Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Journal of Korean Applied Linguistics
Intan Mutiara Hapsah
Universitas Pendidikan Indonesia
Education Languange, Linguistic, Communication & Media

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Korean Applied Linguistics

 1 
Translation shift of translation Webtoon Nae Aidineun Gangnammiin (내 Id 는 강남미인) into I Am Gangnam Beauty Intan Mutiara Hapsah
Journal of Korean Applied Linguistics Vol 3, No 2 (2023): Journal of Korean Applied Linguistics
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jokal.v3i2.37636

Abstract

Translation is one of the branches of applied linguistics as part of activities in communication between people with various languages. The results of this translation activity are then called translation. However, in every activity, there must be obstacles as well as the translation process. This research discussed the translation shift that occurred in the translation of the webtoon Nae Aidineun Gangnammiin into I Am Gangnam Beauty. The purpose of this research is to present the results of the translation shift analysis of both the text and dialogue that occurs in the I Am Gangnam Beauty webtoon according to its type, and the results of the analysis of the translation stage of the I Am Gangnam Beauty webtoon using the theory of Nida and Taber. The data was collected by noting any translation shift found and then grouping them according to their type and stage of translation. The results showed that the most significant translation shift was skewing of information as much as 37 data (41%), gain of information as much as 29 data (32%), and loss of information as much as 24 (27%). Then the translation stages where the most translation shifts were found were the analysis of 40 data (45%), the transfer of 35 data (39%), and the restructuring of 14 data (16%).
Co-Authors