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Revealing Translation Techniques Applied in the Translation of Batik Motif Names in See Instagram

Bibliographic Data

ID21708780
AuthorsDyah Raina Purwaningsih (0009-0005-6557-6638, Jenderal Soedirman University), Ika Maratus Sholikhah (Jenderal Soedirman University), Erna Wardani (Jenderal Soedirman University)
Year2020
Volume19
Issue2
Pages287
Publication date2020-07-15
Open AccessYes
TypeARTICLE
VenueCelt A Journal of Culture English Language Teaching & Literature (JOURNAL)
Journal identifiersISSN: 1412-3320 • E-ISSN: 2502-4914
PublisherSoegijapranata Catholic University (PUBLISHER • ID)
DOI10.24167/celt.v20i1.2090
OpenAlexW4247155312
LanguageEN
Citations received1
References cited4

This article discusses one of the forms of machine translation, the Instagram translation feature called “see translation”. The research is focused on the translation techniques applied by the machine in translating Banyumas batik motifs from Indonesian to English found in @batikantodjamil and @batk_rd. This topic is worth discussing since machine translation is now getting more developed and is projected to replace human translator. However, in some cases, for example in dealing with culturally-bound terms, machine translation cannot perform contextual knowledge as well as the human translator. this mini research was conducted by applying qualitative research with purposive sampling technique in which the researchers obtain the data by selecting two batik center Instagram accounts containing batik motif names in the captions. The result shows that there are three translation techniques applied by the Instagram translation features, namely literal, borrowing, and particularization. The most dominant technique to use is borrowing technique, and it shows a tendency that such cultural terms in the source language do not have one-to-one correspondence in the target language. In other words, the touch of human translator is very important in the post-editing process of translation by machine to make the translation more acceptable. However, if it is impossible to involve human translator, the Instagram administrator should enrich the machine with more contextual linguistic database to provide the users with better translation results

Dynamic and formal equivalence · Example-based machine translation · Indonesian · Linguistics · Literal translation · Machine translation · Machine translation software usability · Natural language processing · Nonprobability sampling · Sociology · Source text · Target text · Computer Science · English Language Learning and Teaching · Language Acquisition and Education · Linguistics and Language Analysis · Artificial Intelligence

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  • Research Methodologies in Translation Studies

    Gabriela Saldanha, O''Brien et al.•Research Methodologies in…•2014

  • The Theory and Practice of Translation

    Eugene A Nida, Charles R Taber•The Theory and Practice of…•1982

  • Research methodologies in translation studies

    Callum Walker•Perspectives•2015

  • Translation Techniques Revisited

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Citations per year0.5
Citation span2024 - 2024 (1)
Highly citedNo

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