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ANALYSIS OF GOOGLE TRANSLATE’S QUALITY IN EMPLOYING TRANSLATION TECHNIQUES

ELT Forum: Journal of English Language Teaching · Vol. 7 No. 1 (2018) · pp. 40–49

DOI
10.15294/elt.v7i1.25304
ISSN
2721-4532, 2252-6706
Published
2018-08-30
Publisher
English Department, Faculty of Languages and Arts, Universitas Negeri Semarang
Language
eng

Abstract

This research focused on the analysis of translation techniques and translation quality of Jakarta Post’s articles in terms of accuracy, acceptability, and readability. The objectives of this research were to find out the translation techniques applied by Google Translate in translating the articles of Jakarta Post and to know the quality of translation by Google Translate. This research applied a descriptive qualitative method. The data were obtained by using content analysis and questionnaire. The data in this research were ten articles of Jakarta Post from opinion section. The other data were the results of the translation quality assessments done by the respondents. The research findings showed that Google Translate applied 9 translation techniques. They were reduction, established equivalent, literal, calque, amplification, transposition, linguistic amplification, linguistic compression, and borrowing technique. The results of the questionnaires showed that the percentage of accuracy was 57.1% with average score 2.5, the percentage of acceptability was 58.6% with the average score 2.5, and the percentage of readability was 63.7% with the average score 2.5. Based on the results obtained, the quality of translation results by Google Translate was less accurate, less acceptable, and less readable. According to the analysis, it can be concluded that calque technique had the best translation quality considering this technique got the highest score in every aspect. While reduction technique was the least because this technique got the lowest score in every aspect. The researcher suggested the users to translate simple sentence instead of a complex one to gain a better quality of translation using Google Translate.

Collaboration network of the authors

17 authors · 23 co-authorship links

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Co-authorOrganisationJoint articles
Jimmi JimmiAffiliation unknown1
Ari Iswanto WibowoAffiliation unknown1
Prapti Wigati PurwaningrumAffiliation unknown1
Baruna PriasmoroAffiliation unknown1
Alfian KhabibiAffiliation unknown1
Danar SuryawijayaAffiliation unknown1
Putri AprilianiAffiliation unknown1
Rudi HartonoAffiliation unknown1
Dwi Putri SetyaniAffiliation unknown1
Intan Permata HapsariAffiliation unknown1
Novita SetiawatiAffiliation unknown1
SRI WAHYUNIAffiliation unknown1
Rizka D. A. A.Affiliation unknown1
Prahda Alifa FegasantiAffiliation unknown1
Pandu Perdana PutraAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/elt/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">ANALYSIS OF GOOGLE TRANSLATE’S QUALITY IN EMPLOYING TRANSLATION TECHNIQUES</dc:title>
	<dc:creator>Kartika, Dewi</dc:creator>
	<dc:creator>Priyatmojo, Arif Suryo</dc:creator>
	<dc:description xml:lang="en-US">This research focused on the analysis of translation techniques and translation quality of Jakarta Post’s articles in terms of accuracy, acceptability, and readability. The objectives of this research were to find out the translation techniques applied by Google Translate in translating the articles of Jakarta Post and to know the quality of translation by Google Translate. This research applied a descriptive qualitative method. The data were obtained by using content analysis and questionnaire. The data in this research were ten articles of Jakarta Post from opinion section. The other data were the results of the translation quality assessments done by the respondents. The research findings showed that Google Translate applied 9 translation techniques. They were reduction, established equivalent, literal, calque, amplification, transposition, linguistic amplification, linguistic compression, and borrowing technique. The results of the questionnaires showed that the percentage of accuracy was 57.1% with average score 2.5, the percentage of acceptability was 58.6% with the average score 2.5, and the percentage of readability was 63.7% with the average score 2.5. Based on the results obtained, the quality of translation results by Google Translate was less accurate, less acceptable, and less readable. According to the analysis, it can be concluded that calque technique had the best translation quality considering this technique got the highest score in every aspect. While reduction technique was the least because this technique got the lowest score in every aspect. The researcher suggested the users to translate simple sentence instead of a complex one to gain a better quality of translation using Google Translate.</dc:description>
	<dc:publisher xml:lang="en-US">English Department, Faculty of Languages and Arts, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2018-08-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/vnd.openxmlformats-officedocument.wordprocessingml.document</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/elt/article/view/25304</dc:identifier>
	<dc:identifier>10.15294/elt.v7i1.25304</dc:identifier>
	<dc:source xml:lang="en-US">ELT Forum: Journal of English Language Teaching; Vol 7 No 1 (2018): ELT Forum: Journal of English Language Teaching; 40-49</dc:source>
	<dc:source>2721-4532</dc:source>
	<dc:source>2252-6706</dc:source>
	<dc:source>10.15294/elt.v7i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/elt/article/view/25304/11348</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 ELT Forum: Journal of English Language Teaching</dc:rights>
</oai_dc:dc>