Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
24
,
No.
1
,
Octo
be
r
2021
,
pp.
530
~
537
IS
S
N: 25
02
-
4752, DO
I: 10
.11
591/ijeecs
.v
24
.i
1
.
pp
53
0
-
53
7
530
Journ
al
h
om
e
page
:
http:
//
ij
eecs.i
aesc
or
e.c
om
AQUAC
ISION:
a multip
aram
eter aquacu
lture w
ater qu
ali
ty
tester
and decisi
on
supp
ort syst
em
Ma
r
k
An
t
hon
y A.
L
az
o,
L
oui
se M
ark Ki
t
S.
Gero
nimo
, L
ester
John
T
. Comil
ang
,
Kenne
th
John
B.
C
ayme,
Ja
y M. Ven
tu
r
a, Er
tie C
. Ab
ana
Com
pute
r
Engi
n
ee
ring
Depa
r
t
m
ent
,
Univ
ersity
of
Saint L
ouis
,
Tu
guega
ra
,
Phi
li
pp
ine
s
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Feb
15
,
2021
Re
vised
A
ug
17
,
2021
Accepte
d
Aug
23
,
2021
The
p
ape
r
pre
se
nts
a
m
ultipar
a
m
et
er
aqu
ac
u
lt
u
re
wat
er
qu
al
i
t
y
te
ster
with
a
dec
ision
support
sy
st
em.
A
devi
c
e
was
deve
lope
d
to
ai
d
aquacul
tu
re
far
m
ers
in
m
onit
oring
wate
r
qua
li
t
y
par
a
m
et
ers
and
m
ai
nta
ini
ng
or
ac
h
ie
v
ing
opti
m
al
le
ve
ls
b
y
sugg
esti
ng
wa
y
s
o
n
how
a
far
m
er
ca
n
respo
nd
to
such
m
ea
surem
ent
s.
The
AQ
UA
CISIO
N
devi
ce
m
e
asure
s
six
diff
e
ren
t
wa
te
r
qual
ity
par
amet
ers;
t
empera
tur
e
,
pra
ct
i
cal
sal
init
y
,
pH
le
ve
l,
t
o
t
a
l
d
i
s
s
o
l
v
e
d
s
o
l
i
d
(
TD
S
)
,
o
xida
ti
on
-
red
uc
tion
pote
nti
a
l
(
ORP
)
,
and
al
gae
dens
i
t
y
.
Mea
surem
en
ts
were
sent
to
the
AQ
UA
CI
SIO
N
appl
i
ca
t
ion
whe
re
they
w
er
e
proc
essed
to
de
te
rm
ine
the
cou
rse
of
a
ct
ion
th
at
was
b
est
to
m
ai
nta
in
or
ac
hi
eve
op
ti
m
al
le
ve
ls using
fuz
z
y
ru
le
s.
Based
o
n
the
compara
t
iv
e
result, the
AQ
UA
CI
SIO
N
was
ac
cur
ate
in
m
ea
suring
te
m
per
at
ur
e,
pra
ct
i
cal
sali
nity
,
pH
le
ve
l,
TDS,
and
ORP
during
the
ac
tu
al
t
esti
ng.
T
he
appl
i
cation
a
l
so
rec
ei
v
ed
an
ex
celle
n
t
r
at
i
ng
on
th
e
ISO
/IEC 25010
softwar
e
qua
li
t
y
m
od
el
standa
rd.
Ke
yw
or
ds:
Algae
de
ns
it
y
Aquac
ultur
e
Pr
act
ic
al
sali
nity
Tem
per
at
ur
e
This
is an
open
acc
ess arti
cl
e
un
der
the
CC
B
Y
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
Jay
M. V
e
ntur
a
Com
pu
te
r
E
ng
i
neer
i
ng D
e
par
t
m
ent
Un
i
ver
sit
y o
f S
ai
nt Louis
Tu
gu
e
gar
a
o, C
agayan,
P
hili
ppines
Em
a
il
: l
hen
j
ay
ven
t
ur
a
@g
m
ai
l.com
1.
INTROD
U
CTION
Re
al
-
tim
e
m
on
it
or
in
g
of
wate
r
qual
it
y
par
a
m
et
ers
in
aq
ua
culture
is
ve
ry
i
m
po
rta
nt
to
avo
i
d
water
po
ll
utio
n.
Para
m
et
ers
su
ch
as
tem
per
at
ur
e,
pH
le
vel,
diss
olv
e
ox
y
gen,
s
a
li
nity
,
el
ect
ri
cal
condu
ct
ivit
y
an
d
al
gae
de
ns
it
y
pro
vid
es
aq
ua
culture
su
it
a
ble
en
vir
onm
e
nt
to
gro
w
[1
]
-
[
4]
.
P
oor
m
anag
em
ent
of
t
hese
par
am
et
ers
le
ads
t
o
water
poll
ution
.
M
or
e
over
,
a
qu
ac
ultu
r
e
poll
utio
n
is
cause
d
by
exc
ess
use
of
fer
ti
li
zers,
un
eat
e
n
feed
pe
ll
et
s
and
a
ppli
cat
ion
of
oth
e
r
c
hem
ic
a
ls.
Both
t
he
fer
ti
li
zer
a
nd
fee
d
pelle
ts
con
ta
in
nu
trie
nt
s
wh
ic
h
if not
co
ntr
olled
m
ay
c
ause p
olluti
on.
Chem
ic
al
s
l
ike
lim
e
al
te
rs
water
qual
it
y;
it
increases both
the
pH
le
vel
and
wate
r
ha
rdness
,
exc
essive
use
of
s
uch
c
hem
ic
al
m
ay
resu
lt
to
f
ish
kill
s
as
fis
he
s
li
ve
in
certa
in
pH
le
vel
[
5]
-
[
7]
.
T
o
a
v
o
i
d
w
a
t
e
r
p
o
l
l
u
t
i
o
n
,
t
h
e
r
e
i
s
a
n
e
e
d
f
o
r
b
e
t
t
e
r
d
e
c
i
s
i
on
s
a
n
d
a
q
u
a
c
u
l
t
u
r
e
m
a
n
a
g
e
m
e
n
t
a
c
t
i
o
n
s
.
D
e
c
i
s
i
o
n
s
t
o
b
e
a
dm
i
n
i
s
t
e
r
e
d
m
u
s
t
b
e
e
s
t
a
b
l
i
s
h
e
d
f
r
o
m
t
h
e
c
u
r
r
e
n
t
a
q
u
a
c
u
l
t
u
r
e
w
a
t
e
r
q
u
a
l
i
t
y
p
a
r
a
m
e
t
e
r
s
[8
]
,
[
9]
.
Ov
e
r
the
past
ye
ars,
there
ha
s
been
a
suffic
ie
nt
nu
m
ber
of
researc
hes
m
a
de
to
t
est
the
c
urren
t
wate
r
qual
it
y
and
t
he
relat
io
ns
hi
p
of
water
po
ll
utio
n
wit
h
poor
aq
uac
ul
ture
decisi
ons
and
act
io
ns
[
10
]
-
[
12
]
.
A
re
search
cond
ucted
f
or
m
on
it
or
in
g
w
at
er
qual
it
y
usi
ng
wireless
ne
tworks
s
ugge
ste
d
that
c
onve
ntion
al
m
on
it
or
i
ng
p
r
o
c
e
s
s
o
f
m
a
n
u
a
l
c
ol
l
e
c
t
i
o
n
of
s
a
m
pl
e
s
a
n
d
l
a
b
o
r
a
t
o
r
y
t
e
s
t
i
ng
a
n
d
a
n
a
l
y
s
i
s
a
r
e
t
i
m
e
-
c
o
n
s
u
m
i
n
g
a
n
d
i
n
e
f
f
e
c
t
i
v
e
.
I
n
t
u
r
n
,
i
t
w
a
s
p
r
o
p
o
s
e
d
t
h
a
t
w
i
r
e
l
e
s
s
s
e
n
s
o
r
s
a
r
e
m
o
r
e
e
f
f
i
c
i
e
nt
i
n
m
o
ni
t
or
i
n
g
w
a
t
e
r
q
u
a
l
i
t
y
[13
]
,
[
14]
.
Anothe
r
researc
h
intr
oduce
d
a
sm
art
phone
-
base
d
e
m
bed
ded
syst
e
m
design
e
d
to
m
easur
e
dif
fer
e
nt
water
qual
it
y
par
am
et
ers
in
var
i
ou
s
rem
ote
locat
ion
s
[
15
]
-
[
17
]
Re
se
arch
on
m
ulti
-
pa
ram
et
er
in
t
egr
at
e
d
water
qu
al
it
y
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
AQUAC
I
SION
: a mult
ip
ar
am
et
er aquac
ultu
re
wa
te
r
qualit
y test
er and de
ci
sion
…
(
Ma
rk
An
t
hony
A
. La
zo
)
531
sens
or
s
offer
a
low
-
c
os
t
syst
e
m
fo
r
water
m
on
it
or
ing
[18
]
,
[
19]
.
So
m
e
of
the
stud
ie
s
condu
ct
e
d
on
water
qu
al
it
y
m
on
it
or
in
g
us
ed
wi
re
le
ss
sens
or
network
to
m
on
it
or
an
d
c
ontr
ol
m
ul
ti
ple
sen
s
ors
that
are
c
on
nected
via
Zig
b
ee
[
20]
-
[22
]
u
sin
g
m
ulti
ple
sen
sors
needs
diff
e
re
nt
qual
it
y
of
ser
vi
ces
since
it
ca
te
rs
to
m
ulti
ple
da
t
a
pr
i
or
it
ie
s
[
23
]
-
[25]
.
T
h
e
r
e
s
e
a
r
c
h
a
i
m
s
t
o
b
u
i
l
d
a
de
v
i
c
e
t
h
a
t
m
e
a
s
u
r
e
d
i
f
f
e
r
e
n
t
w
a
t
e
r
q
u
a
l
i
t
y
p
a
r
a
m
e
t
e
r
s
f
o
r
a
q
u
a
c
u
l
t
u
r
e
a
n
d
p
r
o
v
i
d
e
d
e
c
i
s
i
on
s
u
p
p
o
r
t
s
y
s
t
e
m
.
T
h
e
p
a
p
e
r
f
o
c
u
s
e
s
o
n
t
h
e
p
H
l
e
v
e
l
,
e
l
e
c
t
r
i
c
a
l
c
o
n
d
u
c
t
i
v
i
t
y
,
t
e
m
pe
r
a
t
u
r
e
,
a
l
g
a
e
d
e
n
s
i
t
y
,
t
u
r
b
i
d
i
t
y
o
f
t
h
e
w
a
t
e
r
,
t
o
t
a
l
di
s
s
o
l
v
e
d
s
o
l
i
d
(
T
D
S
)
,
a
n
d
o
x
i
d
a
t
i
o
n
-
r
e
d
u
c
t
i
o
n
p
o
t
e
n
t
i
a
l
(
O
R
P
)
p
a
r
a
m
e
t
e
r
s
o
f
w
a
t
e
r
.
T
h
e
p
a
p
e
r
a
l
s
o
c
om
e
s
w
i
t
h
a
n
a
p
p
l
i
c
a
t
i
o
n
f
o
r
t
h
e
d
e
c
i
s
i
o
n
s
u
p
p
o
r
t
s
y
s
t
e
m
.
T
he
a
p
p
l
i
c
a
t
i
o
n
s
u
g
g
e
s
t
s
a
c
t
i
o
n
c
o
n
s
t
r
u
c
t
e
d
f
r
om
f
u
z
z
y
l
o
g
i
c
a
c
c
o
r
d
i
n
g
t
o
t
h
e
r
e
s
ul
t
s
of
t
h
e
m
e
a
s
u
r
e
d
w
a
t
e
r
q
u
a
l
i
t
y
s
e
n
s
o
r
s
.
2.
RESEA
R
CH MET
HO
D
2.1
.
Bl
oc
k
di
ag
r
am
of
th
e
AQUCI
SIO
N
The
de
vice
is
con
sist
in
g
of
a
m
ic
ro
con
tr
oller,
pH
se
nsor
,
TDS
se
nsor
,
ORP
se
nsor
,
el
ect
rical
cond
uctivit
y
sens
or
,
te
m
per
at
ur
e
se
nsor
,
L
EDs,
ph
otodio
de
tra
ns
im
pedance
ci
rc
uit,
bl
uetoo
t
h
m
odul
e,
2
-
channel
relay
m
od
ules
an
d
t
oggle
s
witc
hes
as
s
how
n
in
Figure
1
.
The
m
ic
ro
co
ntro
ll
e
r
is
the
brai
n
of
t
he
dev
ic
e.
It
c
on
t
ro
ls
al
l
the
processes
a
nd
ac
ti
viti
es
the
devi
ce
will
per
f
or
m
.
The
toggle
switc
hes
with
li
gh
t
-
e
m
itti
ng
diode
s
(
LED
)
in
dica
tors
sta
rts
the
dev
ic
e
wh
e
n
s
et
to
on
an
d
st
op
s
t
he
de
vice
wh
e
n
tu
rn
e
d
off.
T
he
decisi
on
suppo
rt
syst
e
m
will
gen
e
rate
sugg
e
sti
on
s
acco
rd
i
ng
to
the
read
re
su
lt
s
from
the
pH
se
nsor,
el
e
ct
rical
cond
uctivit
y
sens
or
,
te
m
per
at
ur
e
se
ns
or,
T
DS
se
ns
or,
O
RP
sens
or
a
nd
in
sit
u
fluor
om
et
er.
The
six
sensors
will
m
easur
e si
x diff
e
re
nt w
at
er
qu
a
li
ty
p
a
ra
m
et
ers
necessa
ry in a
quacult
ures.
The
blu
e
LE
D
and
phot
od
i
ode
transim
pedance
am
plifie
r
com
pr
ise
the
in
sit
u
fluorom
et
er
us
ed
to
m
on
it
or
the
alg
ae
bio
m
ass
den
sit
y.
The
blue
too
th
m
od
ule
is
us
ed
to
creat
e
a
con
necti
on
with
the
dev
ic
e
and
the
ap
plica
ti
on
for
sen
ding
of
m
easur
ed
par
a
m
et
ers
fo
r
deci
sion
gen
e
rati
on.
T
he
2
-
c
hann
el
relay
m
od
ules
are
us
e
d
to
switc
h
betwee
n
de
vices
in
qu
e
ue
of
m
easur
in
g.
T
he
app
li
cat
ion
will
gen
erate
s
uggestio
ns
on
act
ion
s
an
aq
uac
ultur
e
far
m
er
sh
oul
d
ta
ke
t
o
im
p
rove
product
io
n,
util
iz
e
resour
ces
,
or
m
iti
gate
water
poll
utio
n.
Decisi
ons
gen
e
rated
will
b
e
di
sp
la
ye
d
t
og
et
he
r wit
h
the
sensor m
easur
em
e
nts in
the a
ppli
cat
ion
.
Figure
1. Bl
oc
k diag
ram
o
f
th
e AQU
ACI
SION
2.2
.
AQUA
C
ISIO
N
ap
pli
c
at
i
on
The
A
Q
UA
C
I
SI
O
N
a
pp
li
cat
ion
s
how
n
in
Figure
2
is
cr
eat
ed
us
in
g
A
ndr
oid
stu
dio
.
It
su
pport
s
Gr
a
ddle
-
ba
sed
bu
il
ds
an
d
pro
vid
es
a
n
a
ndr
oid
virtu
al
dev
ic
e
to
te
st
and
de
bug
t
he
ap
plica
ti
ons.
The
AQU
ACISIO
N
a
pp
li
cat
io
n
con
ta
in
s
te
xt
vi
ews
to
dis
pla
y
the
m
easur
e
m
ents
sent
fro
m
the
AQUAC
IS
I
O
N
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
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E
le
c Eng &
Co
m
p
Sci,
Vo
l.
24
, N
o.
1
,
Oct
ober
20
21
:
53
0
-
53
7
532
dev
ic
e,
t
o
act
as
la
bels
of
ea
ch
m
easur
em
e
nts
an
d
fiel
ds,
and
t
o
dis
play
the
ge
ner
at
e
d
su
ggest
io
ns
ba
sed
on
fu
zzy
lo
gic.
It
co
ntains
S
pinners
t
hat
creat
es
dro
pdown
m
enu
s
for
the
us
er
,
li
st
vie
w
that
al
lo
ws
a
li
st
of
op
ti
ons
to
be
di
sp
la
ye
d
a
nd
sr
oll
view
s,
c
ons
trai
nt
la
youts
,
and
li
near
la
yo
uts
f
or
a
fixe
d
and
ar
range
d
di
sp
la
y
of
ob
j
ect
s.
Th
e
fu
zzy
log
ic
set
s
are
incorporate
d
in
the
app
li
cat
ion
a
s
well
as
the
creati
on
of
bl
ueto
ot
h
adap
te
rs
a
nd th
read
i
ng pro
ce
s
ses for
the a
ppli
c
at
ion
a
nd the
dev
ic
e t
o
c
omm
un
ic
at
e.
Figure
2. A
QUACIS
ION
a
ppli
cat
ion
2.3.
Ap
pli
ca
t
ion e
va
lu
ati
on resp
on
den
ts
The
AQU
ACI
SI
O
N
a
ppli
cat
ion
is
eval
uate
d
by
20
respo
nd
e
nts
us
in
g
t
he
I
SO
/
IEC
25010
s
oft
war
e
qu
al
it
y
m
od
el
sta
nd
a
rd
t
hro
ugh
a
1
-
5
rati
ng
scal
e.
The
20
respo
nd
e
nts
a
re
com
po
se
d
of
5
res
pondent
s
w
ho
are
ne
w
to
aq
uacu
lt
ure
,
5
a
qu
ac
ultu
re
farm
ers,
an
d
10
respo
nd
e
nts
w
ho
ha
ve
stu
died
pro
fessi
on
a
l
fiel
ds
relat
ed
to
aq
ua
culture
.
T
he
va
riet
y
of
res
pond
e
nts
is
t
o
te
st
the
ove
rall
qu
al
it
y
of
the
app
li
cat
io
n
us
ing
the
su
b
-
c
har
act
eris
ti
cs p
rese
nted
in
the
stan
dard
us
e
d.
2.4.
Te
s
ting
an
d
evalu
at
i
on
A.
Percent
accur
acy
(P
A)
:
The
accur
acy
m
ea
su
res
the
de
gree
of
ho
w
cl
ose
are
cal
c
ulate
d
or
m
easur
e
d
values
t
o
their
act
ual
valu
es.
The
per
ce
nt
error
is
giv
e
n
as
the
r
at
io
of
e
rro
r
to
act
ual
val
ue
the
n
m
ul
ti
plied
by
100.
The
pe
rce
nt
erro
r
is
subt
racted
to
100
to
get
t
he
pe
rce
nt
a
ccu
racy.
T
he
f
or
m
ula
for
per
ce
nt acc
ur
a
cy
is g
ive
n
,
=
100
−
(
ℎ
−
ℎ
∗
100
)
(1)
B.
Avera
ge:
Av
e
r
age
is
the
num
ber
that
e
xpres
ses
the
central
value
in
set
s
of
data
w
hich
is
achieved
by
div
idi
ng
t
he
sum
of
al
l
the
values
in
a
set
by
the
total
nu
m
ber
of
values
in
the
set
.
The
re
searche
rs
use
d
this co
nce
pt to ca
lc
ulate
the a
ver
a
ge of
the
a
pp
li
cat
io
n
s
urv
ey
r
esults.
Th
e
form
ula is
,
=
∑
(2)
C.
Standar
d
devi
ation
:
The
sta
nd
a
r
d
de
viati
on
m
easur
es
the
a
m
ou
nt
of
di
sp
ersi
on
or
va
riat
ion
of
set
s
of
values
.
Sta
nd
a
rd
de
viati
on
s
t
hat
are
lo
w
in
dicat
es
that
va
lues
te
nd
t
o
be
nea
r
to
the
m
ean
of
the
s
et
,
wh
il
e sta
nd
a
rd
dev
ia
ti
o
ns
t
hat
are
high in
dica
te
s that v
al
ues a
re sprea
d o
ut
ov
e
r wide
r ran
ge.
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
AQUAC
I
SION
: a mult
ip
ar
am
et
er aquac
ultu
re
wa
te
r
qualit
y test
er and de
ci
sion
…
(
Ma
rk
An
t
hony
A
. La
zo
)
533
=
√
∑
(
−
=
1
̅
)
2
−
1
(3)
3.
RESU
LT
S
A
ND
D
IS
C
USS
ION
3.1.
Act
u
al
d
evice
T
h
e
w
h
o
l
e
d
e
v
i
c
e
h
a
s
a
m
e
a
s
u
r
i
n
g
p
a
r
t
w
h
i
c
h
c
a
n
b
e
s
u
b
m
e
r
g
e
d
i
n
t
o
t
h
e
a
q
u
a
c
u
l
t
u
r
e
a
nd
a
h
a
n
d
h
e
l
d
s
w
i
t
c
h
p
a
r
t
to
t
u
r
n
o
n
a
n
d
o
f
f
t
h
e
w
h
o
l
e
d
e
v
i
c
e
.
T
h
e
s
u
bm
e
r
s
i
b
l
e
p
a
r
t
o
f
t
h
e
d
e
v
i
c
e
w
a
s
m
a
d
e
o
f
w
o
o
d
s
a
n
d
p
l
a
s
t
i
c
s
.
T
h
i
s
i
s
m
a
d
e
w
a
t
e
r
p
r
o
o
f
t
o
s
a
f
e
g
u
a
r
d
t
h
e
e
l
e
c
t
r
i
c
a
l
c
om
p
o
n
e
n
t
s
e
n
c
l
o
s
e
d
i
n
s
i
d
e
a
s
s
h
o
w
n
i
n
F
i
g
u
r
e
3
.
Figure
1
.
A
ct
ua
l AQU
ACISI
ON
d
e
vice
3.2.
Perce
nt
accur
acy of
differen
t
se
ns
or
s
The
com
pu
ta
ti
on
of
p
erce
nt
accuracy
of
the A
Q
U
ACISIO
N
over
the
c
om
m
ercial
dev
i
ce
in
te
rm
s
the
diff
e
re
nt w
at
e
r
quali
ty
p
aram
et
ers
are
sho
w
n
in
Ta
bles 1 t
o 5.
A.
Tem
pera
t
ur
e
:
The
per
ce
nt
a
ccur
acy
of
the
A
QUACIS
I
O
N
ov
e
r
the
co
m
m
ercial
dev
ic
e
in
te
rm
s
of
tem
per
at
ur
e
is
sh
ow
n
i
n
Tabl
e
1.
It
can
be
s
een
from
the
t
able
that
the
dev
ic
e
is
accura
te
in
m
easur
ing
the tem
per
at
ure o
f
the
d
if
fere
nt po
nds
hav
i
ng a
n
a
ver
a
ge of
99.687%
.
Table
1.
T
em
per
at
ur
e
te
st res
ults
Po
n
d
Nu
m
b
er
Co
m
m
e
rcial
Dev
ic
es (°
C)
AQUACI
SIO
N (
°
C)
Percent A
ccurac
y
(
%)
1
28
2
8
.21
9
9
.25
0
2
27
2
7
.07
9
9
.74
1
3
28
2
8
.05
9
9
.82
1
4
27
2
7
.03
9
9
.88
9
5
30
3
0
.08
9
9
.73
3
Av
erage:
9
9
.68
7
B.
Ele
ct
ric
al
co
nductiv
it
y
:
T
he
el
ect
rical
condu
ct
ivit
y
m
eas
ur
es
the
sal
ini
ty
of
the
wate
r.
T
he
per
c
ent
accuracy
of
th
e
dev
ic
e
is
show
n
Ta
ble
2.
It
can
be
seen
fr
om
the
ta
ble
that
the
dev
i
ce
is
accurate
in
m
easur
in
g
th
e
el
ect
rical
co
nd
uctivit
y of t
he diffe
re
nt po
nd
s
h
a
ving a
n
a
verage
of 99.
495%
Table
2.
Elec
tr
ic
al
conduct
ivit
y t
est
r
esults
Po
n
d
Nu
m
b
er
Co
m
m
e
rcial
Dev
ic
es (pp
t)
AQUACI
SIO
N
(p
p
t)
Percent A
ccurac
y
(
%)
1
9
.65
9
.59
9
9
.37
8
2
8
.87
8
.92
9
9
.43
6
3
8
.91
8
.94
9
9
.66
3
4
8
.71
8
.76
9
9
.42
6
5
9
.32
9
.36
9
9
.57
1
Av
erage:
9
9
.49
5
C.
pH
le
vel
:
T
he
per
ce
nt
accu
r
acy
of
the
de
vice
in
m
easur
in
g
the
pH
le
vel
of
the
wat
er
is
show
n
i
n
Table
3.
It
ca
n
be
see
n
f
ro
m
the
ta
ble
the
de
vice
is
al
so
acc
ur
at
e
in
m
easu
rin
g
the
pH
le
ve
l
of
the
water
hav
i
ng an ave
r
age
of 99.
298%
.
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.
24
, N
o.
1
,
Oct
ober
20
21
:
53
0
-
53
7
534
Table
3.
pH
te
s
t resu
lt
s
Po
n
d
Nu
m
b
er
Co
m
m
e
rcial
Dev
ic
es
AQUACI
SIO
N
Percent A
ccurac
y
(
%)
1
7
.01
7
.07
9
9
.14
4
2
8
.01
8
.09
9
9
.00
1
3
8
.57
8
.61
9
9
.53
3
4
7
.97
8
.03
9
9
.24
7
5
9
.27
9
.31
9
9
.56
7
Av
erage:
9
9
.29
8
D.
To
tal
diss
olved
so
li
ds
:
T
he
pe
rcen
t
accu
racy
of
the
de
vice
over
the
com
m
e
rcial
dev
ic
e
in
te
rm
s
of
TD
S
is
sh
own
in
Ta
ble
4.
It
can
be
seen
from
th
e
ta
ble
the
devi
ce
is
accurate
in
m
easur
in
g
the
TDS
of
th
e
diff
e
re
nt po
nd
s
h
a
ving a
n
a
verage
of 99.
720%
.
Table
4.
T
otal
disso
l
ved s
olid
s test
r
es
ults
Po
n
d
Nu
m
b
er
Co
m
m
e
rcial
Dev
ic
es (pp
m
)
AQUACI
SIO
N (
p
p
m
)
Percent A
ccurac
y
(
%)
1
8452
8
4
3
1
.1
8
9
9
.75
3
2
9157
9
1
7
5
.3
3
9
9
.78
0
3
8651
8
6
7
7
.5
1
9
9
.69
4
4
9323
9
3
5
1
.5
8
9
9
.69
3
5
7856
7
8
8
1
.2
2
9
9
.67
9
Av
erage:
9
9
.72
0
E.
Oxid
ation
-
re
duct
ion
-
po
te
ntia
l
:
It
ca
n
al
s
o
be
seen
f
ro
m
Table
5
that
t
he
de
vice
is
acc
ur
a
te
in
m
easur
in
g
the O
R
P
of
t
he
d
if
fer
e
nt
pond
s h
a
ving a
n
a
ve
rag
e
of
95.58
7%
.
It
can
be
see
n
f
ro
m
Tables
1
to
5
the
com
par
ison
of
t
he
com
m
ercial
water
qual
it
y
te
ste
r
m
easur
em
ents
ov
er
the
AQUA
C
IS
I
O
N
de
vice
m
easur
e
m
ents
in
five
diff
e
ren
t
po
nds.
T
he
com
pu
ta
ti
on
rev
eal
s
that
t
he
A
QUACI
SION
is
acc
ur
at
e
in
m
easur
in
g
t
he
diff
e
re
nt
water
q
ualit
y
pa
ram
et
ers.
S
i
m
i
la
rly
,
Table
6
s
hows
the algae
d
e
ns
i
ty
o
f
t
he diffe
r
ent po
nds.
Table
5.
O
xid
a
ti
on
-
reducti
on
-
po
te
ntial
test
re
su
lt
s
Po
n
d
Nu
m
b
er
Co
m
m
e
rcial
Dev
ic
es (
m
V)
AQUACI
SIO
N (
m
V)
Percent A
ccurac
y
(
%)
1
1
0
0
.57
1
0
4
.73
9
5
.86
4
2
8
7
.03
9
1
.39
9
4
.99
0
3
8
1
.23
8
4
.96
9
5
.40
8
4
7
1
.59
7
4
.01
9
6
.62
0
5
9
1
.54
9
6
.07
9
5
.05
1
Av
erage:
9
5
.58
7
Table
6.
Algae
d
e
ns
it
y t
est
r
e
su
lt
s
Po
n
d
Nu
m
b
er
AQUACI
SIO
N (
p
p
b
)
1
3
.51
2
2
.89
3
2
.35
4
2
.07
5
1
.54
3.3.
S
oftware
eva
lu
ati
on
usi
ng
I
SO/IE
C
2501
0
The
e
valuati
on
of
the
s
oft
wa
r
e
com
po
ne
nt
of
the
A
QUICI
SI
O
N
is
sho
w
n
on
Table
7.
I
t
can
be
see
n
from
the
Table
7
that
the
dev
el
op
e
d
s
of
t
war
e
f
or
A
Q
UCISIO
N
is
excell
ent
in
te
rm
s
of
the
diff
ere
nt
char
act
e
risti
cs p
rese
nted
b
y
I
SO
/IEC
25
010.
Table
7.
ISO/I
EC 2
5010
e
valuati
on r
es
ults
Ch
arac
teristic
Av
erage
Fu
n
ctio
n
al Stability
4
.63
3
Perf
o
r
m
an
ce
Ef
f
icien
cy
4
.66
7
Co
m
p
atib
ilit
y
4
.52
5
Usab
ility
4
.75
0
Reliab
ility
4
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Ind
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J
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4752
AQUAC
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SION
: a mult
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)
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d
m
a
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h
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l
e
a
r
n
g
i
n
(
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L
)
t
o
f
o
r
e
c
a
s
t
t
h
e
w
a
t
e
r
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u
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y
p
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r
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e
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e
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o
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u
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d
b
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t
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d
e
v
i
c
e
.
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8605146.
BIOGR
AP
HI
ES OF
A
UTH
ORS
Mar
k
An
thon
y
A.
Laz
o
rec
ent
l
y
h
is
ba
che
lor’s
degr
ee
in
Com
p
ute
r
Engi
ne
eri
ng
at
Univ
ersi
t
y
of
Saint
Loui
s,
Tugue
gar
ao
Ci
t
y
.
His
ar
ea
s
of
int
er
est
in
cl
ude
C
la
nguag
e
pro
gra
m
m
ing,
web
deve
lopment
,
software
dev
el
op
m
ent
,
sensor
te
c
hnologi
es,
and
e
m
bedde
d
s
y
stems
.
He
at
te
nd
ed
var
io
us
works
hops
on
roboti
cs,
m
ic
roc
ontrollers
,
and
embedde
d
s
y
stems
.
He
a
lso
compete
d
in
a
reg
ional
progr
a
m
m
ing
competi
t
ion.
Lou
ise
Mar
k
Ki
t
S.
Ge
roni
mo
rec
entl
y
his
bac
hel
or’s
deg
ree
in
Com
pute
r
Engi
nee
r
ing
at
Univer
sit
y
of
Saint
Lou
is,
T
uguega
rao
Cit
y
.
His
are
as
of
int
er
est
in
cl
ud
e
C
l
angua
g
e
progra
m
m
ing,
web
developm
ent
,
and
software
d
e
vel
opm
ent
.
H
e
a
tt
end
ed
var
ious
works
hops
on
roboti
cs,
m
ic
roc
ontrol
l
e
rs, and e
m
bedde
d
s
y
st
ems
.
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
AQUAC
I
SION
: a mult
ip
ar
am
et
er aquac
ultu
re
wa
te
r
qualit
y test
er and de
ci
sion
…
(
Ma
rk
An
t
hony
A
. La
zo
)
537
Leste
r
John
T.
Comilang
rec
en
tly
h
is
bac
he
lor’
s
degr
ee
in
Com
pute
r
Engi
n
ee
rin
g
at
Univer
sit
y
of
Saint
Loui
s,
Tugue
gar
ao
Ci
t
y
.
His
ar
ea
s
of
int
er
est
in
cl
ude
C
la
nguag
e
pro
gra
m
m
ing,
web
deve
lopment
,
a
nd
software
d
eve
lopment
.
H
e
attend
ed
var
ious
works
hops
on
robotics,
m
ic
roc
ontrollers
,
and
embedd
ed s
y
stems
.
Ke
nn
eth
John
B.
Cay
m
e
recen
tly
his
bac
h
el
or’
s
degr
ee
in
Com
pute
r
Engi
n
ee
r
in
g
at
Univer
si
t
y
of
Saint
Loui
s,
Tugue
gar
ao
Ci
t
y
.
His
ar
ea
s
of
int
er
est
in
cl
ude
C
la
nguag
e
pro
g
ramm
ing,
web
deve
lopment
,
a
nd
software
d
eve
lopment
.
H
e
attend
ed
var
ious
works
hops
on
robotics,
m
ic
roc
ontrollers
,
and
embedd
ed s
y
stems
.
Jay
M.
Ventu
r
a
obtained
h
is
Bac
he
lor
of
Sci
enc
e
degr
ee
in
Com
pute
r
Eng
ine
er
ing
from
Univer
sit
y
of
Sa
int
Lo
uis
Tugu
e
gar
ao,
Phili
pp
in
es
in
2009
.
He
f
ini
shed
h
is
m
aste
r’s
degr
ee
in
Inform
at
ion
T
echnolog
y
in
2014
from
the
Univ
er
sit
y
of
Sain
t
Lou
is
Tugue
ga
rao
.
He
is
cur
r
entl
y
ta
king
up
Doct
or
of
Eng
ine
e
ri
ng
with
spe
ci
a
l
iz
a
ti
on
in
Com
pute
r
Engi
ne
ering
from
the
Te
chno
logi
c
al
I
nstit
ute
of
th
e
Phili
ppine
s
in
Quez
on
Cit
y
,
P
hil
ippi
n
es.
His
r
ese
arc
h
intere
sts
inc
lud
e
wire
l
ess
bod
y
ar
ea
n
et
work,
wir
el
es
s
sensor
net
work,
queui
ng
al
g
or
it
hm
,
imag
e
proc
essing
and
m
ac
hine
learni
n
g.
Erti
e
C.
Ab
ana
is
cur
r
ent
l
y
t
he
Hea
d
of
Ce
nte
r
for
Engi
n
e
eri
ng
R
ese
arc
h
and
T
ec
hnolog
y
Innova
ti
on
in
U
nive
rsit
y
of
Sain
t
Loui
s.
He
is
t
e
ac
hing
r
ese
ar
ch
for
five
(5)
y
e
ars
to
Engi
ne
eri
ng
student
s
and
is
a
ls
o
a
p
art
-
t
ime
p
rofe
ss
or
in
th
e
G
rad
uate
School
p
rogra
m
of
Unive
rsit
y
of
Sain
t
Loui
s.
He
r
ecei
ved
the
d
egr
e
e
s
BS
in
Com
p
ute
r
Eng
ineeri
n
g
and
Master
i
n
Inform
at
ion
Te
chno
log
y
in
t
he
sam
e
unive
rsit
y
on
2011
and
2016,
respe
ctive
l
y
.
He
is
now
ta
king
up
Doctor
i
n
Inform
at
ion
T
ec
hnolog
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.