TRANSLATION SHIFT AND ACCURACY OF NOUN PHRASE IN INSTAGRAM CAPTION TRANSLATION

Abstract

Noun phrase is used when a single word is not enough to describe a noun. Ambiguity and mistranslation might happen in noun phrase translation that needs different structure depending on two languages. This research has purposes to find out the translation shifts that occur on noun phrase in Instagram caption translation, to reveal the translation techniques applied in translating noun phrase from ST to the TT and to assess the translation accuracy of noun phrase in TT from the ST. The theories used in this research are Catford’s theory of translation shift, Molina and Albir’s theory of translation technique, and translation accuracy in Nababan et al TQA (Translation Quality Assessment). This research is descriptive qualitative research. The data of this research are 125 noun phrases from Instagram caption and their translation into Indonesian. Questionnaire is also distributed to three raters as the data of this research. The analysis shows that there are six kinds of translation shift in translating the data; intra-system shift is 32% (40 data), structure shift is 22.4% (28 data), unit shift is 20% (25 data), level shift is 9.6% (12 data), none shift is 8.8% (11 data), and class shift is 7.2% (9 data). There are 9 translation techniques used; literal translation is 42.40% (53 data), borrowing technique is 20.80% (26 data), establish equivalent is 16.80% (21 data), calque is 7.20% (9 data), discursive creation and reduction each are 4.80% (6 data), linguistic compression is 1.60% (2 data), and linguistic amplification and transposition each are 0.80% (1 datum). In term of translation accuracy, 66 data are accurate with 58.20%, 27 data are less accurate with 21.60%, and 32 data are inaccurate with 25.60%.

Keywords: noun phrase, translation shift, translation technique, translation accuracy, Instagram caption translation.