Komarawan, Yulizar
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Translation Accuracy of Complex Sentences in Disciplinary Texts Using Google Translate (GT) Khorina, Mulyati; Sulyaningsih, Iis; Komarawan, Yulizar
Jurnal Bahasa Inggris Terapan Vol. 10 No. 2 (2024): Oktober 2024
Publisher : Jurusan Bahasa Inggris - Politeknik Negeri Bandung

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Abstract

Google Translate has gained popularity due to some improvements to produce accurate translations since 2016. However, there is an on-going debate over the accuracy of Google Translate products. In response to this issue, the current study investigates how Google Translate interprets source language, particularly relative clauses into target language and how accurate the translation products are. This study used a qualitative case study. Moreover, the study used some chapters from an engineering textbook together with their translation version as primary data. The data in the form of relative clauses were put on a table side by side. It was then analysed and evaluated using a comparative method to find out similarity and differences. The study found that dominantly current Google Translate uses literal and expansion techniques. Furthermore, the findings suggest that GT produces accurate translation when translating relative clauses.
The Analysis of Lexical Cohesion in The Global Story Podcasts by BBC World Service YouTube Channel Rasis, Vanessa Mutiara; Khorina, Mulyati; Komarawan, Yulizar; Firdhani, Anggi Rizky
Jurnal Bahasa Inggris Terapan Vol. 11 No. 1 (2025): April 2025
Publisher : Jurusan Bahasa Inggris - Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35313/jbit.v11i1.6580

Abstract

Lexical cohesion can be found in both written and spoken texts. It is critical because it is a device to make text cohesive and coherent. Consequently, lexical cohesion serves as an indicator to measure whether a text is cohesive or coherent. However, using lexical cohesion appropriately is challenging, especially for non-native English learners. Therefore, the purpose of this article was to analyze lexical cohesion found in spoken text. This study applied qualitative method and the data were collected from five podcasts of The Global Story podcast by the BBC World Service YouTube channel. In analyzing the data, the theory of lexical cohesion proposed by Paltridge (2022) was applied. The results reveal that all types of lexical cohesion, such as repetition, synonymy, antonymy, hyponymy, meronymy, and collocation are found in the data. Among them, collocation is the most frequently used. Moreover, lexical cohesion in podcasts shows its essential role in maintaining coherence and facilitating comprehension in spoken text. These findings can be used as the reference for improving the vocabulary of non-native English learners, especially for spoken use.