H
S
I
L
G
N
E
–
I
N
D
O
N
E
S
I
A
N
C
O
D
E
-
M
I
X
I
N
G
U
S
E
D
B
Y
N
A
I
S
E
N
O
D
N
I
T
W
I
T
T
E
R
U
S
E
R
S
A
S
S
E
E
N
T
H
R
O
U
G
H
T
H
E
I
R
S
T
E
E
W
T
S I S E H T E T A U D A R G R E D N U N A
s t n e m e ri u q e R e h t f o t n e m ll if l u F l a it r a P s a d e t n e s e r P
r o
f theDegreeo fSarjanaSastra s r e tt e L h s il g n E n i
y B
T I K A N I R A W I J U T S A W R A N I N A V E T S
: r e b m u N t n e d u t
S 084214053
S R E T T E L H S I L G N
E STUDYPROGRAMME
T N E M T R A P E
D OFENGLISHLETTERS
S R E T T E L F O Y T L U C A F
Y T I S R E V I N U A M R A H D A T A N A S
A T R A K A Y G O Y
i
H
S
I
L
G
N
E
–
I
N
D
O
N
E
S
I
A
N
C
O
D
E
-
M
I
X
I
N
G
U
S
E
D
B
Y
N
A
I
S
E
N
O
D
N
I
T
W
I
T
T
E
R
U
S
E
R
S
A
S
S
E
E
N
T
H
R
O
U
G
H
T
H
E
I
R
S
T
E
E
W
T
S I S E H T E T A U D A R G R E D N U N A
s t n e m e ri u q e R e h t f o t n e m ll if l u F l a it r a P s a d e t n e s e r P
r o
f theDegreeo fSarjanaSastra s r e tt e L h s il g n E n i
y B
T I K A N I R A W I J U T S A W R A N I N A V E T S
: r e b m u N t n e d u t
S 084214053
S R E T T E L H S I L G N
E STUDYPROGRAMME
T N E M T R A P E
D OFENGLISHLETTERS
S R E T T E L F O Y T L U C A F
Y T I S R E V I N U A M R A H D A T A N A S
A T R A K A Y G O Y
v i
N A U J U T E S R E P N A A T A Y N R E P R A B M E L
S I M E D A K A N A G N I T N E P E K K U T N U H A I M L I A Y R A K I S A K I L B U P
: a m r a h D a t a n a S s a ti s r e v i n U a w s i s a h a m a y a s ,i n i h a w a b i d n a g n a t a d n a tr e b g n a Y
a m a
N :Stevan iNarwastuJ iwaRinakti a
w s i s a h a M r o m o
N :084214053
e g n e p u m li n a g n a b m e g n e p i m e
D tahuan ,saya membeirkan kepada Perpustakaan :l
u d u jr e b g n a y a y a s h a i m li a y r a k a m r a h D a t a n a S s a ti s r e v i n U
h s il g n
E – IndonesianCode-MixingUsedbyI ndonesianTwitterUser sa sSeen s
t e e w T r i e h T h g u o r h T
r e v i n U n a a k a t s u p r e P a d a p e k n a k ir e b m e m a y a s n a i k i m e d n a g n e
D stia sSanata
, n i a l a i d e m k u t n e b m a l a d n a k h il a g n e m , n a p m i y n e m k u t n u k a h a m r a h D
n a d , s a t a b r e t a r a c e s n a k i s u b ir t s i d n e m , a t a d n a l a k g n a p k u t n e b m a l a d a y n a l o l e g n e m
s i m e d a k a n a g n it n e p e k k u t n u n i a l a i d e m u a t a t e n r e t n i i d a y n n a k i s a k il b u p m e m
n ij i a t n i m e m u lr e p a p n a
t dar isaya maupun membeirkan royatl ikepada saya .s
il u n e p i a g a b e s a y a s a m a n n a k m u t n a c n e m p a t e t a m a l e s
. a y n r a n e b e s n a g n e d t a u b a y a s i n i n a a t a y n r e p n a i k i m e D
, a tr a k a y g o Y i d t a u b i D
2 1 0 2 r e b m e v o N 0 3 : l a g g n a t a d a P
n a k a t a y n e m g n a Y
v
p
u
e
vi
g
r
e
v
e
n
ll'
I
ni
e
vi
g
r
e
v
e
N
ni
p
il
s
t
b
u
o
d
f
o
y
a
r
a
t
el
r
e
v
e
N
ll
a
f
I
fi
d
n
A
li
a
f
r
e
v
e
n
ll'
I
ni
a
g
a
y
rt
d
n
a
p
u
t
e
g
t
s
u
j l
l'I
e
p
o
h
e
s
o
l
r
e
v
e
N
h
ti
a
f
e
s
o
l
r
e
v
e
N
e
k
a
t
s
t
a
h
c
u
m
o
o
t
h
c
u
m
s
'
e
r
e
h
T
d
n
e
p
e
d
t
s
u
m
I
fl
e
s
y
m
n
o
p
U
e
c
al
p
r
o
f
g
ni
k
o
o
l
t
o
n
m
'I
o
r
s
h
o
w
ni
w
a
n
n
o
g
m
'I
t h gi n K c M n ai r
i v
,
s
t
n
e
r
a
p
d
e
v
o
l
e
b
y
m
r
o
F
n
o
t
h
i
n
g
o
t
s
e
r
a
p
m
o
c
y
o
u
r
e
v
e
r
l
a
s
t
i
n
g
l
o
v
e
,
&
s
r
e
y
a
r
p
s
u
p
p
o
r
t
;
I
l
o
v
e
y
o
u
.
o
T
e
v
e
r
y
T
w
e
e
p
i
n
t
h
e
T
w
i
t
t
e
r
l
a
n
d
w
h
o
e
m
d
e
r
i
p
s
n
i
w
i
t
h
t
h
e
i
r
t
w
e
e
t
s
t
o
d
o
t
h
i
s
n
o
p
e
e
k
d
n
a
t
o
l
a
s
k
n
a
h
t
,
h
c
r
a
e
s
e
r
!
g
n
i
p
r
i
h
c
i v
,
s
t
n
e
r
a
p
d
e
v
o
l
e
b
y
m
r
o
F
n
o
t
h
i
n
g
o
t
s
e
r
a
p
m
o
c
y
o
u
r
e
v
e
r
l
a
s
t
i
n
g
l
o
v
e
,
&
s
r
e
y
a
r
p
s
u
p
p
o
r
t
;
I
l
o
v
e
y
o
u
.
o
T
e
v
e
r
y
T
w
e
e
p
i
n
t
h
e
T
w
i
t
t
e
r
l
a
n
d
w
h
o
e
m
d
e
r
i
p
s
n
i
w
i
t
h
t
h
e
i
r
t
w
e
e
t
s
t
o
d
o
t
h
i
s
n
o
p
e
e
k
d
n
a
t
o
l
a
s
k
n
a
h
t
,
h
c
r
a
e
s
e
r
!
g
n
i
p
r
i
h
c
i v
,
s
t
n
e
r
a
p
d
e
v
o
l
e
b
y
m
r
o
F
n
o
t
h
i
n
g
o
t
s
e
r
a
p
m
o
c
y
o
u
r
e
v
e
r
l
a
s
t
i
n
g
l
o
v
e
,
&
s
r
e
y
a
r
p
s
u
p
p
o
r
t
;
I
l
o
v
e
y
o
u
.
o
T
e
v
e
r
y
T
w
e
e
p
i
n
t
h
e
T
w
i
t
t
e
r
l
a
n
d
w
h
o
e
m
d
e
r
i
p
s
n
i
w
i
t
h
t
h
e
i
r
t
w
e
e
t
s
t
o
d
o
t
h
i
s
n
o
p
e
e
k
d
n
a
t
o
l
a
s
k
n
a
h
t
,
h
c
r
a
e
s
e
r
ii v
S T N E M G D E L W O N K C A
o t e d u ti t a r g t s e t a e r g y m s s e r p x e o t e k il d l u o w I , ll a f o t s ri
F Jesu sChrist
r o
f a lloft heblessing sHeha sgiven to me .It hank Him fo rguiding mepasst he .s
i s e h t s i h t g n i h s i n if n i e m it d r a h
, r o s i v d a s i s e h t y m o t s e o g n o it a i c e r p p a t s e p e e
D Dr .Franci sBorgia sAilp ,
. A . M , . d P .
M ,fo rhi sguidance in the proces so fcompleitng my thesis . Iam u
s s i h r o f l u f e t a r g y l p e e
d ggesiton ,advice ,assistance ,and ciritcism i n every par t
k n a h t o t e k il d l u o w o s l a I . s i s e h t s i h t f o n o it e l p m o c e h t g n ir u d y d u t s y m f o
. m u H . M , . d P . S i t a i r ti F a n n
A , my co-advisor ,fo rproofreading my t hesis . Iam s
s e n d n i k d n a s n o it s e g g u s r e h r o f l u f k n a h
t tome.
o t s k n a h t t s e n r a e y m s s e r p x e o t t n a w
I alll ecturer sandstaf fo fEngilsh t
n e m t r a p e D s r e tt e
L ,especially fo rmy academic advisor ,Maria Ananta Tr i .
d E . M , . S . S i r a d n a y r u
S It hank herf o rhe rcareand guidanceand I t hank al lo f k
d e r a h s e h t r o f m e h
t nowledgeand expe irencet ha twli lbevery usefulf o rmei n
. e r u t u f e h t
, s t n e r a p d e v o l e b y m o t d e s s e r d d a y lt s o m s i e d u ti t a r g t s e t a e r g y
M Yohane s
o y r u S g n a b m a
B and Yohana Rin iSusan it ,fo rsupporitng me morally and n
a e v o l g n it s a lr e v e r i e h t r o f , y ll a i c n a n
if dcare ,prayer ,guidance ,andatteniton .My
, s r e h t o r b d e v o l e b y m o t o g o s l a s k n a h t g n i m l e h w r e v
o Nicko ,Denni ,sandDeo.
y ll a i c e p s e , 8 0 0 2 h c t a b f o s d n e ir f l l a k n a h t
I Lany ,Yultia ,Erltia ,Dewi ,
, y tt e r G , a i
ii i v
, y r c , r e t h g u a l ,s e ir o t s e h t r o f u o y k n a h T . s r a e y y ti s r e v i n u e h t g n ir u d t r o p p u s d n a
. d e r a h s e w r a e f d n a
t o n n a c s e m a n e s o h w , y d o b y r e v e k n a h t o t e k il d l u o w I , t s a e l t o n t u b t s a L
s i h t h s i n if n a c I t a h t o s r e y a r p d n a t r o p p u s r i e h t r o f , e n o y b e n o d e n o it n e m e b
.s s e n i p p a h d n a , y o j , e c a e p h ti w m e h t t n a r g t s ir h C s u s e J y a M . s i s e h t
x i
S T N E T N O C F O E L B A T
E G A P E L T I
T ... i .... E
G A P L A V O R P P
A ... ii E
G A P E C N A T P E C C
A ... iii A
Y R A K I S A K I L B U P N A U J U T E S R E P N A A T A Y N R E P R A B M E
L ILMIAH
S I M E D A K A N A G N I T N E P E K K U T N
U ... vi E
G A P O T T O
M ... v E
G A P N O I T A C I D E
D ... iv S
T N E M E G D E L W O N K C
A ... iiv S
T N E T N O C F O E L B A
T ... xi E
L B A T F O T S I
L S ... x T
C A R T S B
A ... i....x K
A R T S B
A ... iix N
O I T C U D O R T N I : I R E T P A H
C ... 1 .... .
A Backgroundoft heStudy ...1 .
B ProblemFormulaiton ... 3 .
C Objecitve soft heStudy ...3 .
D De ifniitono fTerm s ...3 W
E I V E R L A C I T E R O E H T : I I R E T P A H
C ... 5 .
A Reviewo fRelatedStudie s...5 .
B Reviewo fRelatedTheo ire s ...7 .
C Theoreitca lFramework ...1 8 I
I R E T P A H
C I :METHODOLOGY ... 02 .
A Objec toft heStudy ...2 0 .
B Approachoft heStudy ...2 0 .
C Methodoft heStudy ...2 1 V
I R E T P A H
C :ANALYSIS ... 52 .
A TheType so fCode-Mixing ... ....2 5 .
B ThePossibleReason so fCode-Mixing ...3 3 .
C Miscellaneou sFinding s ...4 3 V
R E T P A H
C :CONCLUSION ... 9....4 Y
H P A R G O I L B I
B ... 15
S E C I D N E P P
A
x i d n e p p
A 1: Observa itonFormoft heType so fCode-Mixing ... 35 :
2 x i d n e p p
A Observa iton Form o fthe Possible Reason so f Code -g
n i x i
x
E L B A T F O T S I
L S
f o s e p y T e h t f o m r o F n o it a v r e s b O . 1 . 3 e l b a
T Code-mixing ... 22 s
i s y l a n A f o s n o s a e R e l b i s s o P e h t f o m r o F n o it a v r e s b O . 2 . 3 e l b a
T ... 32
e d o C f o s e p y T e h t f o s i s y l a n A e h t f o t l u s e R e h T . 1 . 4 e l b a
T -Mixing ... 62
. 2 . 4 e l b a
i x T C A R T S B A . ) 2 1 0 2 ( . T I K A N I R A W I J U T S A W R A N I N A V E T
S Engilsh – IndonesianCode
-.s t e e w T r i e h T h g u o r h T n e e S s a s r e s U r e tt i w T n a i s e n o d n I y b d e s U g n i x i M a m r a h D a t a n a S , s r e tt e L f o y tl u c a F , s r e tt e L h s il g n E f o t n e m tr a p e D : a tr a k a y g o Y . y ti s r e v i n U e d o
C -mixing i sone o fthe phenomena in socioilnguisitcs .I tnormally t n e r e f fi d m o r f e l p o e P . a i s e n o d n I s a h c u s , y ti n u m m o c l a u g n il it l u m n i s r u c c o u g n a l d n a d n u o r g k c a
b age smay use more than one language in communicaiton . e d o c f o s n o it a t e r p r e t n i g n i v i g t a d e m i a y d u t s s i h
T -mixing in one o f socia -l
, s e ti s b e w g n i k r o w t e
n Twitte.r Thereweresomeelement so fEngilsh which were e e w t e h t n i n a i s e n o d n I f o s t n e m e l e h ti w d e s o p a t x u
j t sposted by Indonesian
.s r e s u r e tt i w T ) 1 ( : e r e w y e h T . y d u t s s i h t n i d e r e w s n a e b o t s n o it s e u q o w t e r e w e r e h T e h t e r a t a h
w type so fcode-mixingusedbyIndonesianTwitter’ suser sasf oundon s t e e w t ri e h
t ? and( 2 )wha taret hepossibler easonsf ort heuseofthecode-mixing r e tt i w T n o ? 0 0 1 m o r f n e k a t e r e w h c r a e s e r s i h t f o a t a d e h
T statuses ,o rusually called
s t e e w
t ,on Twitte rwhichcontained code-mixing betweenEngilsh and I ndonesian e g a u g n a
l posted by1 -9 untli-25-y - earold Indonesian user swho arestudying in ro m o r f d e t a u d a r g e v a
h theuniverstiy .Thecollecteddatawereanalyzedi ndetai land d e if i s s a l
c basedont hechosent heo ires .Inordert oanswert hef ris tproblemoft hi s r e ti r w e h t , h c r a e s e
r used t het heoryoft ype so fcode-mixing by Kachru ( 1982)t o find outt hecode-mixingused by t heTwitter’ suser .sWhlie Hoffmann’ s(1991) ;
s u T d n a a il g i m a s l a C d n a , ) 0 8 9 1 ( s ’ k c a l p o P , ) 4 7 9 1 ( s ’ r a a s k
O ón’ s(1984) ;and
r o e h t ) 7 7 9 1 ( s ’ e r u l C c
M i es a sctied by Hoffmann (1991 :116 )and also Mailk’ s y r o e h t ) 4 9 9 1
( aboutt hereason soft heuseo fcode-mixingwereusedt oanswert he . h c r a e s e r s i h t f o s m e l b o r p d n o c e s e v if d e s u s r e s u r e tt i w T n a i s e n o d n I t a h t d e w o h s y d u t s e h t f o t l u s e r e h T e d o c f o s e p y
t -mixing namely sentence inseriton 1(5 %) ,uni tinseriton (39.9%) , o ll o c d n a m o i d
i caiton inseriton (4.2%) , uni t hyb irdizaiton (3.5%) , and n o it a c il p u d e
r 4(1. % .) I twa salso found t hat t here i sa tendency t o apply vairou s t e e w t e l g n i s a n i s e p y
t .Meanwhlie, t here were seven kind so freason so fcode -y b d e t s o p s t e e w t e h t n i d e r r u c c o g n i x i
m Indonesian Twitte rusers .They were e h t f o d o o m , ) % 6 . 1 1 ( c i p o t r a l u c it r a p a t u o b a g n i k l a t ,) % 2 . 3 2 ( e c n e ir e p x e l a u ti b a h , ) % 2 . 6 ( e s l e y d o b e m o s g n it o u q , ) % 6 . 1 1 ( t n i o p a g n i z i s a h p m e , ) % 6 . 1 1 ( r e k a e p s i s e d s ’ r e k a e p s e h t g n i w o h s d n a g n i h t e m o s t u o b a c it a h p m e g n i e
b re to be wel l
ii x K A R T S B A . ) 2 1 0 2 ( . T I K A N I R A W I J U T S A W R A N I N A V E T
S Engilsh – Indonesian Code
-d e s U g n i x i
M by Indonesian Twi tter User sa sSeen Through Their Tweet .s . a m r a h D a t a n a S s a ti s r e v i n U , a rt s a S s a tl u k a F , s ir g g n I a rt s a S n a s u r u J : a tr a k a y g o Y a y n a s a i b i n i l a H . k it s i u g n il o i s o s a n e m o n e f u t a s h a l a s h a l a d a e d o k r u p m a C tr e p e s l a u g n il it l u m t a k a r a y s a m i d i d a jr e
t iI ndonesia .Orangyangberasa ldairl ata r i r a d h i b e l n a k a n u g g n e m a s i b n a n i k g n u m e k a d e b r e b g n a y a s a h a b n a d g n a k a l e b n a k r a p a m e m k u t n u n a u j u tr e b i n i n a it il e n e P . i s a k i n u m o k r e b m a l a d a s a h a b u t a s o s g n ir a j e j s u ti s u t a s h a l a s i d e d o k r u p m a c i a n e g n e m i s a t e r p r e t n
i sial ,Twitter .
n e m e l e m a l a d n a k p il e s i d g n a y s ir g g n I a s a h a B n e m e l e a p a r e b e b t a p a d r e
T -elemen
m a l a d i d a i s e n o d n I a s a h a
B tweetsyangdtiuil solehpenggunaTwitterI ndonesia. a p a ) 1 ( : u ti a y , i n i n a it il e n e p m a l a d b a w a ji d n i g n i g n a y n a a y n a tr e p a u d a d A u p m a c e p
it rkodeyangdigunakanolehpenggunat witters epe tr iyangt ampakpada s
t e e w
t mereka? dan (2 )apasaja yang mungkin menjad ialasan dar ipenggunaan ? r e tt i w T i d e d o k r u p m a c 0 0 1 i r a d l i b m a i d i n i n a it il e n e p a t a
D tweetsd iTwitte ryang mengandung e d o k r u p m a
c antara Bahasa Ingg ir sdan Bahasa Indonesia d idalamnya ,yang 9 1 a r a t n a a i s u n a g n e d a i s e n o d n I i r a d l a s a r e b g n a y r e tt i w T a n u g g n e p h e l o s il u ti d n a s u l u l n u p u a t a a w s i s a h a m i a g a b e s s u t a t s r e b h i s a m n a d n u h a t 5 2 n a g n e d i a p m a s h a d u s g n a y a t a D . i g g n it n a u r u g r e p i r a
d terkumpu ldianailsa secara deit ldan ir o e t n a k r a s a d r e b n a k i s a k if i s a l k i
d -teor i yang sudah dipiilh . Untuk menjawab e p it i r o e t n a k a n u g g n e m s il u n e p , i n i n a it il e n e p i r a d a m a tr e p n a a y n a tr e
p -itpe
i r a d e d o k r u p m a
c Kachru (1982) untuk mengetahu icampu rkode yang dipaka i ir o e t , u ti a r a t n e m e S . r e tt i w T a n u g g n e p h e l
o -teor idar iHoffmann( 1991) ;Oksaar’ s s u T n a d a il g i m a s l a C , ) 0 8 9 1 ( k c a l p o P , ) 4 7 9 1
( ón (1984) ;dan McClure (1977 )
) 4 9 9 1 ( k il a M i r a d i r o e t a g u j n a d , ) 6 1 1 : 1 9 9 1 ( n n a m f f o H h e l o p it u k i d g n a y i tr e p e s a s a l a i a n e g n e
m n-alasan dar i penggunaan campu r kode digunakan untuk .i n i n a it il e n e p i r a d a u d e k n a a y n a tr e p b a w a j n e m a i s e n o d n I r e tt i w T a n u g g n e p a w h a b n a k k u j n u n e m i n i n a it il e n e p i r a d l i s a H n a p i s i y n e p , ) % 1 5 ( t a m il a k n a p i s i y n e p u ti a y , e d o k r u p m a c e p it a m il n a k a n u g g n e m ( t i n
u 39.9%) ,penyisipan i diom dan kolokas i(4.2% ,) hib irdisas iuni t(3.5%) ,dan 4 . 1 ( i s a k il p u d e
r % .) D isamping tiu ,dtiemukan juga bahwa ada kecenderungan u t a s m a l a d e p it m a c a m i a g a b r e b n a k a n u g g n e m k u t n
u tweet .Sementara tiu ,ada
c n a a n u g g n e p n a s a l a m a c a m h u j u
t ampu rkode yang terdapa tdalam tweet syang , ) % 2 . 3 2 ( n a a s a i b e k n i a l a r a t n a , a i s e n o d n I r e tt i w T a n u g g n e p h e l o s il u ti d r u p m a c a n u g g n e p n a a s a r e p , ) % 6 . 1 1 ( s u s u h k k i p o t u t a u s i a n e g n e m n a a r a c i b m e p t a y n r e p p it u g n e m , ) % 6 . 1 1 ( n a a t a y n r e p h a u b e s n a n a k e n e p , ) % 6 . 1 1 ( e d o
k aanorang
a n u g g n e p n a n i g n i e k n a k k u j n u n e m n a d u t a u s e s p a d a h r e t it a p m e a s a r , ) % 2 . 6 ( n i a l n a s a l a n a d , ) % 5 . 4 ( it r e g n e m i d k u t n u e d o k r u p m a
c -alasanl ain( 31.3% )yangt erdri i i s a s il a n o s r e p i r a
1 I R E T P A H C N O I T C U D O R T N I y d u t S e h t f o d n u o r g k c a B . A r i e h t y l e m a n , s e d o c e r o m r o o w t r e t s a m e l p o e p e r o m d n a e r o m , s y a d a w o N y ti li b a e h t e v a h o s l a y e h T . e g a u g n a l d n o c e s e h t d n a e g a u g n a l e v it a
n to uset hese
y lt n e u lf s e d o
c .The language which i susually mastered wel lby people i sthei r
e u g n o t r e h t o m r i e h t d e s u y lt s ri f m e h t f o t s o M . e g a u g n a l e v it a n r o e u g n o t r e h t o m r i e h t g n ir u d r e v e w o H . y t e i c o s d n a y li m a f r i e h t h ti w e t a c i n u m m o c o t ti w n o it a c i n u m m o
c hothe rpeopleand becauseoft heneedo funderstandingothe r
w o n k r o r e t s a m o t e l p o e p e h t r o f d n a m e d a s i e r e h t , n a e m y e h t t a h w t u o b a e l p o e p e g a u g n a l r e h t o n a n r a e l o t e l p o e p y n a m s e s u a c n o it i d n o c s i h T . s e g a u g n a l r e h t o e h t t a c i n u m m o c r i e h t e k a m o t r e d r o n
i ion more effecitve .Thi salso happen sto the
.l a u g n il it l u m e r a o h w e l p o e p n a i s e n o d n I n n a i s e n o d n I e h t t s a e l t a r e t s a m e l p o e p n a i s e n o d n
I aitonall anguaget hati s
a i s e n o d n
I n and thei r regiona llanguage .Well-educated people usually maste r
s , s e g a u g n a l n g i e r o
f uch a sEngilsh ,Japanese ,French ,Chinese ,etc .Thefactt ha t
r e v e n e h w e d o c x i m o t m e h t s e g a r u o c n e e g a u g n a l e n o n a h t e r o m e s u n a c e l p o e p . e m it e m a s e h t t a e g a u g n a l e n o n a h t e r o m e s u n a c e l p o e p r e d n o w o N . k a e p s y e h t li b e h t r o f e l b i s s o p o s l a s i ti , r e v o e r o
M ingua lo rmulitilngua lpeoplet o usemore
e h t n i e d o c r o e g a u g n a l e n o n a h t e r o m e s u e l p o e p n e h w n o it i d n o c e h T
d e ll a c s i n o it a c i n u m m o c n i e l p o e p r o , t x e t n o c , c i p o t e m a
s code-mixing .The
e d o c f o n o n e m o n e h
p -mixing i s then considered common in biilngua l o r
e d o c d e n if e d ) 5 2 1 : 8 7 9 1 ( n a b a b a N . s e it e i c o s l a u g n il it l u
m -mixing a s“the use o f
. ” e g a u g n a l r e h t o n a n i e c n e t n e s a n i h ti w e g a u g n a l e n o f o s t n e m e l e
e d o
C -mixingoccur sbothi nw irttenandora lcommunicaiton .Code-mixing
, s m a r g o r p n o i s i v e l e t , s m a r g o r p o i d a r n o d n u o f e b n a c e g a u g n a l n e k o p s n i
g n i h c a e
t -learning process ,etc .The code-mixing can also be found in w irtten
e m t e n r e t n i ,s l e v o n , s e n i z a g a m , s r e p a p s w e n n i s a h c u s e g a u g n a
l diaandetc .
e d o c y n a m d n if n a c e w a i d e m t e n r e t n i n
I -mixing ,fo rexample when we
r u o e t a d p u e w n e h w r o , r e g n e s s e m o o h a Y r o k o o b e c a F n o e l p o e p r e h t o h ti w t a h c
y b d e s u s y a w l a s i f l e s ti r e tt i w T . r e tt i w T n o ” s t e e w t “ r u o r o k o o b e c a F n o s u t a t s
a s a e l p o e p y n a
m too lo fcommunicaiton nowadays. I n Twitte rwecan ifndmany
e d o
c -mixing used by the user s in w iritng thei r tweets . Twitte r affect s the
e d o c f o g n i s a e r c n
i -mixing custom in Indonesia too ,especially Indonesian and
h s il g n
E code-mixing .Fromt hoser eason sabove,t hewrtieri si nterestedi n ifnding
e d o c t u
o -mixing t ha toccursi n oneoft hosesocial-networking websties ,which i s
n o it a l u m r o F m e l b o r P . B
t u o b a s i h c r a e s e r s i h
T Engilsh and Indonesian code-mixing used by
n a i s e n o d n
I Twitter’ suser sin wiritng thei rtweets .I ti sbased on the research
: w o l e b s n o it s e u q
.
1 Wha taret hetype so fcode-mixing usedbyI ndonesian Twitte ruser sasf ound
s t e e w t ri e h t n
o ?
.
2 Wha taret hepossibler easonsf ort heuseoft hecode-mixingonTwitter?
t S e h t f o e v it c e j b O .
C u dy
e h t t u o d n if o t s t n a w e h s e s u a c e b h c r a e s e r f o c i p o t s i h t s e s o o h c r e ti r w e h T
e d o c f o s e p y
t -mixing used by Indonesian Twitter users .Besides ,the wrtie ralso
e d o c y h w s n o s a e r e h t t u o d n if o t s t n a
w -mixingareusedi nt hetweets.
s m r e T f o n o it i n if e D . D
: y d u t s t n e s e r p e h t r o f y r a s s e c e n e r a w o l e b s m r e t e h T
.
1 Codei sdeifned a s“Any kind o fsystem t hatt wo o rmorepeopleemployf o r
f o s d n i k e h t d n a , e l y t s , t c e l a i d , e g a u g n a l a o t r e f e r n a c t I . n o it a c i n u m m o c
a v e g a u g n a
l ireites”( Wardhaugh ,2010 :84 .)
.
2 Code-mixing i sdeifned a s“the use o felement so fone language wtihin a
.
3 Socia lnetworking webstie (socia lstie )i san onilne communtiy member s
r o , n o i g il e r , s e i b b o h n i s t s e r e t n i n o m m o c e r a h s y ll a u s u h c i h
w poilitcs .Thi s
d n a s r e b m e m r e h t o f o s e g a p e li f o r p e h t g n i d a e r e d u l c n i y a m n o it a z il a i c o s
( . m e h t g n it c a t n o c n e v e y l b i s s o
p www.whaitssocialnetworking.com)
.
4 Twitteri sasocia lnetworkingand microbloggingservicet ha tallow suserst o
.s e t a d p u t s e t a l r i e h t t s o
p Twitte ri sa real-itme informaiton network tha t
.s w e n d n a , s n o i n i p o , s a e d i , s e ir o t s t s e t a l e h t o t s r e s u s t c e n n o
c An updatei s
1 y b d e ti m
il 40 character sand can be posted through a va irety o fmethods ,
x e t ; e ti s b e w s ’ r e tt i w T g n i d u l c n
i tmessaging ;instan tmessaging ;and thrid
-p o t k s e d y
tr a
p , moblie , and web appilcaitons .
r e tt i w t/ y n a p m o c / m o c . e s a b h c n u r c . w w w // : p tt h
( )
.
5 Tweeti sdeifned a san updatepubilshed by a Twitte ruser . tIi ssimliart o a
a e m e r a s t e e w T . s r e t c a r a h c 0 4 1 n a h t r e g n o l e b t o n n a c t u b , g n it s o p g o l
b nt t o
h ti w s r e s u r e h t o s e d i v o r p h c i h w ” ? g n i o d u o y e r a t a h W ” , n o it s e u q e h t r e w s n a
n o p u w o h s l li w t i ,t e e w t a h s il b u p u o y n e h W . e fi l r u o y t u o b a s e t a d p u k c i u q
n e h w , y lr a li m i S . g n i w o ll o f e r a u o y s r e s u e h t l l a f o s e g a p e m o h r e tt i w T e h t
y , r e tt i w T o t n i g o l u o
y ouwli lseet hemostr ecentt weet soft heuserst ha tyou
( . w o ll o f o t n e s o h c e v a
5
I I R E T P A H C
W E I V E R L A C I T E R O E H T
s e i d u t S d e t a l e R f o w e i v e R . A
e m a s e h t n i s r e h c r a e s e r s u o i v e r p e h t m o r f s e i d u t s e e r h t s e s u r e ti r w e h T
s u o i v e r p e h T . s e i d u t s d e t a l e r r e h s a y d u t s s i h t s a d l e
if studie swere done by )
0 1 0 2 ( o t n a y i
R ,Datu( 2009) ,andSeitawan( 2009 .)
.
1 Code Swtiching Study in Bukan Empa t Mata Ente trainmen t Program )
0 1 0 2 , o t n a y i R (
o t n a y i
R ’ sstudy was t o ifnd ou t(1) t hetype so fcode-swtiching used and )
2
( the reason s why the code- iswtching i s used in Bukan Empa t Mata
m a r g o r p t n e m n i a tr e t n
e .
o t n a y i
R observed three episode so fBukan Empa tMata ,and found 76 e
d o
c -swtiching cases .Hi sstudywa sadescirpitvestudyi n whichqualtiaitvedata .
d e y o l p m e s a w s i s y l a n a
f o g n i d n if e h
T Riyanto’ss tudys howedt hatt herewerethreet ype so fcode -n
i d e r r u c c o h c i h w g n i h c ti w
s Bukan Empa tMata ,namely conversaitona lcode e
l g n i s , g n i h c ti w
s -word code-swtiching and integrated loanwords .He also found h
t ree possible reason so fthe use o fcode-swtiching in the show ,namely topic .
.
2 EngilshCode-Swtichingi nI ndonesianWomanMagazines( Datu ,2009)
u t a
D ’ sobjecitves o fthe study wa sto ifnd ou t(1 )the type so fcode ,
s e n i z a g a m n a m o w n a i s e n o d n I n i g n i h c ti w
s (2 )the possible reason sfo rcode f o n o it a c il p m i e l b i s s o p e h t ) 3 ( d n a , s e n i z a g a m n a m o w n a i s e n o d n I n i g n i h c ti w s
e d o
c -swtiching in Indonesian woman magazine s toward s Engilsh language i
s e n o d n I n i g n i n r a e
l a. Sheconducted adescirpitvestudyand t heapproach o fhe r e
v it a ti l a u q s a w y d u t
s dataanalysis.
e r e w e r e h t t a h t d e w o h s y d u t s e h t f o s g n i d n if e h
T six majort ype so fcode -c i s s o l g i d , y l e m a n s e n i z a g a m n a m o w n a i s e n o d n I e h t n i d e r r u c c o h c i h w g n i h c ti w s
e d o
c - iswtching ,single-word code-swtiching ,phrasecode-swtiching ,clausecode -e
d o c e c n e t n e s e l o h w , g n i h c ti w
s -swtiching and integrated loanword s code -e
d o c r o f s n o s a e r e l b i s s o p r u o f e r e w e r e h t t a h t d n u o f o s l a e h S . g n i h c ti w
s -swtiching
i s s u c s i d r e d n u c i p o t e h t y l e m a
n on,t hewrtie rquote sothers ’expression,f ormaltiy , , g n i n r a e l e g a u g n a l o t s a w n o it s e u q d ri h t e h t r o f r e w s n a e h t e li h W . y c n e i c if f e d n a
e d o c l a c it a m m a r
g -swtiching may suppor t learning bu t ungrammaitca l code -e
s e r e h t ,s e d i s e B . g n i n r a e l t c u rt s b o y a m g n i h c ti w
s arche ralsof ound someEngilsh .
e g a u g n a l n a i s e n o d n I o t d e t p o d a y ll u f e r e w s d r o w
.
3 Code Mixing in Interview Aritcle s Pub ilshed in Popular Indonesian )
9 0 0 2 , n a w a it e S ( e n i z a g a M
e h t y b d e s u g n i x i m e d o c f o s e p y t e h t d e t a g it s e v n i r e ti r w e h t , y d u t s s i h t n I
d n a e l a
e l a m e f d n a e l a m e h t y b d e s s e r p x e g n i x i m e d o c f o e s u e h t n i s e c n e r e f fi d e h T d e n i m a x e o s l a e r e w s e e w e i v r e t n
i .Thewrtie rusedqualtiaitve-descirpitvedata.
n i e l a m e f o w t d n a e l a m o w t e s o h c e
H tervieweesi nf ouri nterview saritcle s n i d e h s il b u
p Popularmagazine .Thenheanalyzedt heanswer soft hei nterviewee s . s n o it s e u q h c r a e s e r e h t f o r e w s n a e h t t u o d n if o t e n i z a g a m e h t n i s e e w e i v r e t n i e h t t a h t d e w o h s s i s y l a n a e h t f o t l u s e r e h T p y t e e r h t d e s
u e so fcodemixing .They areunti i nseriton ,uni thyb irdizaiton ,and e d o c r a li m i s d e s u e l a m e f d n a e l a m t a h t d n u o f o s l a s a w t I . n o it r e s n i e c n e t n e s d i d r e d n e g f o t c e p s a e h t t a h t d e il p m i s i h T . s e c n e r e f fi d t n a c if i n g i s o n h ti w g n i x i m e c n e r r u c c o e h t e c n e u lf n i t o
n o fcodemixing.
s e i d u t s d e t s i x e y d a e rl a e h t p o l e v e d o t s e ir t r e ti r w e h t , y d u t s t n e s e r p s i h t n I o
c nducted by previou s researchers by rtying to use othe r type o f w irtten a , a i d e m t e n r e t n i s e s u r e ti r w e h T . y d u t s e h t f o t c e j b o e h t s a a i d e m n o it a c i n u m m o c a i c o
s l-networkingwebstietobeexac,tt os eewhethe rcodemixingalsooccur sand . g n i x i m e d o c g n i s u r o f s r e s u e h t f o s e v it o m e h t t u o d n if o t o s l a s e i r o e h T d e t a l e R f o w e i v e R . B o t r e ti r w e h t p l e h o t d e s u e b d l u o w t a h t s e ir o e h t e h t s t n e s e r p n o it c e s s i h T , m s il a u g n il i b , e d o c e r a d e t n e s e r p s e ir o e h t e h T . a t a d e h t e z y l a n
.
1 C eo d
9 0 2 : 0 0 0 2 ( h c n i
F -210 )ha sdeifnedcodeasf ollows:
Code i sa system o frule stha tallow speople to give informaiton in t a h t s d r o w f o s t s i s n o c t I . e d o c a s i e g a u g n a l n a m u H . m r o f c il o b m y s c n i r e h t e g o t t u p s i t i n e h W . s t c e j b o d n a , s t n e v e , s a e d i t n e s e r p e
r e train
s i e d o c , s d r o w r e h t o n I . e t a c i n u m m o c o t e l p o e p p l e h l li w t i ,s e c n a t s m u c ri c o t d e s u y ll a c i s a
b conveypeople’si deao rmessage.
r i e h t n e p o e l p o e p n e h W . n o it a c i n u m m o c y r e v e f o e s a b e h t s i e d o
C mouth ,s t hey
h t n o g n i d n e p e d e d o c r a l u c it r a p a e s o o h c t s u
m e need in cetrain cricumstances . . o s g n i o d d i o v a t o n n a c y e h T 9 9 : 6 8 9 1 ( h g u a d r a
W -100 )alsos tatest hat:
, k a e p s o t t u o b a e r a e l p o e p n e h W . e t a c i n u m m o c o t d e s u y ll a r e n e g s i e d o C e h T . g n il e e f f o s d n i m r i e h t s s e r p x e o t e d o c r a l u c it r a p a e s o o h c o t e v a h y e h t it r a
p cula rcode in thi scase can be a paritcula rlanguage ,dialect ,style , t n e r e f fi d e s u y a m e l p o e p , n o it a u ti s y li a d n i , e r o f e r e h T . y t e ir a v r o , r e t s i g e r a e s u o t d e e n y e h t t a h t k n i h t e l p o e p n e h W . s n o it a u ti s t n e r e f fi d n i e d o c r e c h ti w e t a c i n u m m o c o t e d o c n i a tr e
c tain people,t heywli ladjustt het ype h t n o g n i d n e p e d e d o c f
o eneed.
o t e d o c e n o n a h t e r o m e s u o t e l b a e r a o h w e l p o e p y n a m e r a e r e h t y a d o T e t a c i n u m m o
c wtih each other .Therefore , ti i svery possible for t hem t o use t he y li a d r i e h t n i d e r e t s a m y e h t s e d o
c lfiedepending on t he stiuaiton .T his stiuaiton . m s il a u g n il i b d e ll a c n o n e m o n e h p c it s i u g n il r e h t o n a o t s d a e l .
2 Biilnguailsm
l a n o it c n u f e m o s s a h o h w n o s r e p a “ s a l a u g n il i b s e n if e d ) 5 4 : 8 9 9 1 ( y k s l o p S e n o m o r f y r a v y a m y ti li b a s i h T . ” e g a u g n a l d n o c e s n i y ti li b
a biilngualt o another . c h c e e p s o t d e t a l e
b m u n a t a h t d n a n o it c a r e t n i e m a s e h t n i d e s u e b n a c s e d o c t a h t s tl u s e r e h
t e ro f
l a u g n il i b e r a s l a u d i v i d n
i ”. I n sho tr ,biilngual scan choosewhatl anguaget hey are .
e s u o t g n i o g
f o e ri o tr e p e r a e v a h s l a u g n il i b e h T “ s y a s ) 6 4 : 8 9 9 1 ( y k s l o p S , e n il s i h t n I n i a m o
d -relater ule sofl anguagechoice”.I n othe rwords ,biilngual scan varythei r o t r e d r o n i n o it i d n o c d n a n o it a u ti s g n it s i x e e h t t i u s o t e g a u g n a l f o e c i o h c
e m a s e h t n i h ti w s e d o c o w t e t a n r e tl a o t m e h t s d a e l s i h T . y l e v it c e f f e e t a c i n u m m o c
e c n e t n e
s o rcommonlycalled ,codemixing.
.
3 Borrowing
e d o
C -mixing o r code-swtiching i s dfiferent fom borrowing . Grosjean m o r f d e s s a p e v a h t a h t s m r e t o t r e f e r o t ’ g n i w o r r o b e g a u g n a l‘ m r e t e h t s e s u ) 2 8 9 1 (
e H . s l a u g n il o n o m y b n e v e d e s u e b o t e m o c e v a h d n a r e h t o n a o t e g a u g n a l e n o
e h t s e v i
g following example to illusrtate the dfiference he see sbetween cod -e :)
b ( g n i w o r r o b d n a ) a ( g n i h c ti w s
.
a ‘çam ’étonnerai tqu’onai tcode-swtichedautan tqueç ’a .
b ‘çam ’étonnerai tqu’onai tcode-swtichéautan tqueç ’a
) 8 0 3 : 2 8 9 1 n a e j s o r G (
e d o c e w t a h t e v e il e b t ’ n a c I ‘ ( e m a s e h t n a e m s e c n e t n e s h t o
B -swticheda so tfen a s .)
’t a h
t Fo rGrosjean ,borrowingi nvolve smorphologica ladopiton, codeswtiching e
d o c ‘ d r o w e h t ,) a ( e c n e t n e s n I . t o n s e o
e r F a n i m r o f e l p i c it r a
p nch sentence .Meanwhlie ,the word ‘code-swtiché ’i s . y ll a c i g o l o n o h p d n a y ll a c i g o l o h p r o m h c n e r F o t d e t p a d a s i ti e s u a c e b g n i w o r r o b
y b d e ti c s a ) 9 8 9 1 ( z t a h c S o t g n i d r o c c
A Michae lG Clyne in Dynamic so f :
t c a t n o C e g a u g n a
L Engilsh and Immigran t Languages , code-swtiching i s e
l g n i s h t o b r o f d e y o l p m
e -word and mulit-word elements ,borrowingi s ilmtied t o t u b g n i w o r r o b n i y l e k il s i n o it a r g e t n i l a c i g o l o h p r o m d n a l a c i g o l o n o h P . r e m r o f e h t
e d o c n i t o
n -swtiching .Schatzshowst ha tmonoilngual so rbiilngual scan ‘ borrow ’ e
d o c ‘ s l a u g n il i b y l n o t u
b -swtich .’
.
4 Type so fCodeMixing
c it s i u g n il a s i g n i x i m e d o c “ , ) 5 2 1 : 8 7 9 1 ( n a b a b a N o t g n i d r o c c A
n e tf o d n a n o n e m o n e h
p seenamongbiilnguals peakersi nmulitilnguals ociety . tIi s h
ti w e g a u g n a l e n o f o s t n e m e l e f o e s u e h t s a d e n if e
d in a sentence in anothe r .
” e g a u g n a
l Wardaugh( 1992 :106 )alsodeifne s“codemixinga samixo fcodet ha t n
e h w s r u c c
o conversantsuse t wo codes t ogethert ha tchange sfrom one code t o o
w t s e x i m e n o e m o s f i s u h T . e c n a r e tt u e l g n i s a f o e s r u o c e h t n i s r e h t o e h
t codesi n
e d o c s e s u e h t a h t s n a e m t i , e g a u g n a l f o s t n e m e l e r e h t o g n it r e s n i y b e c n e t n e s e n o
. ” g n i x i m
’ g n i x i m e d o c ‘ o s l a ( ’ g n i x i m e d o c ‘ m r e t e h t d e s u e v a h s r e h c r a e s e r e m o S
e d o c ‘ d n
a -mixing’ )to refe rspeciifcally to in rtasentenita lswtiching ,and code n
i h c ti w
s gt or efert oi ntersentenita lswtiching.I nmos tcurrentl tierature ,however , h t o b h ti w , ’ g n i h c ti w s e d o c ‘ h ti w y l b a e g n a h c r e t n i d e s u s i ’ g n i x i m e d o c ‘ m r e t e h t
s m r e
) 9 3 : 2 8 9 1 ( u r h c a
K state sthatt here are ifvet ype so fcodemixing namely n o it a c o ll o c d n a m o i d i , n o it r e s n i e c n e t n e s , n o it a z i d ir b y h t i n u , n o it r e s n i t i n u
n o it a c il p u d e r d n a , n o it r e s n
i . Fu trhe rexplanaiton about t hose ifve t ype so fcode -.
w o l e b d e t n e s e r p e b l li w g n i x i m
.
a UntiI nseriton
Gumperz( 1982 :60 )statest ha tuntii nseritonr eferst ot hei n rtoducitono fa r e h t o n a m o r f e s u a l c t n e d n e p e d d n a , e s a r h p , d r o w s a h c u s , ti n u l a c it a m m a r g
:. g . E . e g a u g n a l
.i Goandge tmycoa tau sdemSchrankda.
g n E ( .’ e r e h t t e s o l c e h t f o t u o t a o c y m t e g d n a o G
‘ ilsh rtanslaiton)
e h T . s e d o c y n a m r e G d n a h s il g n E e h t s e x i m r e k a e p s e h t , e l p m a x e s i h t n I
e s a r h p e h t n i s i h c i h w e d o c y n a m r e G e h t d n a , h s il g n E s i d e s u e d o c n i a m
.) 0 6 : 2 8 9 1 , z r e p m u G ( d e tr e s n i s i l e v e l
.
b Uni tHyb irdizaiton
t n e r e f fi d m o r f ) s e m e h p r o m r o ( s t n e m e l e f o p u e d a m d r o w a s i d ir b y H
s a h c u s , s e g a u g n a
l televsiion (Greek tele “far” plu s Laitn visto “seeing” ) 1
: 1 1 0 2 , t s i u q d r o N
( ) .I ti salso someitme scalled the morphologica ladaptaiton m
a x e r e h t o n A . ) 0 3 1 : 4 0 0 2 , it r a i n r u M
.i Aku bel i HP paviilon mx50 , walau processor- an y Celeron 766 tap i .s
u g a b a y n i s a k if i s e p s
e h t , 6 6 7 n o r e l e C s i r o s s e c o r p e h t h g u o h t n e v e , 0 5 x m n o il i v a p P H t h g u o b I ‘
) n o it a l s n a rt h s il g n E ( ’. d o o g s i n o it a c if i c e p s
l g n E e h t s e x i m r e k a e p s e h t , e l p m a x e s i h t n
I ish andI ndonesian codes .The x
if f u s a i s e n o d n I e h t d n a , a i s e n o d n I s i d e s u e d o c n i a
m – any combinedwtih d e s u e d o c n i a m e h t o t n i d e tr e s n i s i ) r o s s e c o r p ( e d o c h s il g n E e h t
.) 0 3 1 : 4 0 0 2 , it r a i n r u M (
.
c SentenceI nseriton
o r f e c n e t n e s a f o n o it r e s n i n a o t s r e f e r s i h
T m anothe rlanguage into the :.
e .i , ) 9 3 : 2 8 9 1 , u r h c a K ( e s r u o c s i d e h t f o e s a b e g a u g n a l
.i tI l’ lgoi ntot hes amecolumnal e imingmmingngo ijs ia?
h s il g n E ( ’ ? n a e m I t a h w d n a t s r e d n u u o y o d , n m u l o c e m a s e h t o t n i o g l l’ tI ‘
) n o it a l s n a rt
e p s e h t , e l p m a x e s i h t n
I akeri nsetred Engilshsentencei ntot heCantonese . e h t n i s i h c i h w e d o c h s il g n E e h t d n a , e s e n o t n a C s i d e s u e g a u g n a l n i a m e h T
.) 0 0 1 : 8 0 0 2 , n e h C ( d e tr e s n i s i l e v e l e c n e t n e s
.
d IdiomandCollocaitonI nseriton
f o e c n e u q e s a o t r e f e r o t y g o l o c i x e l d n a r a m m a r g n i d e s u m r e t a s i m o i d I
e h t f o s g n i n a e m e h t , t n i o p w e i v c it n a m e s a m o r F . ti n u e l g n i s a s a n o it c n u f
e m m u s e b t o n n a c s d r o w l a u d i v i d n
i d to produce the meaning o fthe i‘diomaitc ’ r o o w t t a h t y a w e h t s i n o it a c o ll o C . ) 9 8 1 : 7 9 9 1 , l a t s y r C ( e l o h w a s a n o i s s e r p x e
, r e d r u m h ti w y a w a t e g , r e tt u b d n a d a e r b “ s e l p m a x e r o f , d e t a i c o s s a e r a s d r o w e r o m
. ) 0 3 : 0 0 0 2 , o d r a tt A & n w o r B ( ” r e p p e p d n a t l a s
h t o n
A e rexampleofi diomandcollocaitoni nseritoni s:
.i ‘Biasal ah ,ngantorninet o ifve’. ’. e v if o t e n i n g n i k r o w m ’ I ,l a u s u s A ‘
.i
i ‘Wasitng itmebange tnih’. ’ . e m it g n it s a w y ll a e r s i tI
‘ (Engilsh rtanslaiton)
ti r w e h t , e l p m a x e t s ri f e h t n
I e rinsetred the idiom “nine to ifve” which s
n a e
m a job wtih norma l dayitme hours . Meanwhlie , in the second h
s il g n E n a , e l p m a x
e collocaiton “wasitng itme” wa sinse tred into the .
e c n e t n e s n a i s e n o d n I
.
e Redupilcaiton
g n it a e p e r f o s s e c o r p e h t s i n o it a c il p u d e r f o s s e c o r p e h
T thesamemeaning :.
e .i , ) 9 3 : 2 8 9 1 , u r h c a K ( s e d o c o w t n i
.i Parov ,sorry.
a m a l s i B d n a e d o c h s il g n E e h t s e t a c il p u d e r r e k a e p s e h t , e l p m a x e s i h t n I d n a ) h s il g n E ( y r r o s , e d o
c parov(Bislama) .Both word sactually havet he e
m a
s meaning .Themaincodei sBislama ,andt heEngilshcodei si nsetred .) 6 2 2 : 7 0 0 2 , m o rt s d n i L ( .
5 Reasonsf o rCodeMixing
5 1 1 : 1 9 9 1 ( n n a m f f o H o t g n i d r o c c
A -116 ) swtiche s may occu r when c a f f o k c a l f o e s u a c e b e b n a c t I . c i p o t r a l u c it r a p a t u o b a g n i k l a t s i e n o e m o
s litiyi n
. s n o it a t o n n o c s u o ir a v f f o r e g g ir t s m e ti n i a tr e c e s u a c e b r o r e t s i g e r t n a v e l e r e h t g n i e b r o , e s l e y d o b e m o s g n it o u q s i t c e j b u s e h t e s u a c e b e r a s n o s a e r e l b i s s o p r e h t O . n o it it e p e r r o n o it c e jr e t n i f o m r o f e h t n i e b n a c t i ; g n i h t e m o s t u o b a c it a h p m e c ti w
S hingmayalsos howst hes peaker’ sdesriet obewel lunderstood.
s u T d n a a il g i m a s l a C d n a , ) 0 8 9 1 ( k c a l p o P , ) 4 7 9 1 ( r a a s k
O ón( 1984 )a sctied e d o c “ t a h t t s e g g u s o s l a ) 6 1 1 : 1 9 9 1 ( n n a m f f o H y
b -swtiching i salso used to h ti w y ti r a d il o s d n a … y ti t n e d i p u o r g s s e r p x
e suchagroup” .Hoffmannalso ctied e d o c “ t a h t ) 7 7 9 1 ( e r u l C c M m o r f t n e m e t a t s e h
t -swtiche sare o tfen used wtih the . ” r o t u c o lr e t n i e h t r o f t n e t n o c h c e e p s e h t g n i y fi r a l c f o n o it n e t n i k o o b r e h n i ) 4 9 9 1 ( k il a M y b d e s o p o r p s n o s a e r r e h t
O Socio-ilnguisitcs :A y
d u t
S o fCode-swtichingarel ackoff aclitiy,l ackofr egister ,moodoft hespeaker , y ti t n e d i w o h s o t , e c n a c if i n g i s c it n a m e s , e c n e ir e p x e l a u ti b a h , t n i o p a e z i s a h p m e o t t c a rt t a o t d n a , s n o s a e r c it a m g a r p , e c n e i d u a t n e r e f fi d s s e r d d a o t , p u o r g a h ti w r u F . n o it n e tt
.
a Lackoff aclitiy
r o n o i s s e r p x e e t a ir p o r p p a n a d n if t o n n a c r e k a e p s a n e h w s n e p p a h t I r a l u c it r a p e h t e v a h t o n s e o d n o it a s r e v n o c f o e g a u g n a l e h t n e h w r o m e ti y r a l u b a c o v n o y r r a c o t d e d e e n d r o
w the conversaiton smoothly .In accordance wtih thi s . n a i s e n o d n I n i s d r o w t n e l a v i u q e f o k c a l e h t o t d e t a l e r s i n o s a e r s i h t , h c r a e s e r e r a h c i h w s n o i s s e r p x e h s il g n E l a u ti b a h e h t o t s r e f e r o s l a t i , e r o m r e h tr u F n o it a u ti s d n a t x e t n o c e m o s n i d e s u y l n o m m o
c s inI ndonesia.
.
b Lackofr egister
o w t n i t n e t e p m o c y ll a u q e t o n s i r e k a e p s a h c i h w n i n o it i d n o c e h t s i t I n I . s e g a u g n a l o w t n i s m r e t e h t w o n k t o n s e o d r e k a e p s e h t n e h w d n a , s e g a u g n a l e r o , s r e y w a l ,s r o t c o d f o h c e e p s e h t n i s r u c c o n e tf o t i ,s n o it a p u c c o n i a tr e
c ngineer s
s m r e t r e p o r p e m o s t a h t t c a f e h t f o e s u a c e b s e v l e s m e h t g n o m a t c a r e t n i y e h t e li h w . e l b a li a v a e b t o n y a m h s il g n E n a h t r e h t o e g a u g n a l r e h t o y n a n i .
c Moodoft hes peaker
e d o c , y r g n a r o d e ri t e r a s l a u g n il i b n e h w y ll a u s u t a h t s m i a l c ) 4 9 9 1 ( k il a M g n i h c ti w
s take splacewtihanewdimension.I tmeanst ha twhen t hespeakeri si n s n o i s s e r p x e h s il g n E n i a tr e c d n if y l s u o e n a t n o p s n a c e h s / e h , d n i m f o e t a t s n i a tr e c . g n il e e f r e h / s i h t n e s e r p e r t a h t .
d Toemphasizeapoint
o t n i o p n i a tr e c e z i s a h p m e o t d e s u o s l a s i g n i h c ti w
.
e Habtiua lexpeirence
d e x if n i s r u c c o n e tf o g n i h c ti w s e d o c “ t a h t t c a f e h t s tr e s s a ) 7 1 : 4 9 9 1 ( k il a M
n i ,t s e u q e r d n a s d n a m m o c , g n it r a p d n a g n it e e r g f o s e s a r h
p vtiaiton ,expression so f s n o i s s e r p x e e h t e s u a c e b h c ti w s e d o c e l p o e P ” .s r e k r a m e s r u o c s i d d n a , e d u ti t a r g
. e fi l y li a d n i e c n e ir e p x e l a u ti b a h a n e e b e v a h d e s u
.f Semanitcs igni ifcance
f o n o it p e c r e p s ’t n a p i c it r a p n o s d li u b t a h t e c r u o s e r e v it a c i n u m m o c a s i t I l o w
t anguages .I tmay also servea san i mpilci tpurposewhich i sonly known by .
n o it a m r o f n i c if i c e p s n i a tr e c n i s r e k a e p s r a l u c it r a p
.
g Tos howi denttiywtihagroup
s t n a r g i m m i n a il a tI t a h t s tr o p e r ) 4 9 9 1 ( k il a M n i d e ti c s a ) 7 7 9 1 ( o rt e i P i D
g n E n i e k o j a l l e t d l u o
w ilsh andgivet hepunch ilnei n tIailan ,no tonlybecausei t e m a s e h t o t g n o l e b l l a y e h t t a h t t c a f e h t w o h s o s l a t u b n a il a tI n i d i a s r e tt e b s a w
.s e c n e ir e p x e d n a s e u l a v d e r a h s h ti w , p u o r g y ti r o n i m
.
h Toaddres sadfiferen taudience
r e k a e p s e h t n e h w d e s u s i t
I intend sto addres s people from va irou s .s
d n u o r g k c a b c it s i u g n il
.i Pragmaitcr easons
e e r g e d t n e r e f fi d a s i e r e h t e s u a c e b s n e p p a h g n i h c ti w s e h t , e s a c s i h t n I
. e e s s e r d d a e h t o t t c e p s e r w o h s o t d e s u s i g n i h c ti w s s i h T . s r o t u c o lr e t n i n e e w t e
e n a v a J a , e l p m a x e n
a sestuden twho wast alkingt o hisf irendsi n Javanese ,when r e d r o n i n a i s e n o d n I o t n i e g a u g n a l e h t d e h c ti w s e h s u p m a c t a r e r u t c e l s i h o t g n i k l a t . e ti l o p e r o m e b o t
.j Toatrtac tatteniton
d o c , ) n e tt ir w d n a l a r o n i h t o b ( t n e m e s it r e v d a n i t a h t s w o h s ) 4 9 9 1 ( k il a M . s r e n e t s il r o s r e d a e r f o n o it n e tt a t c a rt t a o t d e s u s i g n i h c ti w s t i f I . n o it a u ti s l a m r o f n i n i s n e p p a h g n i x i m e d o c , e m it e h t f o t s o M “ o t e c n a r e tt u r o d r o w e l b a ti u s o n s i e r e h t e s u a c e b s i ti , n o it a u ti s l a m r o f n i s n e p p a h g n i e b s i h c i h w e g a u g n a l a n i ti y a
s used”( Nababan ,1984 :32 .)
.
6 Languageandt heI nternet
e g n a h c l a i c o s f o x e d n i e v it i s n e s a h c u s g n i e b e g a u g n a L
“ … .Languagei s a y ll a e r s i t e N e h T ‘ . y ti v it c a r e t n i s i y ti v it c a t e N r o f , t e n r e t n I e h t f o t r a e h e h t t a s r e t u p m o c f o r e b m u n t s a v a r e h t e g o t s k n il h c i h w m e t s y
s and t hepeoplewho use m
e h
t ’( Naughton ,1999 :40 )… .TheI nterneti snotj us tat echnologicalf ac;t tii sa k c o t s f e i h c s ti d n a , t c a f l a i c o
s - ni -rtadei sl anguage”( Crystal ,2001 :237 .)
s i t e n r e t n I e h t f o n o it a c i n u m m o c e h t , ) 8 3 2 : 1 0 0 2 ( l a t s y r C o t g n i d r o c c A i n o it a t p a d a c if i c e p s f o s t e s y b d e z ir e t c a r a h
c n graphology ,grammar ,semanitc , h t o t , e s r u o c s i d d n
a eproperite soft het echnologyandt heneed soft heuse .r
t e n r e t n I e h t f o s e r u t a e f e g a u g n a l d e k r a m e r t s o m e h t f o e n O / n o it a i v e r b b a f o s e p y t s u o ir a v f o e s u e h t s i , k a e p s t e N s a n w o n k , n o it a c i n u m m o c o r c
n e v e n a f o n o it u l o v e e h t d e t a v it o m s a h , y g r e n e d n a e m it f o l a e d t a e r g a g n i v a s d n a r o s d r o w o t d e t c ir t s e r r e g n o l o n e r a s m y n o r c a e h T . e g a u g n a l d e t a i v e r b b a e r o m e c n e t n e s e b n a c t u b , s e s a r h p t r o h
s -length :CIO [‘Check i tou ’t] ,GTG [‘Go tto e e r h t r o o w t o t d e c u d e r e b n a c s d r o w l a u d i v i d n I . ] ’ n o i n i p o y m n I ‘ [ O M I , ] ’ o g e k il e r a e m o S . ] ’ r e v e t a h w ‘ [ E W , ] ’ s k n a h t‘ [ X T r o X H T , ]’ e s a e l p ‘ [ S L P : s r e tt e l a f o e l b a ll y s a s a s t c a l a r e m u n r o r e tt e l e h t f o e u l a v d n u o s e h t t a h t n i , s e s u b e r m o c e r a r o , d r o
w binaiton so frebu sand lette riniital :L8R [l‘ater’] ,CU [‘See e c a F ‘ [ F 2 F , ] ’ u o
y - oT -Face’] . However ,there mus tbe a seirou s ilmi tto the k s ir l a e r a d n a , n o it a i v e r b b a g n i s u d e y e v n o c e b n a c h c i h w n o it a m r o f n i f o t n u o m a 4 8 : 1 0 0 2 , l a t s y r C ( y ti u g i b m a f
o -86 ,229-230 ,237-238) .
k r o w e m a r F l a c it e r o e h T . C r e ti r w e h t , h c r a e s e r s i h t f o m e l b o r p t s ri f e h t r e w s n a o t r e d r o n
I used t he
e d o c f o s e p y t f o y r o e h
t -mixingbyKachru( 1982)t o ifndoutt hecode-mixingused r e tt i w T e h t y
b user .s
e li h
W Hoffmann’ s (1991) ; Oksaar’s (1974) , Poplack’ s (1980) , and s u T d n a a il g i m a s l a
C ón’ s(1984) ;and McClure’ s(1977 )theori es a sctied by k il a M o s l a d n a ) 6 1 1 : 1 9 9 1 ( n n a m f f o
H ’ s(1994 )theoryaboutt her eason soft heuse e
d o c f
o -mixingwli lbeusedt oanswert hes econdproblem soft hisr esearch.
e d o c f o s e p y t e v if e r a e r e h t ) 9 3 : 2 8 9 1 ( u r h c a K o t g n i d r o c c a , t s ri
F -mixing .
h t i n u , n o it r e s n i t i n u e r a y e h
e r a e r e h t , d n o c e
S twelvepossibler eason swhichwli lbeusedt oexplaint he h
s il g n
E -Indonesiancode-mixingusedbyI ndonesianTwitte rusersi npositngt hei r e
h T . s t e e w
t twelve possiblereason sare :( 1) talking abou ta paritcular t opic ,(2 ) e h t s w o h s d n a g n i h t e m o s t u o b a c it a h p m e g n i e b ) 3 ( , e s l e y d o b e m o s g n it o u q
p
s eaker’ sdesrie to be wel lunderstood (Hoffmann ,1991 :115-116) ,(4 )expres s d n a a il g i m a s l a C d n a , ) 0 8 9 1 ( k c a l p o P , ) 4 7 9 1 ( r a a s k O ( y ti r a d il o s d n a y ti t n e d i p u o r g
s u
T ón (1984 )a sctied by Hoffmann ,1991 :116) ,and (5 )clarfiying the speech r
e t n i e h t r o f t n e t n o
c locuto r(McClure ,1977 a sctied by Hoffmann ,1991 :116 ) . e h t l l a e s u t o n l li w r e ti r w e h T . ) 4 9 9 1 ( k il a M y b d e s o p o r p e r a s n o s a e r r e h t O
e s u a c e b k il a M y b d e s o p o r p s n o s a e
r thereare some reason swhich are simliar t o e
h t f o e m o S . n a m f f o H y b d e tr e s s a s n o s a e r e h
t reasonsf rom Mailk (1994 )which , t n i o p a e z i s a h p m e o t ) 7 ( ,r e k a e p s e h t f o d o o m ) 6 ( e r a h c r a e s e r s i h t n i d e s u e b l li w
t n e r e f fi d s s e r d d a o t ) 0 1 ( , e c n a c if i n g i s c it n a m e s ) 9 ( , e c n e ir e p x e l a u ti b a h ) 8 (
t n e tt a t c a rt t a o t ) 2 1 ( d n a , s n o s a e r c it a m g a r p ) 1 1 ( , e c n e i d u
a i on.
d e s u s i ’ g n i x i m e d o c ‘ m r e t e h t t a h t ) 2 1 5 : 6 0 0 2 ( n a it o o h a M y b d e t a t s s A
, ’ g n i h c ti w s e d o c ‘ h ti w y l b a e g n a h c r e t n
i fort hepresen tstudy ,code-mixing wli lbe .
0 2
I I I R E T P A H C
Y G O L O D O H T E M
s i h t d n a , y d u t s s i h t t c u d n o c o t y g o l o d o h t e m n i a tr e c a d e s u r e h c r a e s e r e h T
r e t p a h
c provides t heapproach oft hestudy and t he descirpiton oft he procedure s
.s i s y l a n a a t a d f o s d o h t e m e h t d n a n o it c e ll o c a t a d n i d e s u
.
A Objec toft heStudy
e h
T objec to fthe study w as the sentence sused in the status ,o rusually
d e ll a
c tweets ,w irttenbyt heuser so fas ocial-networkingwebstie ,Twitte.r
.
B Approachoft heStudy
b o r e ti r w e h
T served code-mixingon Twitte randi twa ssrtongly r elated t o
s e i d u t s s c it s i u g n il f o d l e if a s i s c it s i u g n il o i c o S . s c it s i u g n il o i c o
s which t irestosee
e n n o c e h
t citon between l anguageand society ,and t heway weuse ti i n dfiferen t
.s n o it a u ti s l a i c o s
r e ti r w e h
T chosequaltiaitve-explanatory method because thegoa loft hi s
e d o c e s u n e tf o e l p o e p y h w s n o s a e r e h t n i a l p x e d n a t u o d n if o t s a w h c r a e s e
r
-c i n u m m o c n i g n i x i
m aitng wtih the others .The approach o fthi sresearch wa s
s e r e v it a ti l a u
q earch because thi s research aimed to acqurie an in-depth
.
C Methodoft heStudy
.
1 Popula itonandSample
.
a Popula iton
p e h
T opulaiton of t hestudy was t het weetsposted by Indonesian Twitte r
h s il g n E d e n i a t n o c h c i h w s r e s
u – Indonesiancode-mixingint heris entences.
.
b Sample
o S . g n il p m a s e v i s o p r u p d e s u r e ti r w e h
T t hesampleoft hestudy consisted
f
o 1 00statuses, o rusuallycalledt weets ,onTwitterwhich containedcode-mixing
a i s e n o d n I d n a h s il g n E n e e w t e
b n language .Thewrtie ralso ilmtiedt heageandt he
d e s u y l n o r e ti r w e h T . c if i c e p s e r o m t i e k a m o t s r e s u e h t f o d n u o r g k c a b n o it a c u d e
d o c d e n i a t n o c s t e e w t e h
t e-mixing which were posted by 1 -9 untli-25-y - earold
n a i s e n o d n
I user swhoarestudying ni o rhavegraduated f romtheuniverstiy. The
e s o h c r e ti r
w thi sdatabecausemanyofI ndonesian Twitte ruser so tfen mixe dtwo
d n a h s il g n E ( s e g a u g n a
l Indonesian )in w iritng thei rtweets ,especially the user s
. d n u o g k c a b n o it a c u d e d n a e g a n i a tr e c m o r f e m a c o h w
.
2 Instrument sandDataCo lleciton
.
a Instrument s
e r o f e r e h t ,r e h c r a e s e r e h t s a w t n e m u rt s n i n i a m e h t , h c r a e s e r e v it a ti l a u q n I
the main insrtumen tfor t hi sresearch was the wrtie rherse .fl The wrtie rd id no t
a t a d r o e c r u o s e h t n i a g o t s e ri a n n o it s e u q y n a d e e
k r a m d n a d a e r r e ti r w e h t e s u a c e
b e d the data taken from a social-networking
. e ti s b e
w The wrtie rdid al lthe data colleciton and data analysi sby using the
d n a ) 2 8 9 1 ( u r h c a K y b d e s o p o r p g n i x i m e d o c f o s e p y t f o y r o e h
t also Hoffmann’ s
s u T d n a a il g i m a s l a C d n a , ) 0 8 9 1 ( s ’ k c a l p o P , ) 4 7 9 1 ( s ’ r a a s k O ; ) 1 9 9 1
( ón’ s(1984) ;
r o e h t ) 7 7 9 1 ( s ’ e r u l C c M d n
a i aes sctiedbyHoffmann ( 1991 :116) ,and also t heory
) 4 9 9 1 ( k il a M m o r
f aboutt her eason soft heusingo fcode-mixing.Theexampleo f
. w o l e b n w o h s s a w a t a d n i a t b o o t s n a e m e h t
. o
N Tweets Type so fCode-Mixing I
U U H S I I CI R
f o s e p y T e h t f o m r o F n o it a v r e s b O . 1 . 3 e l b a
T Code-mixing
I
U =UntiI nseriton H
U =Uni tHyb irdizaiton I
S =SentenceI nseriton I
C
. o
N Tweets PossibleReasons 1
0 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 1 0 1 1 1 32 1
s i s y l a n A f o s n o s a e R e l b i s s o P e h t f o m r o F n o it a v r e s b O . 2 . 3 e l b a T
1
0 =Talkingabou taparitculart opic 2
0 =Quoitngs omebodyelse 3
0 =Being emphaitc abou tsomething and showst he speaker’ sdesrie t o e
b wel lunderstood 4
0 =Expres sgroupi denttiyands oildartiy 5
0 =Clarfiyingt hes peechcontentf ort hei ntelrocutor 6
0
