Sunday, 29 October 2017

MT Performance in Translation Literary Text from English into Indonesian: Comparing Two Machine Translation

MT Performance in Translation Literary Text from English into Indonesian: Comparing Two Machine Translation

Choirul Fuadi
Yogyakarta State University
Choirul.fuadi2015@student.uny.ac.id

Anisa Nur’aini
Yogyakarta State University
anisanicha@gmail.com

Riyan Nuari
Yogyakarta State University
riyannuarii@gmail.com

Abstract: Since world war, machine translation has been developed and used in translation of text. By the emergence of technology, machine translation (MT) has shown good improvement toward many researches. Generally, there are two kinds of machine translation, known as free source and commercial machine translation. The using of machine translation as assistance for translation is very helpful for translator. The MT able to translate many genres of text, literary text included. In particular study, it aimed to present the machine translation performance in translation of literary text. Google Translate as free source MT and Memsource as commercial MT were used in this article. The two systems were compared by translation of famous novel, The Al Chemist by Paulo Coelho. The data took randomly though stratified sampling and there were 1330 words length and 84 segments. In the analysis of data, SAE J2450 by SAE was used as guideline of the study. The Indonesian version of The Al Chemist Novel (Sang Al Kemis) was used as the reference translation. The findings, Google Translate has 43 errors and the error weight of Google translate is 7.7 %. Meanwhile Memsource has 61 errors and the error weight of Memsource is 9.8%. Both Memsource and Google, Miscellanous error and Misspelling are by far the most commonly attested error type in the output of translation literary text. The errors of Miscellanous error involved literal translation. The error of misspelling involved the violation the concept of target language. It might be happen because the literary language is ‘special’ kind of language; different to the 'ordinary' language (Eagleton, 2003:4).


Keywords: Machine Translation, Literary Text,


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artikel ini telah dipersentasikan pada seminar nasional penerjemahan 2017. Prodi Sastra Inggris, Universitas Sanata Dharma.

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