
.
The
stu
dy
re
cognizes
the
c
on
ceal
e
d
c
orre
la
ti
on
betwee
n
the
f
ai
le
d
course
of
stud
ie
s
an
d
reco
m
m
end
ed
appr
opriat
e
so
ur
ces
for
the
f
ai
lure
of
stu
de
nts
to
increase
t
he
l
ow
capaci
ty
of
stu
den
ts
’
pe
rfor
m
ances.
An
obse
rv
at
io
n
was
de
du
ce
d
that
t
he
ti
m
e
of
i
m
ple
m
entat
io
n
of
the
m
et
ho
d
was
co
ntra
riwise
pro
portio
nate
to
the
le
ast
su
pport
beca
us
e
it
increases
as
the
le
ast
su
pp
or
t
dim
inishes
we
r
e
the
refo
re
es
ta
blished
an
increm
ent
in
t
he
syst
em
com
plexit
y
and
reacti
on
per
i
od
s
just
as
the
le
ast
su
ppor
t
re
duces.
T
he
are
19
re
cu
rr
in
g
it
em
set
s
and
114
r
ules
wer
e
pr
oduce
d.
T
he
auth
or
,
there
fore,
co
nclu
de
d
that
ever
y
sin
gle
on
e
of
the
r
ul
es
with
confi
de
nce
1
is
a
very
strong
ru
le
.
This
inv
a
riably
i
m
plies,
if
a
stud
ent
fail
ed
the
determ
inant
course
of
stud
y
,
su
ch
stu
de
nt
will
su
rely
fail
th
e
dep
e
ndent
co
urse(s
).
T
he
aut
hors
th
us
sugge
ste
d
that
this
ru
le
sho
uld
be
enlist
ed
in
the
curriculum
structu
re.
Fu
rt
her
m
or
e,
i
f
the
r
ule
support
is
highe
r,
this
m
eans
al
l
t
he
co
urse
s
of
stud
y
bei
ng
as
so
ci
at
ed
wit
h
by
th
e
stud
e
nts
wer
e
al
l
fail
ed
toge
ther
by
m
os
t
especial
ly
th
e
stud
ie
d
stu
de
nts.
Last
ly
,
the
sugg
e
ste
d
m
et
ho
d
assist
ed
in
the
curricul
um
str
uctu
re
as
well
as
in
m
od
ific
at
ion
to
im
pr
ove
stu
de
nts’
a
cadem
ic
per
for
m
ance
and to t
rim
d
ow
n t
he fai
lure
ra
te
A
de
w
ole et
al,
[
27]
.
AL
-
Zawai
dah,
Jb
ara
&
A
bu
-
Z
anona
[32]
pos
tulat
ed
an
as
soc
ia
ti
on
r
ule
m
i
ning
te
ch
nique
that
co
uld
com
petentl
y
ascerta
in
the
ass
ociat
ion
r
ules
i
n
e
norm
ou
s
da
ta
bases.
This
postulat
ed
te
ch
ni
qu
e
was
ori
gi
nated
from
the
or
th
odox
A
pr
i
or
i
m
et
ho
d
with
s
ever
al
ad
diti
onal
qual
it
ie
s
t
o
increa
se
the
perform
ance
of
data
m
ining
.
C
om
pr
ehe
ns
ive
ex
pe
rim
entation
s
w
ere
im
ple
m
ent
ed
a
nd
t
he
al
gorithm
perfor
m
ances
th
at
is
bo
t
h
the
existi
ng
al
gori
thm
and
the
new
al
go
rithm
wer
e
com
pared
an
d
the
com
par
is
on
s
howe
d
that
the
stud
y
su
ggest
e
d
m
e
t
hod
outpe
rfo
r
m
ed
the
existi
ng
m
et
ho
ds
a
nd
it
cou
ld
s
pe
edily
discov
e
r
fr
e
qu
e
nt
it
e
m
s
et
s
and
eff
ect
ively
m
ine potenti
al
ass
ociat
ion
r
u
le
s
.
In
s
umm
ary, th
is sessi
on
had
been
a
ble to cover
var
i
ou
s t
opic
s w
hich
i
nclu
de
in
ven
t
or
y m
anag
em
ent
syst
e
m
s
.
In
ve
nt
or
y
was
sim
pl
y
def
ine
d
as
st
ock
ta
king
a
nd
an
in
ven
t
or
y
m
anag
em
ent
syst
e
m
is
a
co
m
pu
te
r
-
base
d
syst
em
fo
r
t
rack
i
ng
in
ve
ntory
le
vels,
s
al
es,
orde
rs
,
an
d
deliveries.
T
he
im
po
rtance
of
t
he
a
pp
li
cat
ion
of
data
m
ining
w
as
al
so
po
i
nted
out.
Data
m
i
ning
was
de
fin
ed
as
si
m
ply
t
he
process
of
analy
zi
ng
data
fr
om
diff
e
re
nt
per
s
pe
ct
ives
and
s
um
m
arizi
ng
it
i
nto
us
e
f
ul
inform
ation
.
Va
rio
us
te
chn
i
qu
e
s
us
e
d
in
data
m
ining,
wh
ic
h
inclu
de:
associat
ion
,
f
or
ecast
in
g,
cl
a
ssific
at
ion
,
a
nd
cl
us
te
ring,
to
m
ention
a
few
wer
e
al
so
disc
us
se
d.
Also
,
va
rio
us
al
gorithm
s
have
been
c
onsid
ered,
su
c
h
as
Aprio
ri,
S
VM,
K
-
m
eans
,
an
d
so
on.
Ha
ving
f
ully
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
21
, N
o.
3
,
Ma
rc
h
2021
:
1868
-
1876
1870
consi
der
e
d
th
ose
top
ic
s,
it
ca
n
the
refor
e
be
sai
d
that
ap
plica
ti
on
of
data
m
ining
to
in
ve
ntory
m
anag
em
ent
is
ver
y
im
po
rtant
and
ver
y
hel
pful.
T
he
w
or
l
d
is
beco
m
ing
m
or
e
a
dv
a
nce
d
e
ver
y
day
a
nd
it
is
al
so
beco
m
i
ng
a
com
pu
te
rized
world
,
extracti
ng
knowle
dge
fo
r
al
rea
dy
avail
able
inf
orm
at
ion
play
s
a
vital
ro
le
i
n
the
dev
el
op
m
ent of the
wor
l
d
.
2.
RESEA
R
CH MET
HO
D
In
t
he
sam
e
way
that
it
w
as
earli
er
disc
us
se
d,
t
his
res
earch
f
ocused
on
the
de
vel
op
m
ent
of
a
n
inv
e
ntory
m
an
agem
ent
syst
e
m
and
the
i
nve
ntory
syst
e
m
wo
ul
d
be
able
t
o
carry o
ut v
ari
ou
s
f
un
ct
i
on
s s
uch
as:
getti
ng
up
date o
f
it
em
s
in
stock,
k
ee
ping adequ
at
e rec
ords of
product in stock, carr
yi
ng out p
r
oper calcu
la
ti
on
of
product
so
l
d,
placi
ng
orde
r
s
to
supp
li
ers
vi
a
el
ect
ro
nic
-
m
ai
l
(e
-
m
a
il
),
send
i
ng
a
no
ti
fic
at
ion
to
a
us
e
r
wh
e
n
a
product
is
about
to
be
s
ol
d
out
com
pletely
,
gen
erate
r
eport
ei
ther
da
il
y
rep
or
t,
wee
kly
repor
t,
m
on
thly
repor
t,
ye
arly
r
eport
or
repor
t
fo
r
s
pecific
da
ys
that
do
no
t
fall
between
tho
s
e
cat
egorie
s
(f
or
exam
ple
it
can
be
decide
d
t
o
gen
e
rate
repor
t
betwee
n
M
on
day
an
d
Tue
sda
y
al
on
e
an
d
s
o
on).
The
syst
e
m
sta
rts
with
a
logi
n
pag
e
,
w
h
ere
it
pr
om
pts
the
us
er
to
input
the
us
er
nam
e
and
pass
w
ord,
if
the
us
e
r
nam
e
and
passw
or
d
corres
pond w
it
h
that al
read
y s
aved
in
t
he
dat
abase it
p
r
ocee
ds
and is conne
ct
ed
oth
e
rw
is
e it
sta
ys on
th
e log
in
pag
e
a
nd
in
for
m
s
the
us
er
t
ha
t
a
wrong
us
e
rn
am
e
or
pa
ss
word
has
bee
n
inputt
ed,
bu
t
i
f
the
us
er
has
n’t
bee
n
create
d
at
al
l,
t
he
us
e
r
w
ou
l
d
then
just
create
an
acco
un
t
or
add
a
use
r.
T
he
log
in
pag
e
is
need
e
d
as
a
m
e
asu
r
e
of
sec
ur
it
y,
so
no
on
e
e
xc
e
pt
auth
or
iz
e
d
pe
r
so
ns
w
ou
l
d
acce
ss
the
inv
e
nt
or
y
syst
em
.
I
f
t
he
log
i
n
is
su
c
cessf
ul
the
us
e
r
can
now
decide
w
he
ther
to
a
dd
ne
w
stoc
k,
dele
te
stock,
upda
te
stock,
see
the
go
ods
avail
able,
purc
hase
or sell
g
oo
ds
or eve
n view
the
sal
es
repor
t
(eit
he
r d
ai
ly
,
week
ly
, m
on
thly
,
or ye
arly
)
.
Algo
rithm
f
or
the In
ven
t
or
y
Ma
nag
em
ent S
yst
e
m
1.
Start.
2.
Check
if
the
use
r
e
xists.
3.
If
t
he
us
er
ex
is
ts g
o
to
6.
4.
Else
5.
Creat
e u
se
r
6.
Lo
gin
i
nto
t
he a
ccount
7.
Sele
ct
the
desir
ed op
e
rati
on.
8.
If
t
he
op
e
rati
on selec
te
d i
s
product
go to 1
4.
9.
Else
if
the
ope
r
at
ion
selec
te
d i
s sales
go to 2
5.
10.
Else
if
the
ope
r
at
ion
selec
te
d i
s sup
plier
go to
35.
11.
Else
if
the
ope
r
at
ion
selec
te
d
orders
to
go t
o 41.
12.
Else
G
e
ner
at
e
repor
t.
13.
Go to 4
3.
14.
Sele
ct
the
desir
ed op
e
rati
on fo
r
a
pro
du
ct
.
15.
If
t
he
op
e
rati
on selec
te
d i
s Add p
r
oduct
go to 22.
16.
Else
if
the
ope
r
at
ion
selec
te
d i
s Mana
ge purc
hases.
17.
Com
pu
te
the t
otal cost
of pu
r
chase
T
he
t
otal cost
of pur
c
hase
=
a
m
ou
nt
of
pro
du
ct
* Q
uan
ti
t
y t
o
be
pu
rch
as
ed
18.
Ma
na
ge
pur
c
ha
se.
19.
Go to 4
3.
20.
Else
Mana
ge p
rod
uct.
21.
Go to 4
3.
22.
Enter p
rod
uct
detai
ls.
23.
Add pro
duct
.
24.
Go to 4
3.
25.
Sele
ct
the
desir
ed op
e
rati
on fr
om
sales.
26.
If
t
he
op
e
rati
on selec
te
d i
s Add sal
es
go to 29.
27.
Else
Mana
ge
S
al
es
28.
Go to 4
3
29.
Searc
h
f
or a
product.
30.
Inp
ut the desc
r
ipti
on
of the
pr
oduct
31.
Inp
ut the q
uan
t
it
y t
o
be
s
old.
32.
Com
pu
te
the t
otal cost
of sal
es
T
he
t
otal cost
of sale
s=am
ou
nt of
pro
du
ct
*qua
ntit
y sold
33.
Ma
ke
sal
es.
34.
Go to 4
2.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Develo
pm
e
nt
of
a
n i
nve
nto
ry
man
ag
e
me
nt s
yst
em usin
g as
so
ci
atio
n
r
ule
(
Tinu
ke
O.
Oladel
e
)
1871
35.
Sele
ct
the
desir
ed op
e
rati
on fo
r
s
upplier
oper
at
ion
.
36.
If
t
he
op
e
rati
on selec
te
d i
s Add sup
plier
go
to 38.
37.
Else
m
anag
e s
upplier
go to
43.
38.
Enter su
ppli
er
detai
ls.
39.
Add
s
upplier
go to 4
3.
40.
Enter
the
detai
ls of
the
pro
du
ct
to
be
or
der
e
d.
41.
Ma
ke or
der g
o t
o
43.
42.
Applic
at
ion o
f a
pr
i
or
i al
go
rith
m
.
43.
Stop.
Figure
1
sho
w
s
the
dev
el
ope
d
syst
e
m
flow
char
t
w
hich
e
xp
la
in
s
the
functi
on
al
it
y
of
the
syst
e
m
.
Figure
2
sho
w
s
the
us
e
c
ase
diag
ram
fo
r
th
e
dev
el
oped
a
pp
li
cat
io
n
w
hi
ch
s
hows
al
l
the
entit
ie
s
involve
d
in
the d
e
velo
pm
ent of t
he
syst
e
m
an
d
their
va
r
iou
s
acti
on
s
.
Figure
1
.
Pro
gra
m
f
lowc
har
t
Evaluation Warning : The document was created with Spire.PDF for Python.
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S
N
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2502
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4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
21
, N
o.
3
,
Ma
rc
h
2021
:
1868
-
1876
1872
Figure
2
.
Pro
gra
m
u
se case
di
agr
am
3.
RESU
LT
S
A
ND
D
IS
C
USS
ION
This
sessi
on
di
scusse
d
the
im
plem
entat
ion
of
the
i
nv
e
ntory
m
anag
e
m
ent
syst
e
m
,
the
va
rio
us
pag
es
include
d
in
th
e
s
yst
e
m
,
the
var
i
ou
s
op
e
rati
on
s
ca
rr
ie
d
out
in
the
syst
e
m
,
and
al
so
sc
re
ens
ho
ts
of
the
entire
syst
e
m
and
ex
planati
ons
of
how
t
hey
operat
e
.
The
l
og
i
n
pa
ge
is
nee
de
d
as
a
m
easur
e
of
secu
rity
.
The
lo
gi
n
pag
e
is
s
how
n
in
Fi
gure
3
.
I
t
ens
ur
es
that
on
ly
a
uthorize
d
per
s
onnel
ca
n
acce
ss
the
i
nv
e
ntory
syst
e
m
.
It
prom
pts
the
us
er
f
or
their
use
rn
am
e
and
pas
swor
d
a
nd
if
a
n
acc
ount
has
no
t
bee
n
c
reated
ye
t,
the
use
r
create
s
an
acc
ount a
nd
logs in
.
Figure
3
.
Logi
n pag
e
of t
he
i
nv
e
ntory
syst
e
m
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Develo
pm
e
nt
of
a
n i
nve
nto
ry
man
ag
e
me
nt s
yst
em usin
g as
so
ci
atio
n
r
ule
(
Tinu
ke
O.
Oladel
e
)
1873
The
Re
gistrati
on
Page
is
s
how
n
in
Fig
ur
e
4.
O
nce
the
l
og
i
n
pr
ocess
i
s
su
ccess
f
ul,
the
use
r
c
a
n
procee
d
to
ca
r
ry
out
any
ope
rati
on
re
qu
ire
d
of
t
hem
.
Also,
in
creati
ng
t
he
acco
un
t
the
per
s
onnel
wou
ld
be
prom
pted
to
se
le
ct
if
he/
s
he
i
s
a
us
er
or
a
n
adm
in.
The
use
r
has
li
m
i
te
d
featur
e
s.
The
only
thin
g
t
he
use
r
ca
n
do
is
m
ake
sal
es,
ge
ner
at
e
th
e
repor
t
,
a
nd
m
ake
orde
rs.
In
oth
e
r
w
ords,
t
he
us
er
is
li
ke
th
e
sal
esper
s
on.
Wh
il
e
the
adm
in
on
t
he
oth
er
ha
nd
serv
e
s
m
or
e
li
ke
the
m
anag
er
or
business
owne
r.
The
ad
m
in
can
do
ev
eryt
hing
the user
does,
bu
t
with a
ddit
ion
al
res
pons
i
bili
ty
.
The
a
dd
pro
duct
pa
ge
is
for
a
dd
i
ng
a
ne
w
product
t
o
t
he
sy
stem
as
show
n
in
Fig
ur
e
5
.
T
he
pro
du
c
t
to
be
ad
ded
does
n’
t
necessa
rily
hav
e
to
be
new
.
Also
,
t
he
data
m
ining
associat
ion
ru
l
e
com
es
o
n
the
add
pag
e
,
a
fter
ge
tt
ing
t
he
fr
e
quen
t
it
e
m
set
s
and
gen
e
rati
ng
the
strong
ass
ociat
ion
r
ules,
the
s
yst
e
m
al
erts
the
us
e
r
or
the
adm
in
pe
rson
nel
of
pr
oducts
t
hat
ar
e
freq
ue
ntly
bought
t
og
et
her
wh
e
n
a
par
ti
cu
la
r
pr
oduct
is
entere
d
(for
exam
ple,
wh
e
n
t
he
c
us
to
m
er
buys
br
ea
d,
a
nd
it
is
e
nt
ered
into
the
s
yst
e
m
,
the
syst
e
m
al
erts
the
use
r
that
the
cu
stom
er
m
igh
t
al
so
be
interest
ed
in
buyi
ng
m
il
k
and
s
o
on).
T
he
al
ert
of
f
re
qu
e
ntly
bought
it
em
s
is
sh
ow
n
in
Fi
gur
e
6.
Figure
4
.
Regis
trat
ion
pa
ge of
the in
ven
t
or
y s
yst
e
m
Figure
5
.
Ad
d pro
du
ct
pa
ge
(i
n
case
of a
ne
w product
)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
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4752
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on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
21
, N
o.
3
,
Ma
rc
h
2021
:
1868
-
1876
1874
Figure
7
disp
la
ys
al
l
the
or
de
r
that
as
ever
be
en
place
d.
T
he
adm
in
per
sonn
el
or
the
m
anag
e
r
co
ul
d
decide
to v
ie
w
the
re
port of
sa
le
s
or
the
re
por
t
of p
urcha
se. Th
e
i
nv
e
ntory
syst
e
m
can
ge
ne
rate
a
repo
rt, eit
he
r
daily
,
week
ly
,
m
on
thly
,
or
ev
en
ye
arly
.
All
the
adm
in
as
to
do
is
to
sel
ect
the
sta
rt
and
e
nd
date
of
the
repor
t
they
wou
l
d
li
ke
to gene
rate a
s sho
wn in Fi
gure
8
On
ce
the
date
r
ang
e
has
bee
n
sel
ect
ed,
the
syst
e
m
gen
erates
bo
th
the
sal
es
and
purc
hase
tr
ansacti
ons
that hav
e b
ee
n ca
rr
ie
d ou
t bet
ween
th
os
e d
at
es w
it
h
the start and
end d
at
e inclusi
ve
as sh
own
in
F
ig
ure 9. The
syst
e
m
le
ts
the
adm
in
sel
ect
t
he
dates,
inste
ad
of
m
anu
al
l
y
ty
pin
g
the
da
te
s
in.
Also
,
i
f
the
repo
rt
ha
s
been
gen
e
rated
, th
e
syst
e
m
al
lows
it
to
be p
rinted
if n
ee
de
d
as
show
n
i
n
Fi
gure
9.
Figure
6. Alert
of
product
fr
e
qu
e
ntly
pur
c
ha
sed
t
og
et
her
Figure
7. Vie
w
ord
e
r page
Figure
8. Ge
ne
rate re
port
page
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Develo
pm
e
nt
of
a
n i
nve
nto
ry
man
ag
e
me
nt s
yst
em usin
g as
so
ci
atio
n
r
ule
(
Tinu
ke
O.
Oladel
e
)
1875
Figure
9. Re
po
rt sho
wing tra
nsa
ct
ion
dates
of s
old
it
em
s
4.
CONCL
US
I
O
N
I
n
t
h
i
s
s
t
u
d
y
,
a
c
om
p
u
t
e
r
i
z
e
d
i
n
v
e
n
t
o
r
y
s
y
s
t
e
m
w
a
s
d
e
ve
l
o
p
e
d
a
n
d
w
a
s
a
l
s
o
i
m
p
r
o
ve
d
w
i
t
h
t
h
e
a
s
s
o
c
i
a
t
i
o
n
r
u
l
e
.
T
h
e
s
y
s
t
e
m
h
a
s
b
e
e
n
d
e
v
e
l
o
p
e
d
t
o
g
e
t
u
p
d
a
t
e
s
o
f
a
n
i
t
e
m
i
n
s
t
o
c
k
,
t
o
e
n
s
u
r
e
p
r
o
p
e
r
r
e
c
o
r
d
t
a
k
i
n
g
o
f
p
r
o
d
u
c
t
s
b
o
t
h
t
o
b
e
s
o
l
d
a
n
d
t
o
b
e
p
u
r
c
h
a
s
e
d
,
t
o
k
n
o
w
w
h
e
n
t
o
o
r
d
e
r
f
o
r
p
r
o
d
u
c
t
s
,
t
o
m
a
k
e
a
n
o
r
d
e
r
f
o
r
p
r
o
d
u
c
t
s
,
a
n
d
t
o
g
e
n
e
r
a
t
e
r
e
p
o
r
t
s
f
r
o
m
t
i
m
e
t
o
t
i
m
e
w
h
e
n
r
e
q
u
i
r
e
d
t
o
a
i
d
d
e
c
i
s
i
o
n
m
a
k
i
n
g
p
r
o
c
e
s
s
a
n
d
p
r
o
g
r
e
s
s
o
f
t
h
e
s
t
o
r
e
.
T
he
s
y
s
t
e
m
w
o
u
l
d
e
n
s
u
r
e
p
r
o
p
e
r
i
n
v
e
n
t
o
r
y
m
a
na
g
e
m
e
n
t
a
n
d
i
m
p
r
o
v
e
b
u
s
i
n
e
s
s
p
e
r
f
o
r
m
a
n
c
e
.
T
h
e
r
e
w
i
l
l
b
e
a
g
r
e
a
t
i
m
p
r
o
v
e
m
e
n
t
i
n
i
n
v
e
n
t
o
r
y
v
a
l
u
a
t
i
o
n
m
a
n
a
g
e
m
e
n
t
a
n
d
c
o
n
t
r
o
l
,
w
h
i
c
h
w
o
u
l
d
l
e
a
d
t
o
p
r
o
f
i
t
m
a
xi
m
i
z
a
t
i
o
n
.
T
h
i
s
w
o
r
k
c
a
n
s
t
i
l
l
b
e
i
m
p
r
o
v
e
d
b
y
u
s
i
n
g
m
o
r
e
a
s
s
o
c
i
a
t
i
o
n
r
u
l
e
t
e
c
h
n
i
q
u
e
s
a
n
d
a
l
g
o
r
i
t
hm
s
.
5.
RECOM
ME
NDATIO
N
It
is
ad
vised
or
reco
m
m
end
ed
that
this
pr
oj
e
ct
work
be
a
do
pted
or
im
plem
ented
in
st
ores,
inclu
ding
m
ini
m
arts
and
s
up
e
rm
ark
et
s.
T
he
c
om
pu
te
rized
syst
em
sh
oul
d
re
place
al
l
the
m
anu
al
syst
e
m
s
in
stores
f
or
stock
kee
ping
and
oth
e
r
pr
ocesses
to
m
ake
the
sto
res
m
or
e
eff
ect
ive
and
t
o
ai
d
a
nd
haste
n
m
a
nag
e
rial
decisi
ons a
nd
update
of r
ec
ords
.
REFERE
NCE
S
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oir,
N.
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uwens,
J.,
Joori
s,
B.
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R
oss
e
y
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J.
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Hoeb
eke
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&
De
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“
Uwb
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a
li
z
at
ion
wi
th
bat
t
er
y
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powered
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le
ss
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kb
one
for
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rone
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sed
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IS
S
N
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on
esi
a
n
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c Eng &
Co
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p
Sci,
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21
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Ma
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ark
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ane
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emi,
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“
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ct
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e
loc
at
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entor
y
m
odel
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e
-
l
a
y
er
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y
chain
net
work
desig
n
conside
ri
ng
ca
pacit
y
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la
n
ning,
”
Int
ernati
o
nal
Journal
of
L
ogisti
cs
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ms
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ment
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ee
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An
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ntor
y
m
od
el
for
det
er
iora
t
i
ng
it
ems
with
ra
m
p
ty
p
e
demand
under
fuz
z
y
env
ironment,
”
Int
ernati
onal
Journal
of
Logis
ti
cs
Syste
ms
and
Mana
geme
nt
,
vol
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22
,
no.
4
,
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436
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463
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[10]
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sa
y
ed
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K.
“
Expl
oring
the
re
la
t
ionship
bet
wee
n
eff
ic
i
ency
of
in
vent
or
y
m
ana
ge
m
ent
and
firm
per
form
anc
e
:
a
n
empiric
a
l
r
ese
ar
ch,
”
Int
ernati
on
al
Journal
of
Ser
vi
c
es
and
Opera
ti
ons Manage
me
nt
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vo
l.
21
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no.
1
,
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ynch
L
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go
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”
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x
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ing
Aggre
ss
ive
ness
and
Its
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on
to
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ive
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an
ci
a
l
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ing
,
”
T
he
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oun
ti
n
g
Review:
Marc
h
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vol.
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n
o.
2,
pp.
467
-
496
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2
009
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htt
ps://
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i.
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2308/acc
r
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84.
2
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467
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ber
M.,
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ini
n
g:
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ep
ts
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te
chni
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es.
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Avail
ab
le
:h
tt
p:
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chol
ar.
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le.d
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schol
ar.
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q=
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kY
dwviD3IR4J
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ar.
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ogle
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p
ut=
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y
i,
M.O.
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y
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y
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ant
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d
cl
uster
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appr
oac
h
for
sim
ilar
re
sea
r
c
h
ar
e
a
detec
t
ion,”
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KOMNIKA
(
Tele
communic
ati
on
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ng
El
e
ct
ronics
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”
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s
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CA:
Morga
n
Kaufm
ann
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2006
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“
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ng
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nce
pts,
m
odel
s,
m
et
hods,
and
al
g
orit
hm
s,”
Maid
e
n
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il
e
y
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t
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ie
n
ce
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l
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O.
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O.,
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y
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A.
A.,
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A
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A.,
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y
i
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M.
O.
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at
ion
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g
Algorit
hm
s
for
Feat
ure
Sel
ectio
n
and
Pre
dic
t
io
n
of
Diabe
tic
R
et
inop
at
h
y
,
”
Lect
ure
Not
es
in
Com
pute
r
Scie
n
ce
(inc
ludi
ng
subs
e
rie
s
Le
c
ture
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es
in
Artifi
ci
a
l
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lligen
ce
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c
ture
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nform
at
ics
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716
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20
19.
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ai
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ng
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hm
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hm
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Us
ed
in
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ng.
R
et
ri
eve
d
on
14th
Augus
t
from
htt
ps://
d
at
a
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fla
ir
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tr
ai
ning
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ta
-
m
ini
ng
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al
gori
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[18]
Olade
l
e
T
.
O.
,
Aro
T.
O.
,
Ade
gun
A.
A.
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R.
O.
,
“
Predic
t
ion
of
Student
’s
Aca
d
e
m
ic
Perform
ance
using
k
-
Mea
ns
Cluste
ring
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Multi
ple
L
ine
ar
Regre
ss
ion
s,”
Jo
urnal
of
Engi
neer
ing
and
Appl
ie
d
Sci
ences
,
vol.
14
,
no.
22
,
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