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ERRORS MADE IN GOOGLE TRANSLATE IN THE INDONESIAN TO ENGLISH TRANSLATIONS OF NEWS ITEM TEXTS

ELT Forum: Journal of English Language Teaching · Vol. 5 No. 2 (2016)

DOI
10.15294/elt.v5i2.11228
ISSN
2721-4532, 2252-6706
Terbit
2016-05-16
Penerbit
English Department, Faculty of Languages and Arts, Universitas Negeri Semarang
Bahasa
eng

Abstrak

The objective of this study was to describe the errors made in the Indonesian to English Google Translate translations of News Item texts. This study employed five English translations of Indonesian News Item texts taken from (1) bbc.com, (2) kompas.com, (3) liputan6.com, (4) tempo.co, and (5) viva.co.id made by using Google Translate. Those samples were taken by using purposive sampling technique. The categorization of translation errors were adapted from Dewi’s Indonesian-English translation error typology. The errors can occur in the words, phrases, clauses, and sentences of the texts. The data gathered were analyzed descriptively by using qualitative approach. The findings of the analysis showed that there were 13 categories of translation errors obtained from 278 data. Ranking from the most common to the least common errors found in the data, they were grammatical errors (24.46%), terminology errors (15.47%), omission errors (14.03%), syntax errors (12.23%), mistranslation/misunderstanding errors (6.47%), literalness/faithfulness errors (6.47%), usage errors (6.12%), punctuation errors (3.60%), addition errors (2.88%), ambiguity errors (2.52%), word form errors (2.52%), capitalization errors (2.16%), and spelling errors (1.08%). The data findings also showed that statistical method of Google Translate, the inability of Google Translate to understand the contexts of the texts beyond sentence, and errors in the source texts that carried into translation errors in the target texts were the causes of translation errors found in the data.

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  • State University of Semarang
  • Politeknik Maritim Negeri Indonesia
  • Universitas Harapan Bangsa
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Rekan penulisOrganisasiArtikel bersama
Issy YuliasriState University of Semarang2
Marselia MarseliaPoliteknik Maritim Negeri Indonesia1
Shadam HusseniState University of Semarang1
Hanifah Nur Najibah KomanState University of Semarang1
Irfan Zahid PrasetyaState University of Semarang1
Wahyu MegawatiAfiliasi tidak diketahui1
Djoko SutopoState University of Semarang1
Ida Dian SukmawatiUniversitas Harapan Bangsa1
Mia Nurul AzmiAfiliasi tidak diketahui1
Dwi Anggani Linggar BharatiState University of Semarang1
Ade Dwi CahyantiState University of Semarang1
Ever NicolasState University of Semarang1
Abdurrachman FaridiState University of Semarang1
Ajeng Hidayatul MaghdalenaState University of Semarang1
Arif Suryo PriyatmojoState University of Semarang1
Dwi Putri SetyaniState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/elt/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">ERRORS MADE IN GOOGLE TRANSLATE IN THE INDONESIAN TO ENGLISH TRANSLATIONS OF NEWS ITEM TEXTS</dc:title>
	<dc:creator>Ismail, Adam</dc:creator>
	<dc:creator>Hartono, Rudi</dc:creator>
	<dc:description xml:lang="en-US">The objective of this study was to describe the errors made in the Indonesian to English Google Translate translations of News Item texts. This study employed five English translations of Indonesian News Item texts taken from (1) bbc.com, (2) kompas.com, (3) liputan6.com, (4) tempo.co, and (5) viva.co.id made by using Google Translate. Those samples were taken by using purposive sampling technique. The categorization of translation errors were adapted from Dewi’s Indonesian-English translation error typology. The errors can occur in the words, phrases, clauses, and sentences of the texts. The data gathered were analyzed descriptively by using qualitative approach. The findings of the analysis showed that there were 13 categories of translation errors obtained from 278 data. Ranking from the most common to the least common errors found in the data, they were grammatical errors (24.46%), terminology errors (15.47%), omission errors (14.03%), syntax errors (12.23%), mistranslation/misunderstanding errors (6.47%), literalness/faithfulness errors (6.47%), usage errors (6.12%), punctuation errors (3.60%), addition errors (2.88%), ambiguity errors (2.52%), word form errors (2.52%), capitalization errors (2.16%), and spelling errors (1.08%). The data findings also showed that statistical method of Google Translate, the inability of Google Translate to understand the contexts of the texts beyond sentence, and errors in the source texts that carried into translation errors in the target texts were the causes of translation errors found in the data.</dc:description>
	<dc:publisher xml:lang="en-US">English Department, Faculty of Languages and Arts, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2016-05-16</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/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/elt/article/view/11228</dc:identifier>
	<dc:identifier>10.15294/elt.v5i2.11228</dc:identifier>
	<dc:source xml:lang="en-US">ELT Forum: Journal of English Language Teaching; Vol 5 No 2 (2016)</dc:source>
	<dc:source>2721-4532</dc:source>
	<dc:source>2252-6706</dc:source>
	<dc:source>10.15294/elt.v5i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/elt/article/view/11228/6724</dc:relation>
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