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All Journal Journal of English Language Teaching and Linguistics
Ghithrif, Atsal Naufal
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Measuring the Translation Quality of Bilingual Commercial Web in Indonesian: The Urgency of Avoiding Machine Translation Ghithrif, Atsal Naufal; Nugroho, Raden Arief
Journal of English Language Teaching and Linguistics Journal of English Language Teaching and Linguistics, 10(2), August 2025
Publisher : Yayasan Visi Intan Permata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21462/jeltl.v10i2.1554

Abstract

This research discusses the translation quality of human translation particularly in the Indonesian - English language on a commercial website called Garudafood. This study evaluates the translation quality of the names of products that contain cultural aspects on the Garudafood website. The process of data collection uses a purposive sampling method with cultural categories theory by Newmark (1988). It is found that there are 39 data or names of foods that are categorized into material culture. Guided by past related research, this study employs the translation technique proposed by Molina and Albir (2002) to find out the most frequently used type of technique by translators in translating Garudafood products. Following the goal of this study, the researchers also use the translation quality assessment (TQA) theory by Nababan (2012). The overall result shows that the TQA of Garudafood product translation is averaging a 2.65 score, with established equivalent technique as the most frequently used type of translation technique by the translator. Furthermore, the Machine Translations tested by the researchers only reached the total average score of 2.01 and 2.18. By comparing with the analysis of using machine translation such as DeepL Translation and Google Translate, the researchers conclude that human translation produces a better-quality translation due to the translator's understanding of various contexts compared to machine translation which generates more objective translation. This statement is also supported by comparing with previous studies related to post-editing, machine translation, and human translation.
Co-Authors Raden Arief Nugroho