Translation Techniques and Readability of Indonesian Captions of Breaking News Posts on Badmintalk_Com's Instagram
Abstract
With the wider range of humans accessing various information and entertainment on social media, translation is increasingly important in the cyber world to make information easier for people with different language backgrounds to process. Subsequently, @badmintalk_com's caption on breaking news posts furnished both the English and Indonesian languages. Human involvement in translating can reduce or eliminate the result of an awkwardly translated text. The research uses the theories of Molina and Albir to determine and find the translation techniques in the data and Nababan’s to assess the translation quality in terms of readability. Through the qualitative descriptive methodology, the result found that there are 8 out of 18 translation techniques proposed by Molina and Albir (2002), with the frequent in detail as follows: Amplification 16 (25.8%), Reduction 12 (19.3%), Literal Translation 11 (17.8%), Transposition 7 (11.3%), Borrowing 6 (9.7%), Generalization 5 (8.1), Particularization 4 (6.4%), and Description 1 (1.6%). Therefore, the readability assessment shows that out of sixty-two pieces of data obtained, 52 were counted as readable with a percentage of 83.9%, less readable (16.1%), and no data is considered unreadable
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References
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DOI: https://doi.org/10.24853/elif.6.2.129-138
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