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, 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
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
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 .
) 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
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.
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 ,on Twitterwhich 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 =moodoft hes peaker 7
0 =emphasizeapoint 8
0 =habtiua lexpeirence 9
0 =s emanitcs igniifcance 0
1 =addres sdfiferen taudience 1
1 =pragmaitcr easons 2
1 =atrtac tattenit on 3
.
b DataColleciton
e h
T techniquesi ncollecitngt hedatausedi nt her esearchwere:
.
1 Recording 01 0 tweets which contained the code-mixing o f Engilsh and
a i s e n o d n
I n languagerandomly.
.
2 Catego irzing the type sof code-mixing tha toccu rin the data based on the
. y r o e h t
.
3 Finding to u thepossibler eason so feveryt weetstha thadbeenr ecordedwhich
n i a t n o
c thecodemixingo fEngilshandIndonesian language.
.
3 DataAnalysis
, h c r a e s e r s i h t n
I the t echnique o fdataanalysi swa sexplanatory analysis .
r e h c r a e s e r e h
T ’ sgoa lo fthi sresearch wa sto ifnd ou tthe types o fcode-mixing
r e tt i w T n i d e s
u and explain the reason swhy people o tfen use code-mixing in
s r e h t o e h t h ti w g n it a c i n u m m o
c .The co llected data were analyzed in detai land
d e if i s s a l
c based on the chosen theory . Finally , the wrtie r explaine d some
5 2
V I R E T P A H C
S I S Y L A N A
e r p r e t p a h c s i h
T sent sthe research resutls .This chapte ri sdivided into e
e r h
t secitons ,namely the type so fcode-mixing ,the possible reason so fcode s
g n i d n if s u o e n a ll e c s i m d n a g n i x i
m which occurred in the tweet s posted by n
a i s e n o d n
I Twitte ruser .s
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 by 1 -9 untli-25-y - earold Indonesian user swho arestudying ni ro r
g e v a
h aduatedf romtheuniverstiy .
.
A TheType so fCode-Mixing
e d o c f o s e p y t e h t d e z ir o g e t a c r e ti r w e h t , h c r a e s e r s i h t n
I -mixing based on
y b d e tr e s s a y r o e h t e h
t Kachru (1982) . The type s are uni t inseriton , uni t 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 collocaiton inseriton , and
n o it a c il p u d e
r .
n o it a v r e s b o e h t n i d e t n e s e r p d n a d e z y l a n a n e e b d a h h c i h w a t a d e h t m o r F h t , m r o
f ewrtie rcouldi nformt hatf rom100t weet swhichhadbeengathered,t here e
d o c f o s e s a c 3 4 1 e r e
e l p m a x e e m o s e r e w e s e h
T s o funi tinseriton code-mixing case sin the tweet s :
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 t s o p
. a Word
e d o c n o it r e s n i ti n u e h t n i s d r o w h s il g n E e h
T -mixing weremoslty conten t
s a h c u s s d r o
w nouns ,verbs ,adjecitves ,and adverbs .However ,the wrtie ralso .s
n o it a m a l c x e e m o s d e s o p a t x u j o s l a s r e s u r e tt i w T e h t t a h t d n u o f
) 1 Noun
r e e n i g n
E bjiaksana itdakmemintal emburt ap idimintal embu .r( 69)
(Translaiton:Awiseenginee rdoe sno task t oworkovetrimebuti sasked t o ).
e m it r e v o k r o w ) 2 V erb
h s a w n i a r
B dulu,bia rkejranyapenuhdgi ntegrtias.( 57)
(Translaiton:Brainwashf ris,ts o Icanworkwtihf ulli ntegrtiy). )
3 Adjecitve a ti k u a l a
K awaresm ilngkunganbaka ladabanyaki nsprias idimana2ygbaka l a
ti
k temui.( 35)
(Translaiton: I fwe are aware o fthe envrionment ,there wli lbe plenty o f d
n if l li w e w t a h t n o it a ri p s n
i everywhere).
)
4 Adverb y ll a n i
F ...nyampekon rtakanj g.( 72)
)
5 Exclamaiton ti
h
S ,barui nge tlag ikalopulsakuhabis.( 83)
(Translaiton:Shi!tIj ustr ememberedt ha t Iamou to fmyphone’ scredti).
.
b Phrase
Thewrtie ralsof ound t hatt heTwitte ruser salso j uxtaposedsomeEngilsh s
t e e w t ri e h t n i s e s a r h
p . Some of t he phrases t ha twere found werenoun phrase s .s
e s a r h p b r e v d n a
)
1 NounPhrase ,r e tl a w a m a s r e
B loca lyouth.( 8)
(Translaiton:[ Iam ]WtihWatler ,al oca lyouth). )
2 VerbPhrase
Sebabmimpiinurusanakademi si scallednightmare .(13)
(Translaiton:Becausedreamingabou tacademict hingsi scallednightmare).
.
c Dependen tClause
d n a t s t o n n a c t u b , b r e v a g n i o d t c e j b u s a e v a h s e s u a l c t n e d n e p e D
e t a n i d r o b u s a e v a h y e h t e s u a c e b e c n e t n e s e t e l p m o c a e m o c e b d n a y lt n e d n e p e d n i
. e s u a l c e h t f o t n o r f n i n o it c n u j n o
c In thi sresearch ,the wrtie ralso found some e
d o c e s u a l c t n e d n e p e d d e n i a t n o c h c i h w s t e e w
)
1 Keitka itdak ada1 alatpunygbisadigunakan ,pakaliahotakmu ,andi tw s ,ork .
e c i
n (55)
(Translaiton:Whent herei snothingyoucanuse ,useyou rbrainandi tworks . ).
e c i N )
2 Ternyatamemangs emuabelumt entus esua idgr encanaygktiabuat .Butf atih r
e g n o rt s s u s e k a
m .(89)
(Translaiton: Apparenlty everything doe sno talway sgo according to the ).
r e g n o rt s s u s e k a m h ti a f t u B . e k a m e w t a h t s n a l p
.
2 Uni tHyb irdizaiton t
i n
U hyb irdizaiton i s the combinaiton o f element s o rmorpheme s o f n i s e s a c n o it a z i d ir b y h t i n u f o s r e b m u n l a t o t e h T . d r o w a s s e r p x e o t s e d o c t n e r e f fi d
s e s a c 5 e r e w 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 t s o p s t e e w t e h
t (3.5 %) .Thesewere
t a z i d ir b y h t i n u f o s e l p m a x e e m o
s ioncase susedbyI ndonesianTwitte rusers: .
a Coldplaydipute rkapanpungloomy-n yasamaaja.( 5)
(Translaiton:[Song sby ]Coldplayarealway sgloomywhenevert heyarebeing ).
d e y a l p .
b Jangan men-judge kalo cewe merokok tuhh naka!l!mungkin saja karna k
o k o r e
m dyb smendpatknberbagaii nsprias!i!!(65)
(Translaiton:Donotj udgeagri lwho smoke sa sabadgilr !Shemayge tal o t )
.
c Waktuuntuk itdur .Me-restartpikrianuntukhar iesokyangl ebihbaik.( 77) (Translaiton:I’t sitmet os leep .Restar tmymindf o rabettert omorrow).
e h t t a h t n e e s e b d l u o c t i , e v o b a n o it a z i d ir b y h t i n u f o s e l p m a x e e h t m o r F
s e x if f a n a i s e n o d n I h ti w d e t a r g e t n i e r e w s d r o w h s il g n
E ,andinsetredi nt hemiddle
h c a e f
o sentences. In the example (a) ,the Engilsh word “gloomy” i scombined “
x if f u s n a i s e n o d n I e h t h ti
w -nya”t oproducet heword“gloomy-nya” .Whliei nt he x if e r p n a i s e n o d n I e h t h ti w d e n i b m o c s i ” e g d u j “ d r o w h s il g n E e h t , ) b ( e c n e t n e s
e m
“ (n)-“t o produce t heword “me(n)- uj dge” .Finally, t heEngilsh word “restatr” n
a i s e n o d n I e h t h ti w d e n i b m o c s
i preifx“ em - o“ t producet heword“me-restatr”i n .)
c ( e l p m a x e e h t
.
3 SentenceI nseriton
e h t o t n i e g a u g n a l r e h t o n a m 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
i d e h t f o e s a b e g a u g n a
l scourse .Fromt hedata,i tcouldbeconcludedt ha tsentence .)
% 1 5 ( s e c n e r r u c c o 3 7 h ti w e p y t t n e u q e r f t s o m e h t s a w n o it r e s n
i Example sare
: w o l e b d e d i v o r p
.
a Selama tpagi ,penjelajah !Weareallt raveler sofl fie.(32)
(Translaiton :Goodmorning ,explorers !Weareal l rtaveler sofl fie). .
b Tiadahairt anpas ambal .HowI r eallyl oveI ndonesia !(53)
(Translaiton :Nodaywtihou tchiils auce .HowI r eallyl oveI ndonesia!) .
c Ygs aba.rGodknowst hebes!t(94)
o t m o i d i t a h t d e s u r e s u r e tt i w T a , e v o b a e l p m a x
e expres shi sfeeilng tha tthe
a w d a h e h e g a s s a
m spainfu lbu tatfert ha thi sbodywouldf ee lbette .r
.
b Collocaiton e k a
M jersey barca keililng mailo bener2 menairk perhaitan banyak orang . Sampebuleajapayatteniton.( 66)
(Translaiton :Weairng a Barcelona jersey to walk around Mailoboro really n
e v E . e l p o e p y n a m f o n o it n e tt a e h t s t c a rt t
a foreigner spayattenitont .) o ti
o t g n i d r o c c A . n o it a c o ll o c a s i e v o b a e l p m a x e e h t n i d r o w d e n il r e d n u e h T
y r a n o it c i D s ’ r e n r a e L d e c n a v d A d r o f x
O 7th Ediiton (2005 ,84) ,the co llocaiton r e tt i w T a , e v o b a n o i s s e r p x e e h t n I . y ll u f e r a c g n i k o o l s n a e m e v o b a ” n o it n e tt a y a p “
r e s
u sharedhe rexpe irencewhens heworeaBarcelonaj erseyandmanyf oreigner s d
e k o o
l carefullyati .t
.
5 TranslatedRedup ilcaitono fMeaning g n it a e p e r s n a e m n o it a c il p u d e
R wordsi n t wo dfiferen tcode swhich have g
n i n a e m e m a s e h
t . From t he data which had been gathered ,redupilcaiton code -.)
% 4 . 1 ( s t e e w t 2 n i d e r r u c c o g n i x i
m Thoset weet sareprovidedbelow: .
a Senang. Happy! Meilhatmu antusia s sekail pag i ini . Hidupmu terilha t !
k a h A . h a ri a g r e
b )( 1
(Translaiton :Happy .Happy![ I ]Saw you veryexctiedt hi smorning .Yourl fie d
e m e e
.
b Puj iTuhan.. .praiset heLord..!.!!(64)
(Translaiton :Praiset heLord…Praiset heLord…! )
e h t n
I example sabove ,the Twitte ruser sredupilcated the Engilsh code s s
d r o w e h t ,) a ( e l p m a x e e h t n I . s e d o c n a i s e n o d n I d n
a “senang” (Indonesian )and
) h s il g n E ( ” y p p a h
“ actuallyhavet hes amemeaning .Redup ilcaitonalsooccurredin )
b ( e l p m a x e e h
t .The expression “Puj iTuhan” (Indonesian )and “Praise the .
g n i n a e m e m a s e h t e v a h o s l a ) h s il g n E ( ” ! d r o L
.
B ThePos isbleReason so fCode-Mixing
e d o c f o s n o s a e r e h t d e z ir o g e t a c r e ti r w e h t , h c r a e s e r s i h t n
I -mixing based
y b d e tr e s s a s e ir o e h t e h t n
o Hoffmann (1991) ;Oksaar (1974) ,Poplack (1980) , s
u T d n a a il g i m a s l a
C ón ( 1984) ;and McClure( 1977 )a sctiedbyHoffmann ( 1991 : .
) 4 9 9 1 ( s ’ k il a M o s l a d n a ) 6 1
1 Thosereason saret alking abou ta paritculart opic , 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 , e s l e y d o b e m o s g n it o u
q thespeaker’ s
e h t g n i y fi r a l c , 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 , d o o t s r e d n u l l e w e b o t e ri s e d
e e p
s ch conten tfo rthe intelrocutor ,mood o fthe speaker ,emphasize a point , 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 cance ,addres sdfiferen taudience ,pragmaitc ,s
n o s a e
r andatrtac tatteniton.
t m o r
F hoser eason ,st hewrtierf oundt hatt hereweres everalr eason swhich d i d s n o s a e r e m o s t u b , s r e s u r e tt i w T n a i s e n o d n I y b n e tt ir w s t e e w t e h t n i d e t a n i m o d
. e s a c s i h t n i r u c c o t o
n Thewrtie ralsof ound t ha tsomet weet shad moret hanone e
d o c f o s n o s a e
r -mixing .In thi sresearch ,the wrtie ralso found othe rreason so f e
d o
s g a
t tohelp Twitte randt hei ruserst ounderstandwhati shappeningi n t hewo lrd , m r e t e h t e b ir c s e d o t m r e t t c a x e n a e v a h t o n d i d e g a u g n a l n a i s e n o d n I e s u a c e b
. ” c i p o T g n i d n e r T “
.
2 QuoitngSomebodyElse e d o c f o n o s a e r s i h
T -mixing wa sproposed by Hoffmann (1991 :115- 11 6 .) 2
. 6 t u o b
A % o fthe case so fcode-mixing had been catego irzed a sthi sreason . :
e r a s e l p m a x e e h t f o e m o S
.
a Ment hinkcanbej udgedbyhi swordss eleciton.Kataahl ikomunikasi.( 20) (Translaiton : Men think can be judged by hi s word s seleciton . A communicaiton sexpetrs ays).
.
b Dan cm satu cowok yg bliang 'enjoy you rvacaiton! Aku msh b snahan u
u m a k , u t a s a m u c . .. h h a a a ' k o k n e g n a
k .( 99)
(Translaiton :Andt herei sonlyamanwhosaid ,“Enjoy you rvacaiton ! Ican u
o y g n i s s i m t o n d n a t
s .”Ah,t herei sonlyone,t hati syou).
d e t o u q r e s u r e tt i w T e h t , e l p m a x e t s ri f e h t n
I a statemen t by a
n o it a c i n u m m o
c exper twhich wa sstated in Engilsh .A sthe compensaiton ,the d n o c e s e h t n i e li h W . e c n e t n e s n a i s e n o d n I n a h ti w t i d e s o p a t x u j r e s u r e tt i w T
e c n e t n e s e h t , e l p m a x
e “Enjoy you rvacaiton!” i squoted by a Twitte ruse rfrom r
p r e h o t e c n e t n e s t a h t d i a s o h w e n o e m o
s eviously .Quoitng somebodyelsecould e n o e m o s y b d e t a t s y l e n i u n e g e r e w s t n e m e t a t s e h t t a h t n o i s s e r p m i n i a tr e c a e v i g
, h c r a e s e
r thewrtie rfound 11.6 % case swhich were catego irzed ast hemood o f .
r e k a e p s e h
t Theseweres omeoft heexample: .
a Senang. Happy! Meilhatmu antusia s sekal i pag i ini . Hidupmu terilha t !
k a h A . h a ri a g r e
b )( 1
(Translaiton :Happy .Happy ![I ]Saw you very exctied thi smorning .You r ).
e t a n o i s s a p y r e v d e m e e s e fi l .
b makasihbua tsupportnya , 'Imnots ad,j ustsediki tgalau.( 39)
(Translaiton :Thankyouf ort hes uppor.tI ’mnots ad,j us tal tiltebi tconfuse).
a e v o b a s e c n a r e tt u e h
T rei ncluded i nt hemood oft hespeake rbecauset he e h t , e l p m a x e t s ri f e h t n I . n o i s s e r p x e l a n o s r e p a s s e r p x e o t s i h s il g n E o t n i g n i x i m
r e h w o h d e w o h s y lr a e l c t I . ” ! y p p a H “ n o i s s e r p x e e h t y b d o o m s i h g n it a t s t c e j b u s
s a w g n il e e
f . I n t hesecondexample, t heTwitte ruse ralso swtiched t heexpression o
t d e t n a w d n a m i h d e tr o p p u s o h w e s o h t d e k n a h t e H . g n il e e f s i h w o h s o
t expres s
. d a s t o n s a w e h t a h t
.
5 EmphasizeaPoint
c r o f e r o m d d a o t d n a s s e rt s e v i g o t s m i a g n i h c ti w s e h t , e s a c s i h t n
I et ot he
e d o c e m o s d n u o f r e ti r w e h t , h c r a e s e r s i h t h ti w e c n a d r o c c a n I . t n e m e t a t
s -mixing
n o s a e r s i h t o t d e r r e f e r h c i h w s e s a
c .The tota lpercentage o fcode-mixing case s t
a c e r e w h c i h
w ego irzedi nt hisr easonwa s11.6 .% Hereares omeexamples” .
a Kalaub sskip har ikhususnyad rhar iminggukmrn .Seriously. ( 6)
(Translaiton : Iwish Icould skip the days ,especially since las tSunday . ).
.
a Selamatt anggalnyaktia,s elama thairr ayamul elakiku !Mis sus obad! (70) (Translaiton :Happy anniversary !Happy feast ,my man ![I ]Mis syou so
) ! d a b .
b Ididn' tknow why I loved the Indonesian Ido lLas tnight ,especially the .
a k i d u J t f n a e S f o e c n a m r o f r e
p Behnendangbgt.( 100)
(Translaiton : Ididn' tknow why Iloved the Indonesian Ido lLas tnight , tf
n a e S f o e c n a m r o f r e p e h t y ll a i c e p s
e . Judika.Wow!I ’tsr eallykick!)
e m o
S Engilsh expression such a s“[I] mis syou so bad” in the example t a g n a s u k A “ y a s o t d r a w k w a d n a e g n a rt s ti d n if e l p o e P . d n u o f y l n o m m o c s i e v o b a
. ” u m a k u d n
ir Some Indonesian shardly say t hi sexpression t o othe rpeople .The i
d n u o f y l n o m m o c t o n s i n o i s s e r p x
e n r eall fieandusually i sonlyf oundi npoems , s
e ir o t s r o , s g n o s e v o
l .Therefore ,Indonesian people ,especially the youngsters , n
o i s s e r p x e h s il g n E e s u o t d n e
t toexpres sherf eeilng a s tii smoreconvenien tand .r
e tt e b g n il e e f r e h s e b ir c s e d t
i Atl eas tpeopledono t ifnd tisrtangetosay “ Imis s c
t e , ” u o y e v o l I “ , ” u o
y . Meanwhlie ,in the second example ,the twee tcontain s .
n o i n i p o l a n o s r e p
, d n o c e
S some people may code-mix because by mixing two o rmore t
i ,s e d o
c give sapersonan educatedexpression.Maste irngt wol anguage so rmore .t
i o d o t e l b a e l p o e p e m o s y l n o d n a y s a e t o n s
i Mos tofI ndonesianpeoplewhoare r
e t s a m o t e l b
a other language ,in thi scase Engilsh ,are those who are well -d
e t a c u d
.
a Lag i bebere s kama r dan farewell sama beberapa barang lama , siap n
i a l g n a r o e k n a k s a p e l e
m .( 61)
(Translaiton : Iam cleaning up my room and saying afarewell t o someold )
. e s l e e n o e m o s o t m e h t e v i g o t y d a e r ,s g n i h t .
b Brainwashdulu,bia rkejranyapenuhdgi ntegrtias.( 57)
(Translaiton:Brainwashf ris,ts o Icanworkwtihf ulli ntegrtiy).
.
C Miscellaneou sFindings
g n ir u
D analyzing the data ,the wrtie rfound othe rinteresitng ifnding s n
o it s e u q h c r a e s e r o w t e h t o t s r e w s n a e h t s e d i s e
b s. Howeve,r t he wrtie rwli lno t
. h c r a e s e r r e h tr u f d e e n l li t s y e h t e c n i s s g n i d n if e s e h t t u o b a h c u m n i a l p x e
.
1 TheTendencyt oApplyVairou sTypesi naSingleTweet
e d o c d e t n u o c r e ti r w e h
T -mixing based on the existence o fthe foreign d e n i b m o c e r e w h c i h w , s t n e m e l e e g a u g n a l h s il g n E e s a c s i h t n i ,s t n e m e l e e g a u g n a l
, t e e w t e l g n i s a n i h ti w t a h t d e il p m i a t a d e h T . s t n e m e l e e g a u g n a l n a i s e n o d n I h ti w
e r e h
t couldbemoret han oneuni toft hej uxtaposedelemen twtihvairousl engths . e n o n a h t e r o m e b d l u o c e r e h t , e c n a r e tt u e l g n i s a n i h ti w t a h t d e m u s s a r e ti r w e h T
e d o c f o e p y
t -mixingasi tcouldbeobservedf romt heexamplebelow:
.
a UntiI nseriton - IdiomandCo llocaitonI nseritonCode-Mixing t
s a e l t
A udahgaoverheat ilag.( 4)
d r o w e h t h ti w d e n i b m o c s a w ” t s a e l t a “ n o it a c o ll o c e h t , e l p m a x e e h t n I
. ” t a e h r e v o “
.
b UntiI nseriton- SentenceI nseritonCode-Mixing d
j i n i a y n s u r a
H 5th anniversary..Ah tap i sudahlah.. 'Im happy wtihou t e
r o f e b n a h t r e i p p a H .. m i
h .(31)
(Translaiton :I tshould be t he 5th anniversary .Ah ,but i ’t sokay .I’m happy m
i h t u o h ti
w ,happiert hanbefore).
, e l p m a x e e h t m o r
F untii nseritoncouldbeidenitifedbyt heexistenceo fan 5
“ e s a r h p n u o n h s il g n
E thanniversary” .Whereast heEngilsh sentence“I’mhappy n o it r e s n i e c n e t n e s o s l a s a w e r e h t t a h t d e l a e v e r ” e r o f e b n a h t r e i p p a h , m i h t u o h ti w
e d o
c -mixing.
.
c Uni tHyb irdizaiton- SentenceI nseritonCode-M xi gi n t
a u b h i s a k a
m supportnya , 'Imnots ad,j ustsediki tgalau.( 39)
(Translaiton :Thankyouf ort hes uppor.tI ’mnots ad,j us tal tiltebi tconfuse).
d n a ” tr o p p u s “ d r o w h s il g n E f o n o it a n i b m o c e h t s i ” a y n tr o p p u s “ d r o w e h T
“ x if f u s n a i s e n o d n
I -nya” and i ti sa uni thyb irdizaiton code-mixing .Thi suni t e
d o c n o it a z i d ir b y
h -mixing wa scombined wtih sentence inseriton code-mixing , d a s t o n m ’ I “ e c n e t n e s h s il g n E e h t f o e c n e t s i x e e h t y b d e if it n e d i e b d l u o c h c i h w
.
d SentenceI nseriton- IdiomandCollocaitonI nseritonCode-Mixing s
y a w l a s
A ,t ahunbarus elaludatar2aja ,happynewyea rall! (45)
(Translaiton :A salways ,tii salway sa lfa tnewyear .Happynewyea ral!l)
e d o c f o s e p y t o w t e r a e r e h t , e v o b a e l p m a x e e h t n
I -mixing whichcould be
h t e r a y e h T . d e if it n e d
i e co llocaiton “a salways” and the sentence “Happy new .
” !l l a r a e y
.
e Uni tInseriton - Sentence Inseriton - Idiom and Co llocaiton Inseriton Code -Mixing
n u R n ' ti
H ... .Selalukykgt.. .Sorry.. . Idon tmeant ohti' nr un .(27)
(Translaiton :Hi tandrun . tIi salway silket hat .Sorry . Idon’ tmeant ohi tand ).
n u r
e d o c f o s e p y t e e r h t d e n i a t n o c e l p m a x e e h
T -mixing .Thef ris tonewasuni t n a e m t ’ n o d I “ h ti w n o it r e s n i e c n e t n e s s a w e n o d n o c e s e h T . ” y r r o s “ h ti w n o it r e s n i
s a w e n o t s a l e h T . ” n u r d n a t i h o
t idiom and collocaiton inseriton wtih “hi tand .
” n u r
.f UntiI nseriton - Uni tHyb irdizaiton- SentenceI nseritonCode-Mixing a
c a b h u r u s i d y k i K g n a r o e s a g a t s
A an Eng ilsh nove lbergenre ROMANTIC -Y
D E M O
C begini?Youarekliilngmes oflty.(76)
(Translaiton :Oh my god !Someone ilke Kiky i sasked to read an Engilsh c
it n a m o r s i e r n e g h c i h w l e v o
.
b "anak sekarang in i pergaulan nya lain.." « overheard two grannie s n
it t a h c ti h
c ga tbees' .(30)
(Translaiton :“Today’ skid shave dfiferen tway o fsociailzing.” Overheard .s
'e e b t a g n it t a h c ti h c s e i n n a r g o w
t )
d e k r a m e r t s o m e h t f o e n o n e e b s a h s m y n o r c a / n o it a i v e r b b a f o e s u e h T
. n o it a c i n u m m o c 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 In t hefris texample above, t he
e s u r e s u r e tt i w
T d thel ette r“N” t o replace t heword “and” ,“ur”t o representt he d
n a , ” r u o y “ d r o
w thel ette r“r” t o replacetheword “are”which i suncommon i n d
r a d n a t
S Engilsh .Thesekinds o facronym sarecalled rebuse ,s i n t hat t he sound f o s n o it a n i b m o c e r a r o , d r o w 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
.l a it i n i r e tt e l d n a s u b e r
e h T . t e e w t e h t n i s i s p il l e n a d n u o f r e ti r w e h t , e l p m a x e d n o c e s e h t n I
e t o r w e r e h r e s u r e tt i w
T “overheard t wo grannie schtichatitng a tbees'”i nstead o f o
I
“ verheardt wogrannie swerechtichatitnga tbees'”.I nt hi sexample,t heTwitte r h
t t u o t f e l r e s
u e subjec t“I” and also the be “were” . However ,atlhough some f
o t u o t f e l e r a s d r o
w thesentencebutt hes entencecans tli lbeunderstood.
s s e n e u q i n u r e h t o n a d n u o f o s l a r e ti r w e h t , h c r a e s e r s i h t n
I t shat i
t a h w e k il t s u j , h s il g n E d r a d n a t S n i n o m m o c n
u wa sw irtteni nt heexamplebelow:
k u s a m h ti L n a V i d a m u c # , h
E Trending Topic Indonesia . todays' genera iton i s e
v it c a y ll a r e tt i w
t ya!( 91)
(Translaiton :Wow !#cumadiVanLtih i san Indonesian Trending Topic .Today’ s )
h c i h w ” y ll a r e tt i w t “ d r o w e h t d n u o f r e ti r w e h t , e v o b a t e e w t e h t n
I h asno t
t s i x
e e dint hedicitonaryyet .tIs eemst hatt heuse rhadmadeupanewwordwhich d
n a ” r e tt i w t “ d r o w e h t m o r f d e m r o f e r e
w thes ufifx“ally”,j us t ilkei nothe rword s ,
y ll a c i n o rt c e l e , y ll a n o it i d d a s a h c u
9 4
V R E T P A H C
N O I S U L C N O C
t a h t d n u o f s a w t i , n o it a l u m r o f m e l b o r p t s ri f e h t o t d e t a l e
R from100t weet s
, d e z y l a n
a therewere 143 case so fcode-mixing a sonet wee tcould contain more
e d o c e n o n a h
t -mixing. The ifnding so fthi sresearch showe d tha tIndonesian
f o s e p y t e v if e s u y e h T . s e d o c h s il g n E d n a n a i s e n o d n I d e y o l p m e s r e s u r e tt i w T
y l e m a n g n i x i m e d o
c sentencei nseriton 1(5 %) ,untii nseriton (39.9%,) i diomand
n o it r e s n i n o it a c o ll o
c 2(4. %) ,uni thyb irdizaiton 5(3. %) ,andr edupilcaiton 4(1. % .)
d n u o f o s l a r e ti r w e h
T thet endencyt oapplyvairoust ypesi nas inglet weet ,
s a h c u
s untii nseriton- idiomandcollocaitoni nseritoncode-mixing ,untii nseriton
- sentence inseriton code mixing ,uni thyb irdizaiton - sentence inseriton code
, g n i x i
m sentence inseriton - idiom and collocaiton inseriton code-mixing ,uni t
n o it r e s n
i - sentencei nseriton - idiom and collocaiton i nseriton code-mixing ,u tni
n o it r e s n
i - uni thyb irdizaiton - sentencei nseritoncode-mixing.
n o it a l u m r o f m e l b o r p d n o c e s e h t h ti w g n il a e
D aboutt hepossibler eason so f
e d o
c -mixing, i twasf ound t hatt herewereseven kind sofr eason so fcode-mixing
.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 t s o p s t e e w t e h t n i d e r r u c c
o They were hab tiua l
e c n e ir e p x
e (23.2% ,)t alking abou taparitculart opic( 11.6%) ,moodoft hespeake r
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 e z i s a h p m e , ) % 6 . 1 1
( %) , being
d s ’ r e k a e p s e h t 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
3 . 1 3 ( s n o s a e r r e h t o d n a , ) % 5 . 4
( % )which consist so fpersonailzaiton ,giving an
e r p x e d e t a c u d
e ssion ,andalsor andomands pontaneou sproces .s
,s g n i d n if l u f g n i n a e m g n ir e v o c s i d d n a a t a d g n i z y l a n a r e tf
A the wrtie r
e m o s e v i g o t e k il d l u o
w suggesitons ot othe rresearcher swho are interested in
e d o
c -mixingphenomenaandalso t o I ndonesian peoplei ngenera land I ndonesian
r a l u c it r a p n i s r e s u r e tt i w
T .
y a m s r e h c r a e s e r r e h t o , e n o e l a c s l l a m s a s a w h c r a e s e r t n e s e r p s i h t e c n i S
e d o c n o y d u t s t c u d n o
c -mixing in wide rscope using more va irou skind s o f
e c r u o
s s ,etihe rw irtten o rspoken ,wtih more sample .s The researcher smay also
e d o c a f o e g a t n a v d a s i d d n a e g a t n a v d a e h t e z y l a n
a -mixingphenomenon .
o w r e ti r w e h t , n o it i d d a n
I uld ilket osuggestt hatI ndonesianpeopleshould
g n i h c ir n e r o f e c n a l a
b thei rEngilsh vocabulaire sand excelilng t hei rEng ilsh ,and
e h t e c u d e r t o n l li w t i o s , n a i s e n o d n I n i s d r o w n i a tr e c f o e c n e l a v i u q e e h t g n i w o n k
. n a i s e n o d n I n i s d r o w e h t f o y ti r a il i m a f
y ll u f e p o
H , the ifnding soft he presen tstudy could be usefuli n having an
d o c f o e c n e t s i x e e h t t u o b a t h g i s n
i e mixing among Indonesian people and thi s
S
E
C
I
D
N
E
P
3 5
: 1 x i d n e p p
A Observa itonFormoft heType so fCode-mixing
. o
N Tweets Type so fCode-Mixing
I
U U H S I I R CI
.
1 Senang . Happy! Meilhatmu antusia s
u m p u d i H ! 9 ) ´' ? `' ? ( . i n i i g a p i l a k e s
! k a h A . h a ri a g r e b t a h il r e t
.
2 Semanga t ya @yoeilu s yang akan
didada rsiang in.i..We love you! !! We
u o y r o f g n it i a
w calon sajrana!! !Do the t
s e
b yakkohhh..;. )
.
3 udahj alans etengahdanThi sConneciton
.. . d e ts u r t n U s
i |: .
4 atl eastudahgaoverheatlagi: D
.
5 coldplay dipute rkapan pun gloo -myn ya
( a j a a m a
s - - )"
.
6 Kalau b sskip har i khususnya d rhar i
. n r m k u g g n i
m Seriously..
.
7 Apply thi sgolden rule sto every aspec t
: e fi l r u o y f
o jangan melakukan hal2 yg n a k u k a l n i a l g r o n i g n i k a t u m a k
? . . u m a d a p
.
8 Bersamawatler,loca lyouth..
.
9 selama tpagil agi ,hairi n i Iwon' tgiveup
i g a
l ):
. 0
1 Wha t happen wtih people today? !!
a u m e
S sensiitve,s akti ,marah2 ..: (
. 1
1 Sejahat2nya bandung pd saya , tetep
. a tr a k a j g n i d n a b i d k i a b h i b e
l Sincerely ,
p m a s m l
b er mhkrnmacet: (
. 2
1 Astaga, , in i pub ilc lecture kurang
. . a a y h a l n i g n a r u
k
. 3
1 sebab mimpiin urusan akademi s i s
e r a m t h g i n d e ll a
