Intern
ati
o
n
a
l
Jo
urn
a
l
o
f
E
v
al
ua
ti
o
n
and
Rese
arch in
Education (I
JE
RE)
V
o
l.5
,
No
.2
,
Jun
e
2
016
, pp
. 11
3
~
11
8
I
S
SN
: 225
2-8
8
2
2
1
13
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJERE
Intention and Usage of Computer
Based Information Systems in
Primary Health Centers
Hosiz
a
h
1, 2
, K
untoro
2
,
H
a
ri Basuki N.
2
1
Faculty
of Health Scie
nces
, Es
a
Unggul University
Jakar
t
a, Indon
esia
2
Faculty
of Public Health
, Univ
er
s
itas Airlangga
Surabay
a
, Indon
esia
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Apr 17, 2016
Rev
i
sed
May 16
, 20
16
Accepted
May 29, 2016
The computer-b
ased informa
tio
n sy
stem (CBIS) is adopted b
y
almost all of
in heal
th car
e setting
,
includ
in
g the prim
ar
y
heal
th cent
e
r in
East Java
Province Indo
nesia. Some
of so
ftwares
avai
labl
e were
S
I
M
P
US
,
SIMPU
S
TRONI
K,
SIKDA
Generik,
e-pus
kesmas. Unfortunately
th
ey
wer
e
most of the primar
y
health cen
t
er di
d not successfully
implemented
.
This
stud
y
applied
the Unified Th
eor
y
of
Acceptance
and Use of
Technolog
y
(UTAUT) to as
ses
s
intention and
us
age of CBIS
i
n
Eas
t
J
a
va. It was
a cros
s
-
section
a
l survey, conducted on
Februa
r
y
-Maret 2015. A total
30 of user
CBIS were identified and q
u
estione
rs were distributed w
h
ich 100%
com
p
leted
.
Th
e user’s CBIS inten
tion was significantly influenced
b
y
per
f
orm
a
nce
expec
t
anc
y
,
eff
o
rt expec
t
an
c
y
and s
o
cial
influ
e
nce
.
CBIS
usage was sig
n
ific
antl
y
influ
e
nced
b
y
user’
s
intent
ion and
fac
ilit
at
ing
conditions
. UTAUT results ind
i
cated
that
th
e f
acilitating
conditions hav
e
a
m
a
jor im
pact
to
use of CBIS in
prim
ar
y he
alth
cen
ter.
Th
e res
u
lts of th
is
stud
y
c
a
n be h
e
l
p
ful to the
East
Java provinc
ial
Health Offi
ce to
adjust the
i
r
program
strategi
es and tact
ic for
providing user’s CBIS faciliti
es in order to
im
plem
ent CBIS
s
u
cces
s
f
ull
y
.
Keyword:
B
e
havi
or usa
g
e
B
e
havi
oral
i
n
t
e
nt
i
o
n
C
o
m
put
er ba
se
d i
n
f
o
rm
at
i
on
syste
m
(CBIS)
Prim
ary health care
UTA
U
T
Copyright ©
201
6 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
Hosiza
h,
Facu
lty of
Health
Scien
ces,
EsaUn
ggu
l Univ
ersity,
A
r
ju
n
a
Str
eet N
o
.9, K
e
bon
Jer
u
k
,
W
e
st Jak
a
r
t
a11
410
, I
ndon
esia.
Em
a
il: h
o
z
isah@esaung
gu
l.ac.id
1.
INTRODUCTION
Health I
n
fo
rm
ation Sy
stem
(H
IS)
in m
o
st co
untri
es are in
ad
equ
a
te in p
r
ov
id
ing
t
h
e n
ecessary
sup
p
o
rt fo
r
m
a
nagem
e
nt
[1]
.
In Af
rica, po
o
r
HI
S
is
th
e imp
o
rtan
t ch
alleng
es in
m
o
n
itorin
g
th
e ach
ieve
m
e
n
t
o
f
th
e Millen
n
i
u
m
Dev
e
lo
p
m
en
t Go
als (MDGs). Health
sy
ste
m
p
e
rform
a
n
ce canno
t b
e
assessed
o
r
m
o
n
ito
red
because of inc
o
m
p
lete and inaccurate data
in HIS [2].
One of the
data source
on
HIS is data and
health
in
fo
rm
atio
n
in
p
r
im
ary
h
ealth
cen
ters (
Pu
s
k
es
m
a
s
).
Dat
a
an
d
In
f
o
rm
ati
on C
e
nt
e
r
o
f
M
i
ni
st
ry
of
Heal
t
h
R
I
expl
ai
ne
d t
h
at
t
h
e el
ect
r
oni
c
i
n
f
o
rm
at
i
o
n
syste
m
used was
differe
n
t in e
ach prim
ary
h
ealth
cen
ters in
p
r
og
ram
s
sou
r
ced fro
m
th
e
District/State/Prov
i
n
c
e or
Don
o
r. Th
e su
rv
ey co
ndu
cted
in Nu
sa
Tengg
ara Barat fou
nd
th
at prim
ary h
ealth
centers m
a
de
m
o
re than 30
0
repo
rts pe
r y
ear thr
o
u
g
h
8 ki
n
d
s o
f
avai
l
a
bl
e C
B
I
S
software so the
workers
coul
d not concentrate and entry p
o
o
r
l
y
. Every
C
B
I
S ha
d di
f
f
ere
n
t
dat
a
bases an
d wa
s not
i
n
t
e
g
r
at
ed. T
h
e
adm
i
nistrative burden was
als
o
too
high
[3].
Th
e resu
lts o
f
ev
alu
a
tion
HIS in
In
don
esia was carri
e
d
o
u
t
by
t
h
e C
e
nt
er for Dat
a
an
d I
n
f
o
rm
at
i
on
Min
i
stry o
f
Health
RI i
n
2
007
,
u
s
i
n
g th
e Health
Metrics Netwo
r
k
-
Worl
d
Health
Org
a
n
i
zatio
n
(HM
N
-WHO)
con
s
i
s
t
s
of
6
com
pone
nt
s H
I
S, i
t
i
s
k
n
o
w
n
t
h
at
i
n
ge
ne
ral
HI
S i
n
I
n
d
one
si
a al
ready
e
xi
st
b
u
t
i
n
a
d
equat
e
.
Com
pone
nts of the re
source
s
(47%), in
dicators
(61%
), the source
of t
h
e da
ta (51%), dat
a
quality (55%
), the
use
a
n
d di
ssem
i
nat
i
on o
f
dat
a
(5
7%
)
as wel
l
as
dat
a
m
a
nage
m
e
nt
onl
y
(3
5
%
) [4]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
252
-88
22
IJER
E
V
o
l
.
5,
No
. 2,
Ju
ne
2
0
1
6
:
11
3 – 1
1
8
11
4
Today, m
o
st of electronic i
n
form
ation syst
e
m
used in the prim
ar
y
heal
t
h
care
onl
y
st
ore
dat
a
o
r
patient aggregate inform
atio
n because
of the nee
d
s in m
a
nagem
e
nt level. Based
on the
findings in t
h
e
globa
l
eHealth survey
by the WHO
and the
World Bank, it was
kn
o
w
n t
h
at
t
h
e
St
at
e of Afri
c
a
and So
ut
h
eas
t
Asi
a
were t
h
e hi
ghe
st
(o
ver
9
0
%) i
ndi
vi
d
u
al
pat
i
e
nt
dat
a
u
s
age i
n
pa
pe
r-
base
d
fo
rm
at
[5]
.
Heal
t
h
i
n
f
o
rm
at
i
on i
s
a
st
rat
e
gi
c res
o
urce t
h
at
i
s
neede
d
i
n
t
h
e pr
ocess o
f
m
a
nagem
e
nt
, deci
si
on
-m
aki
ng,
go
ve
rna
n
ce and
i
m
p
l
e
m
en
tatio
n
o
f
accoun
tabilit
y
an
d
goo
d g
o
v
e
rn
an
ce [6
]
,
[7
].
Health
i
n
fo
rm
atio
n
was
ob
tain
ed fro
m
th
e co
llectin
g an
d pro
cessing d
a
ta as inpu
t fo
r d
ecision-
m
a
ki
ng i
s
cal
l
e
d t
h
e M
a
na
gem
e
nt
Inf
o
r
m
at
i
on Sy
st
em
of C
o
m
m
u
n
i
t
y
Heal
t
h
C
e
nt
ers (
S
IM
P
U
S)
o
r
com
m
onl
y
kno
wn
as el
ect
r
oni
c i
n
f
o
rm
at
i
on s
y
st
em
s or c
o
m
put
e
r
-
b
ase
d
i
n
f
o
rm
at
i
on sy
st
em
(C
B
I
S).
The res
u
l
t
s
of
sur
v
ey
i
n
si
x d
i
st
ri
ct
prim
ary
heal
t
h
cent
e
r
s
B
a
nja
r
ba
r
u
So
ut
h Kal
i
m
ant
a
n N
ovem
b
er
20
1
3
not
e
d
t
h
at
m
o
st
of
p
r
i
m
ary
heal
t
h
ce
nt
ers
o
r
4
of
6
sam
p
l
e
s (6
6.
7
%
)
di
d
n
o
t
i
m
pl
em
ent
of S
I
M
P
US.
Onl
y
2 of 6 or
33
.3% use
d
S
I
M
P
U
S
. Of 2 pri
m
ary
hea
lth
cen
ters th
at
use th
e SI
MPUS, 50% a
g
ree t
h
at the
S
I
MPU
S
in
c
r
ea
s
e
d
wo
rk
lo
ad
a
t
th
e prim
ary health
ce
nter
[8].
In line wit
h
the theory
of acc
epta
nce a
nd t
h
e use o
f
i
n
f
o
r
m
at
i
on sy
st
em
s (IS
), t
h
e
Uni
f
i
e
d The
o
ry
o
f
Accepta
nce a
n
d Use
of Tec
h
nol
ogy
(UTAUT) is wi
dely us
e
d
.
UT
AUT
is the the
o
ry to pre
d
icts and e
xplains
t
h
e i
n
t
e
nt
i
o
ns
and
be
havi
or
o
f
t
h
e
use
of
In
f
o
rm
at
i
on Sy
st
em
whi
c
h i
s
a
d
e
vel
o
pm
ent
of
ei
ght
m
odel
s
o
f
t
h
e
pre
v
i
o
us st
u
d
i
e
s:
TR
A;
TAM
;
M
o
t
i
v
at
i
onal
M
odel
;
TPB
;
A C
o
m
b
ined T
h
e
o
ry
o
f
Pl
an
ned B
e
havi
or/
Technol
ogy
Acceptance
Model or CT
PB
/TAM; Model
of Personal C
o
m
put
er Use or
MPC
U
;
Di
ffusion of
Inno
v
a
tion
s
Theo
ry
o
r
IDT; So
cial Cog
n
itiv
e Psycho
log
y
|
Co
gn
itiv
e Th
eo
ry
o
r
SCT
[9
]-[1
1
]
.
This study aimedto
know
the
acceptance a
n
d intention t
o
us
e com
puter-bas
ed SI
(
CBIS) by the users
of
C
B
I
S i
n
pri
m
ary
heal
t
h
ce
nt
er
usi
n
g
UT
AUT
m
odel
ap
pr
oac
h
.
2.
R
E
SEARC
H M
ETHOD
Thi
s
obse
r
vat
i
onal
a
n
al
y
t
i
c
r
e
search
wi
t
h
c
r
oss
-
sect
i
o
nal
st
udy
desi
g
n
,
was c
o
n
d
u
ct
ed
i
n
Fe
br
ua
ry
-
M
a
rch 2
0
1
5
.
The st
udy
p
o
pul
at
i
on was use
r
of C
B
I
S o
f
p
r
i
m
ary
heal
t
h
cent
ers i
n
t
h
e p
r
ovi
nce of East
Java.
Sam
p
l
e
of
30
pe
opl
e
com
i
ng
f
r
om
3
0
pri
m
ary
heal
t
h
ce
nt
ers
i
n
fi
ve
di
st
ri
ct
s,
nam
e
l
y
:
B
a
ngkal
a
n;
Bondowos
o
; Lam
onga
n; Malang; Ke
diri
with m
u
ltistage sam
p
ling m
e
thod, each
district was re
prese
n
te
d by 6
prim
ary
health centers.
Th
e
q
u
e
stionnair
e h
a
s
b
e
en
pr
ep
ar
ed
i
n
acco
r
d
a
n
ce qu
esti
o
n
s
i
n
th
e
o
r
i
g
i
n
al U
T
AU
T [12
]
,[1
3
]
. Th
e
respon
se scale fo
r all UTAUT ite
m
s
was a six
-
po
in
t scale, rang
ing
fro
m
1
(Ex
t
remely
Un
lik
ely) to
6
(Ext
rem
e
ly
likely
)
. Bef
o
re
b
e
ing
use
d
in
researc
h
,
th
e
q
u
e
stio
nn
aires were tested
for th
e v
a
lid
it
y an
d
reliab
ility first. Th
e resu
lt showed
t
h
at th
e valid
ity an
d
reliab
ility was g
o
o
d
(th
e
C
r
onb
ach
Al
p
h
a
v
a
lue was
0.
84
2
)
. A t
o
t
a
l
30 que
st
i
o
n
n
a
i
r
es were
di
st
r
i
but
ed
whi
c
h 10
0% (
3
0 res
p
o
n
ses
)
was a
n
swe
r
e
d
com
p
l
e
t
e
ly
andc
o
n
si
de
red
as val
i
d
o
n
es.
3.
R
E
SU
LTS AN
D ANA
LY
SIS
Pri
m
ary
Heal
th C
e
nt
er
uses
vari
o
u
s t
y
pes
of El
ect
r
oni
c
Inf
o
rm
ati
on
Sy
st
em
or C
B
I
S i
n
fi
ve
d
i
stricts/cities
in
East Jav
a
prov
in
ce as shown
i
n
Ta
b
l
e
1, m
o
st o
f
p
r
i
m
ary h
ealth
cen
ters
u
s
ing
SIKDA
G
e
n
e
r
i
k 46
.7
%.
Tabl
e
1. Ty
pe
of
C
B
I
S i
n
Fi
v
e
Di
st
ri
cs
Pr
ov
i
n
ce East
Ja
va
T
y
pe of CBI
S
Fr
equancy
Percentage
Sim
pustr
onik 6
20.
0
SI
KDA Gener
i
k
14
46.
7
SI
K 6
20.
0
e-
puskes
m
as
4
13.
3
T
o
tal 30
100
So
urce:
dat
a
pr
ocessi
n
g
by
M
s
Excel
,
2
0
1
5
Co
n
s
t
r
u
c
t
v
a
lid
ity test resu
lts with
th
e Sm
art PLS in
m
easurem
en
t
m
o
d
e
l can
b
e
seen
in
th
e v
a
l
u
e
o
f
Co
nv
erg
e
n
t
Valid
ity an
d
reliab
ility tests wit
h
v
a
l
u
e of
Com
p
o
s
ite Rel
i
ab
ilit
y (CR) an
d
Cron
b
a
ch
's Alp
h
a
. In
Tabl
e
2 t
h
e
va
l
u
e o
f
t
h
e l
o
ad
i
ng
fact
o
r
(C
o
nve
r
g
ent
Val
i
d
i
t
y
) al
l
const
r
u
c
t
bet
w
ee
n
0.
6
0
5
-
0.
98
1,
i
t
ca
n
be
expl
ai
ne
d t
h
at
alm
o
st
al
l
i
ndi
cat
ors
o
f
l
o
a
d
i
n
g fact
or >
0.
7.
Onl
y
one
i
ndi
cat
o
r
of s
o
ci
al
co
nst
r
uct
s
t
h
a
t
i
n
fl
ue
nce
or S
I
1
(su
b
j
ect
i
v
e
no
rm
) wi
t
h
l
o
adi
n
g fact
or
o
f
0.
6
0
5
.
Th
e l
o
adi
ng
fact
o
r
of
0.
5 -
0.
6 i
s
st
i
ll
con
s
i
d
ere
d
qui
t
e
[1
4]
.A
vera
g
e
Vari
a
n
ce E
x
t
r
act
ed (
A
VE)
> 0.
5 (
0
.
6
22
-0
.
9
2
7
)
, i
t
sh
ow
s
t
h
at
al
l
i
ndi
cat
ors a
r
e
val
i
d
. C
R
>
0.
7 (0
.8
3
9
-
0
.
9
58
) an
d C
r
o
n
b
ach'
s
Al
p
h
a > 0.6 (
0
.
7
33
-
0
.
9
3
4
)
. Th
us
al
l
t
h
e const
r
uct
s
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ERE
I
S
SN
:
225
2-8
8
2
2
Int
e
nt
i
o
n
a
n
d
Usa
g
e
of
C
o
m
put
er
Ba
sed
I
n
f
o
rm
at
i
o
n
Syst
ems i
n
Pri
m
ar
y He
al
t
h
C
e
nt
ers (
H
o
s
i
z
a
h
)
11
5
Perform
a
n
ce E
x
p
ectan
cy, Effo
rt Exp
ectan
cy, So
cial In
fl
uen
ce, Facilitati
n
g
Cond
itio
n
s
, Beh
a
v
i
or In
ten
tio
n,
Usage Beha
vi
or
has m
e
t the
cut-off
value
of t
h
e
requ
ire
d
and acce
ptabl
e
. This s
hows
the reliability of t
h
e
m
easurem
ent
m
odel
i
s
very
go
o
d
.
Tab
e
l
2
.
Factor Lo
ad
ing
s
, Com
p
o
s
ite Reliab
ilit
y, AVE an
d
Cron
b
a
ch’s
Alp
h
a
Constr
ucts
I
t
em
s
L
o
adings
Co
m
posite
Reliability
AVE
Cr
onbach’
s
Alpha
Perf
or
m
a
nce Expectancy
(PE)
PE1
PE2
PE3
PE4
PE5
0.
740
0.
787
0.
824
0.
796
0.
794
0.
891
0.
622
0.
854
Ef
f
o
rt Expectancy
(EE
)
EE1
EE2
EE3
0.
849
0.
849
0.
852
0.
886
0.
722
0.
811
Social Inf
l
uence (
S
I)
SI1
SI1
SI2
0.
605
0.
907
0.
856
0.
839
0.
839
0.
733
Facilitating Conditions (FC)
FC1
FC2
FC3
0.
877
0.
981
0.
959
0.
958
0.
884
0.
934
Behavior
I
n
tention
(
B
I
)
or
Intention to use CBIS
BI1
BI2
BI3
0.
863
0.
928
0.
822
0.
905
0.
761
0.
841
Usage Behavior
(UB)
or
Usage CBIS
UB1
UB2
UB3
0.
752
0.
976
0.
957
0.
927
0.
927
0.
881
So
urce:
dat
a
pr
ocessi
n
g
by
usi
n
g
SM
AR
T
-
P
L
S, 2
0
1
5
After th
e m
o
d
e
l b
e
ing
estimated
to m
eet c
r
iteria of
ou
ter m
o
d
e
l, and
t
h
en
co
n
t
i
n
u
e
d
t
o
the inn
e
r
m
o
d
e
l test. Th
e test resu
lts in
n
e
r m
o
d
e
l con
s
isted
o
f
a co
efficien
t p
a
ram
e
te
r p
a
th
(path
coefficien
t p
a
rameter),
t
h
e val
u
e
of
R
Sq
uare
(R
2
)
i
n
Tabl
e
3 a
n
d
Ta
bl
e 4
.
Th
e resu
lt
of path
an
alysis
in
Tab
l
e 3
sho
w
s th
at
in
ten
tion
t
o
u
s
e CB
IS
were sign
ifican
tly in
fl
u
e
n
c
ed
by pe
rform
a
nce expectancy,
effort e
x
pectancy and s
o
ci
al
i
n
fl
uence
(al
l
p
-
val
u
es <
0
.
0
5)
. U
s
age
C
B
I
S
were
sig
n
i
fican
tly in
flu
e
n
ced
b
y
facilitat
i
n
g
con
d
i
tio
n
s
and
in
tentio
n
to
use CBIS. Pat
h
co
effi
cien
t p
a
ram
e
te
r and
p
-
v
a
lu
es on
facilitat
i
n
g
co
nd
itio
n
s
(0
.95
2
;
0
.
00
0) is
m
o
re t
h
an
in
ten
tio
n to use CBIS
(0
.0
66; 0
.
0
46).
Tabl
e 3. Pat
h
C
o
ef
fi
ci
ent
o
f
C
onst
r
uct
Direct
and indirect
inf
l
uence between
endogen
ous and ex
ogeno
us var
i
able
Path
Coef
f
i
cient
Sa
m
p
le Mean
(M)
Standar
d
Erro
r
T Statistics
P-values
Perf
or
m
a
nce Expectancy
Intention to
Use CBIS
0.
304
0.
347
0.
135
2.
250
0.
025*
Ef
f
o
rt Expectancy
Intention to Use
CBIS
0.
382
0.
328
0.
200
1.
967
0.
044*
Social Inf
l
uence
Intention to Use
CBIS
0.
327
0.
367
0.
157
2.
077
0.
038*
Facilitating Conditions
Usage CBI
S
0.
952
0.
958
0.
025
38.
266
0.
000*
*
Intention to Use CBIS
Usage
CBI
S
0.
066
0.
064
0.
049
1.
959
0.
046*
So
urce:
dat
a
pr
ocessi
n
g
by
usi
n
g
SM
AR
T
-
P
L
S, 2
0
1
5
(*
si
g=0
.
0
5
,
*
*
si
g
=
0.
01
)
In Ta
bl
e 4, R
-
s
qua
re i
n
t
e
nt
i
o
n
t
o
use C
B
I
S am
ount
ed 0.
5
7
5
.
It
m
eant
t
h
at
the effect
s o
f
t
h
e const
r
uct
by
0
.
5
7
9
i
n
t
h
e cat
eg
ory
of
m
oderat
e
an
d
alm
o
st
st
ron
g
. Th
is showed
th
at th
e Performance
Expect
ancy,
Eff
o
rt
E
x
pect
ancy
, S
o
ci
al
In
f
l
uence c
o
ul
d e
xpl
ai
n
t
h
e
vari
ance i
n
t
e
nt
i
on
t
o
use C
B
IS a
m
ount
ed t
o
5
7
.
9
% a
n
d
t
h
e
rem
a
i
n
i
ng 42
.1
% was
i
n
f
l
uence
d
by
ot
h
e
r vari
a
b
l
e
s.
R
-
sq
ua
re of
C
B
I
S
u
s
age
am
ount
ed 0.
9
3
4
(
s
t
r
on
g
)
.
Th
is showed
t
h
at th
e in
ten
tion
to
u
s
e CBIS an
d
facilitatin
g
co
nd
itio
n
s
o
f
CBIS u
s
ag
e exp
l
ain
e
d
v
a
riance o
f
93
.4
% a
n
d
t
h
e
rem
a
i
n
i
ng i
n
fl
uence
o
f
ot
he
r
vari
a
b
l
e
s.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
252
-88
22
IJER
E
V
o
l
.
5,
No
. 2,
Ju
ne
2
0
1
6
:
11
3 – 1
1
8
11
6
Tabel
4. R
-
S
q
u
a
re (R
2
)
Constr
ucts
R-sq
u
a
re (R
2
)
Intention to Use CBIS
0.
575
Usage CBIS
0.
934
So
urce:
dat
a
pr
ocessi
n
g
by
usi
n
g
SM
AR
T
-
P
L
S, 2
0
1
5
3.
1.
Perfor
mance Expectanc
y
Perf
o
r
m
a
nce Expect
a
n
cy
con
s
i
s
t
s
of fi
ve i
n
di
cat
ors:
pe
rce
i
ved use
f
ul
nes
s
, ext
r
i
n
si
c m
o
t
i
v
at
i
on, j
o
b-
fit, relativ
e adv
a
n
t
ag
e,
o
u
t
come ex
p
ectation
s
. Particip
an
t
s
respon
ded
li
k
e
ly an
d
ex
tremely
lik
ely o
n
all o
f
i
ndi
cat
o
r
perce
i
ved
use
f
ul
nes
s
, e
x
t
r
i
n
si
c
m
o
t
i
v
at
i
on,
j
o
b-
fi
t
,
rel
a
t
i
v
e a
d
va
nt
age,
out
c
o
m
e
ex
pect
at
i
o
n
s
m
o
re
than 78%.
Path coefficient of pe
rformance e
xpecta
n
cy a
ffected
t
h
e in
ten
tion
to u
s
e CBIS by 0
.
304
an
d
significa
nt t-st
atistic of
2.250
(>
1.96). This can
be
expl
ained that the
perform
ace
expectancy use
r
CBIS
p
o
s
itiv
e effect
o
n
in
ten
tion to
u
s
e CBIS.
Perform
a
n
ce e
x
p
ectan
cy p
o
sitiv
e affected
beh
a
v
i
o
r
in
ten
tio
n, th
is is in
l
i
n
e
with
p
r
ev
i
o
u
s
st
u
d
i
es
[10],[14]. The
r
e was a
differe
n
ce
with
the
re
sults of res
earc
h
on t
h
e
use “I
Pass” in
Taiwan
wh
ich
states th
at
per
f
o
r
m
a
nce expect
a
n
cy
h
a
d
no
si
g
n
i
f
i
cant
effect
on
be
ha
vi
o
r
i
n
t
e
nt
i
o
n
[
15]
.
3.
2.
Ef
fo
r
t
Ex
p
e
cta
n
cy
Effort e
x
pectancy is com
pos
ed of
t
h
ree i
n
di
cat
ors
nam
e
l
y
percei
ved
ea
se
of
use, com
p
lexity, ease of
u
s
e. Particip
ants resp
ond
ed lik
ely and
ex
tremely lik
ely
on all of indicator
percei
ved eas
e of
use, com
p
lexity,
ease of
use
more
tha
n
81%. Effect
o
f
effo
rt exp
ectan
cy
to
t
h
e i
n
ten
tio
n to u
s
e CB
IS tested
with p
a
t
h
co
eff
i
cien
t
o
f
0
.
38
2 and
sig
n
i
f
i
can
t t-
stat
istic o
f
1
967 (
>
1
.
9
6
)
.
Th
is can
b
e
exp
l
ain
e
d
t
h
at th
e ef
for
t
ex
p
ectan
cy
u
s
er CBIS affected
p
o
s
itiv
ely
o
n
in
ten
tion
t
o
u
s
e CBIS.
Effort e
x
pectancy affect posi
tively on i
n
tent
ion t
o
use CBIS. CBIS u
s
er
of th
e
prim
ary health centre
,
th
is is in
lin
e
with
th
e th
eo
ry UTAUT
prop
o
s
ed
b
y
Ve
nkatesh et al.,
2003. T
h
is
res
u
lt is as well
as the
pre
v
i
o
us st
u
d
y
[1
0]
, [
14]
. T
h
ere i
s
a di
ffe
re
nce wi
t
h
t
h
e r
e
sul
t
s
of t
h
e E
x
am
i
n
i
ng Loca
t
i
on-B
a
se
d Se
r
v
i
ces
(LBS)
Usa
g
e from
the Pers
pectives of
Uni
f
ied T
h
eory
of Accepta
nce a
nd
Use
of
Tec
h
nology and Privacy
Risk which sta
t
ed that t
h
e effort
e
x
pectancy
had no
si
g
n
i
f
i
cant
ef
fect
on
b
e
havi
or
i
n
t
e
nt
i
o
n
[
9
]
.
3.
3.
Social Influe
nce
Social influe
nce is co
m
pos
ed
of s
u
b co
nst
r
uct
su
bjec
t
i
v
e no
rm
s, s
o
cial factors
and im
age.
Particip
an
ts resp
ond
ed
lik
ely and
ex
trem
el
y lik
ely o
n
a
ll of ind
i
cator su
bj
ectiv
e no
rm
s, social factors
a
nd
im
age m
o
re
than
84%.
So
cial In
fluence p
o
sitiv
ely affected
i
n
ten
t
i
o
n
t
o
use of
CBIS with
p
a
t
h
co
efficien
t of 0.327
and
si
gni
fi
ca
nt
t
-
st
at
i
s
t
i
c
of 2.
07
7 (>
1.
96
). T
h
i
s
can be e
x
pl
ai
ned em
pi
ri
cal
l
y
t
h
at
soci
al
infl
uence
of
pr
im
ary
h
ealth
cen
t
er
user CBIS
h
a
d po
sitiv
e
effect
on
in
ten
tio
n to use CBIS.
Th
is
research
lin
e is con
s
ist
e
n
t
with resu
lt
s of
pre
v
i
o
us st
udi
es o
n
hea
l
t
h
i
n
f
o
rm
at
i
on
sy
st
em
s
t
o
i
m
p
r
ov
e
h
ealth care:
A telem
e
d
i
cin
e
case stud
y wh
ich fou
n
d
th
at
so
cial influ
e
n
ce re
su
lts
as po
sitiv
e effect on
beha
vi
o
r
i
n
t
e
nt
i
on
[
10]
,
[
1
4
]
.
3.
4.
I
n
t
e
nt
io
n to
Us
e C
B
I
S
Int
e
nt
i
on t
o
u
s
e C
B
I
S co
nsi
s
t
s
of t
h
ree i
ndi
c
a
t
o
rs i
n
t
e
n
d
,
pr
edi
c
t
an
d pl
a
n
.
Int
e
nt
i
on t
o
u
s
e C
B
I
S ha
d
p
o
s
itiv
e effect on
CBIS
u
s
ag
e
w
ith
t
h
e
p
a
th
co
efficien
t
o
f
0.066
an
d sig
n
i
fican
t
w
ith a t-statistic o
f
1
.
959
(>1.96
). It can b
e
em
p
i
ricall
y
ex
p
l
ain
e
d
that th
e
in
ten
tion
to
u
s
e CBIS affected
po
sitiv
ely o
n
CBIS u
s
age
effect
on prim
a
r
y health cente
r.
The R
2
i
n
t
e
nt
i
on t
o
use C
B
I
S was
0.
57
5, t
h
i
s
co
ul
d e
xpl
ai
n t
h
at
pe
rf
or
m
a
nce expect
a
n
cy
, ef
fo
rt
expect
a
n
cy
, s
o
ci
al
i
n
fl
ue
nc
e
m
a
y
expl
ai
n va
ri
ance i
n
t
e
nt
i
on t
o
us
e
C
B
I
S am
oun
t
e
d t
o
5
7
.
9
%
and t
h
e
rem
a
i
n
i
ng 4
2
.
1
% i
s
i
n
fl
ue
nce
d
by
ot
her
va
ri
abl
e
s.
3.
5.
Fa
cilitating Co
nditi
o
n
s
Fasilitating conditions consi
s
ted of three
indicator
s of percei
ved
behavior control
,
fasilitating
co
nd
itio
ns,
com
p
at
ib
ility.
Fa
silitat
i
n
g
cond
itio
n
s
h
a
d
po
sitiv
e
effect o
n
Usage
CBIS with
co
efficien
t p
a
th
o
f
0
.
9
5
2
an
d
si
g
n
ifican
t with
a t-statistic o
f
38
.2
66
(>1
.
96
). Th
is can
b
e
explain
e
d
th
at emp
i
rically, facilitatin
g
co
nd
itio
ns h
a
d p
o
s
itiv
e
effect o
n
u
s
ag
e
CBIS at th
e
p
r
im
ary h
ealth
cen
t
er.
Path coe
fficient on facilitating cond
ition sc
ore
d
hi
ghest a
m
ong the cons
truct that affec
t
ed the usage
CBIS in
prim
a
r
y h
ealth
cen
t
re. It supp
orted th
e stat
e
m
en
t o
f
V
e
nk
atesh et al., th
at facilitat
i
n
g
conditio
n
s
affects th
e emp
l
o
y
ees in
th
e
o
r
g
a
n
i
zatio
n
.
It sh
ows th
at facilitat
i
n
g
con
d
i
tio
n
s
in
prim
ar
y h
ealth
cen
ter h
a
v
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ERE
I
S
SN
:
225
2-8
8
2
2
Int
e
nt
i
o
n
a
n
d
Usa
g
e
of
C
o
m
put
er
Ba
sed
I
n
f
o
rm
at
i
o
n
Syst
ems i
n
Pri
m
ar
y He
al
t
h
C
e
nt
ers (
H
o
s
i
z
a
h
)
11
7
h
i
gh
est i
m
p
act o
n
CBIS u
s
ag
e. Facilitati
n
g
co
nd
itio
ns in
clu
d
e
resou
r
ce av
ailab
ility, su
ch
as tech
n
i
cal
assistan
ce,
kn
owledg
e
o
f
th
e syste
m
an
d
co
mp
atib
ility
with
o
t
h
e
r system
s
alread
y in u
s
e [1
2
]
,[13
].
4.
CO
NCL
USI
O
N
Five
hypothesi
s
of this
study ar
e all accepted and in line
with th
e original theo
ry of UTAUT.
Varia
n
ce intention to
use C
B
IS affected
by perform
an
ce expecta
n
cy,
effort e
xp
ecta
n
cy, social influence
am
ount
e
d
t
o
5
7
.
9
% an
d t
h
e
rem
a
i
n
i
ng 42
.
1
% i
s
i
n
fl
ue
n
ced by
ot
h
e
r
vari
a
b
l
e
s. C
B
I
S usa
g
e vari
a
n
ce i
n
p
r
im
ary h
ealth
cen
ters b
y
93.4
%
affected
by th
e in
ten
tio
n to
u
s
e CBIS
an
d
facilitatin
g
con
d
ition
s
an
d
th
e
rem
a
ining
infl
uence of othe
r varia
b
le
s. Effe
ct of facilitating conditions
ha
sthe m
o
st powerful am
ong the other
construct, it is
becom
i
ng a
major
determ
inant for s
u
ccess
f
ul
im
ple
m
entation of CBIS in priary
health c
e
nters
.
Facilitating conditions incl
ude the availability of techni
cal
assistance in the operat
i
on
of CBIS, a
good gras
p
o
n
th
e
syste
m
t
h
at is
b
e
ing
u
s
ed
f
o
r
th
e user
an
d CBI
S should
b
e
co
m
p
atible w
ith
o
t
h
e
r
syste
m
s.
ACKNOWLE
DGE
M
ENTS
The a
u
thors wish to t
h
ank a
n
d to e
x
press
grateful
n
e
ss to th
e all of
p
a
rticip
an
ts and
t
h
e research
tea
m
. Specialty thank to the Provi
n
ce a
nd District
Health
Official and the
Ba
kesba
ngpo
l
(Th
e
Natio
nal Un
ity
an
d Po
litics) for licen
cing
.
REFERE
NC
ES
[1]
T. Lipp
eveld
,
et al.
, “Design and
Implementation
of Health Inform
ation
S
y
stems,” WHO,
Geneva, 2000.
[2]
Mutale W
,
et al.
, “Improving health informatio
n s
y
stems for d
ecision making
across five
sub-
Saharan African
countries: Implementation
strategies from the Af
ri
can
Health In
itiativ
e,”
BMC He
alth Ser
v
ic
es R
e
search
, vol/issue:
13(2), pp
. S9, 20
13. http://www.bi
omedcentr
al.co
m
/1472-6963/13/S2/S9.
[3]
S
o
epardi J
.
, “
H
um
an Res
ource
s
for Health In
form
ation
S
y
stem, Center for
Data and In
for
m
ationMinistr
y
of
Health
,”
Scientific M
eeting I
X
M
e
dica
l Informat
ics PSIK Gunada
rma, Depok-Jaw
a Barat
, 2012.
[4]
Ministr
y
of Health RI, “Surat Ke
putusan No.192/Menke
s/SK/VI/2012: ROADM
AP
Plan
of Strengthtening Health
Information S
y
s
t
em,” 2012
. h
ttp://depke
s.go
.id/do
wnloads/RoadMapSIK.PDF
[5]
W
o
rld Health Organiza
tion (
W
HO),
“
M
anagem
ent of P
a
tien
t
Information: Trends and Challeng
es in Member
States: b
a
sed on
the f
i
ndings of
the
second
glob
al survey
on
eH
ealth,”
Global O
b
servatory for eHealth Series,
vo
l.
6, 2012
.
[6]
Ministr
y
of Health RI, “Sur
at Keputusan No.184 tahun 2004,”
T
h
e Bas
i
cs
Poli
cy
of Pr
imar
y Health Center
, 2012
.
http://www.
depkes.
go.
id.
[7]
Ball M. J.,
et al.
, “
P
ers
onal
Health Re
cord
s: Empowering Consumers,”
Journal of Health
care Information
Management,
vo
l/issue: 21
(1), 20
07.
[8]
Hosizah, “Survey
on Using Co
mputer-Based
I
n
formation S
y
stems (CBIS),” in
Primary Health Ce
nte
r
Distric
t
Banjarbaru South Kalimantan
, 2
013.
[9]
Z. Tao
,
“Examining Locati
on-
Bas
e
d S
e
rvices
(LBS
) Us
age F
r
om The P
e
rs
pectiv
es
of Unified Th
eor
y
of
Accept
a
nc
e and
Use of Technolo
g
y
and Priv
ac
y
Risk,”
Journal o
f
Electronic Commerce Research
, vol/issue: 13(
2)
,
pp.135-144, 201
2.
[10]
Fillion G.
,
et al.
, “Testing UTAUT on th
e Use of
ERP S
y
stems b
y
Middle Man
a
gers and End-User
s of Medium-to
Large-S
i
zed Ca
nadian En
terpr
i
s
e
s
,
”
Academy of Information and
Management Scien
ces
Journa
l
, vol/issue: 15(
2),
2012
[11]
Y. C. Son, “Fa
c
tors Affecting
Individuals To
Adopt
Mobile Banking: Empir
i
ca
l Eviden
ce From The UTAUT
Model,”
Journal of
Electroni
c C
o
mmer
ce R
e
s
e
ar
ch
, vo
l/issue: 13
(2), pp
. 104-121
, 2012.
[12]
Venkatesh V,
et al.
, “A Theoretical Ex
tension
of the
Techno
l
o
g
y
Acceptance
Model: Four Lo
ngitudinal Field
Studies,”
Manag
ement S
c
ience Journal,
vol/issue: 46(2), pp. 186-
204, 2000
.
[13]
Venkatesh V,
et
al
., “
U
ser Acceptanc
e of Inform
ation Technol
og
y
:
Toward a
Unified View,”
MIS Quarterly,
vol.
27, pp
. 425-478
, 2003. Avail
a
ble from
:
http
://ww
w
.vve
nkat
e
sh.co
m
/it/organi
z
atio
ns
/theoretical_m
odels.asp.
[14]
Hengk
y
L. & Gh
ozali I
.
, “Partial
Least Squares:
K
onsep Aplikasi Path Modelling
,
” UNDIP, Semarang, 2013
.
[15]
Cilli
ers L. & S.
V. Flowerda
y, “
H
ealth inform
a
t
i
on sy
st
em
s to im
prove hea
lth c
a
r
e
: A tel
e
m
e
dicin
e
case stud
y,
”
SA
Journal of In
fo
rmation Management
, vol/issue: 15(1), 20
13.
Art. #541, 5
p
a
ges. h
ttp://dx.d
o
i.org/10
.4102
/
sajim.v15i1.541
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
252
-88
22
IJER
E
V
o
l
.
5,
No
. 2,
Ju
ne
2
0
1
6
:
11
3 – 1
1
8
11
8
BIOGRAP
HI
ES OF
AUTH
ORS
Hosizah is docto
ral student of Health Science in
Universitas
Airlangga
Surabay
a
, Indonesia. She
is a lecturer of
Health Scienc
e
Faculty
,
EsaUng
gul University
J
a
karta, Indon
esia. She gr
aduate
d
from Indonesia
University
, with
a MS in Health
In
formatics of
Public Health S
c
ien
c
e. Prior
to
that
, s
h
e
gradu
a
ted from
B
ache
l
or degre
e
in He
alth
Inform
ation
of P
ubli
c
He
alt
h
F
acul
t
y
Es
a
Unggul University
, and
a Diplo
m
a in Health In
formation Management (Medical Record and
Health Information). She is Dir
ector of Indon
esian Higher Ed
ucation for Health Information
M
a
nagem
e
nt As
s
o
ciation (IH
E-
HIM
A
) or aptiRM
I
K, a m
e
m
b
er of Am
erican He
alth Inform
at
ion
Management Associati
on
(AHIMA) and a member team a
ssessor ofIndonesian Accreditation
Agency
for Higher Education (IA
AHEH).
Dr. Kuntoro is a Professor in Department of
Public Health
Science, Univ
ersitasAirlangga
Surabay
a
, Indon
esia. He ob
tain
ed a Dr.PH and MP
H fro
m Department of Bi
ostatistics, Gr
aduate
School Public
HealthUniv
ersit
y
of Pittsburgh
Pe
nns
y
l
van
i
a U
S
A. Prior to that, he gr
aduate
d
from
Medical F
acul
t
y
, Univ
ersit
a
sAirlangga Sur
a
ba
y
a
. Professor Kuntoro is Visiting Professor
at Public Health
Program, Mahidol University
,
Nakhon Sawan Campus in Thailand. He is a
m
e
m
b
er of Am
e
r
ican S
t
atis
ti
ca
l
As
s
o
ciation (AS
A
) and Interna
t
i
onal Biom
etri
c
S
o
ciet
y (IBS
)
.
Professor Kuntoro has published
and presented
num
erous
peer r
e
viewed p
a
pers
at th
e nat
i
ona
l
and in
terna
tion
a
l
lev
e
ls.
Hari Bas
uki N. is
a lectur
er and
s
e
nior res
earch
erat Dep
a
rtm
e
nt
Bios
tatis
ti
cs
of P
ublic Healt
h
Faculty
,
Univ
ersitasAirlangga Su
rabay
a
, Indonesia. Hegradu
a
ted f
r
om Doctor degree at Medical
F
acult
y,
M
a
s
t
er
degre
e
at
P
ublic He
alth
F
a
cult
y,
Ba
chelor
degre
e
at
M
e
dica
l F
acul
t
y
,
UniversitasAirlangga Surabay
a
.
Hari Basuki N
.
has published
and presented
numerous peer
reviewed
pap
e
rs
at the
nat
i
onal and international
levels.
Evaluation Warning : The document was created with Spire.PDF for Python.