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Contact Name
Widyashanti Kunthara Anindita
Contact Email
wk.anindita@gmail.com
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+6289612007317
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Jl. Raya Palur Km. 5 Surakarta Ngringo Jaten Karanganyar Jawa Tengah Jurug, Ngringo, Kec. Jaten, Jawa Tengah 57731
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INDONESIA
Surakarta English and Literature Journal
Published by Universitas Surakarta
ISSN : 26219077     EISSN : 26219085     DOI : 10.52429
The aim of SELJU is to provide a venue for academicians, researchers, and practitioners for publishing original research articles or review articles. The scope of the articles published in this journal deals with a broad range of topics such as Linguistics, Translation, Literature, and another section related to contemporary issues in the English Language.
Articles 1 Documents
Search results for , issue "Vol 9, No 1 (2026): February" : 1 Documents clear
The Slang Translation of Game “Honkai : Star Rail” by Mihoyo Widiyantari, Yunita; Himawan Satria Sakti, Dyanizieus
Surakarta English and Literature Journal Vol 9, No 1 (2026): February
Publisher : University of Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52429/selju.v9i1.155

Abstract

Slang, or colloquial language, is a linguistics phenomenon that often occurs in daily conversations. It is spread into content across various forms of entertainment media such as music, memes, and games. The study analyzes the use of slang in the translation of the game titled “Honkai: Star Rail.” It is a qualitative research with Triangulation data employed to validate the data by using raters. The translation quality was analyzed in terms of accuracy, acceptability, and readability. The results show that the accuracy of 80.25% data is classified as Accurate; 18.52% data is classified as Less Accurate; and only 1.23% is classified as Not Accurate. The acceptability results show that 83.95% data is classified as Acceptable; 16.5% data is classified as Less Acceptable; and none with a score of 1 that is considered as Not Acceptable. Meanwhile, the readability results show that 85.19% data is classified as Highly Readable; 12.35% data is classified as Moderate Readable; and 2.46% data is classified as Low Readable. The score of the translation quality indicates that the translators successfully provided the best equivalent for the translations of this game in those three translation quality aspects.

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