A Comparative Analysis of Google Translate and ChatGPT Results Based on Translation Quality Assessment (TQA)

Authors

  • Roswani Siregar Universitas Al-Azhar
  • Heni Subagiharti Universitas Asahan
  • Diah Syafitri Handayani Universitas Sumatera Utara
  • Dermawan Hutagaol Universitas Al-Azhar Medan
  • Ahmad Laut Hasibuan Universitas Muslim Nusantara Al Washliyah
  • Nuraida Nuraida Universitas Al-Azhar, Medan, Indonesia
  • Ervina Sipahutar Universitas Al-Azhar, Medan, Indonesia

DOI:

https://doi.org/10.55299/ijere.v4i1.1175

Keywords:

translation, quality, assessment, google translate, chatgpt, artificial intelligence

Abstract

The development of digital technology today has a major impact on various aspects of human life. In bridging intercultural communication, translation has a significant role that cannot be separated from the help of technology. Technology also has brought changes in the way translation is done, including helping individual translators to increase efficiency. For example, with the help of machine translation, Google Translate continues to develop transformers and AI. On the other hand, ChatGPT, built on artificial intelligence, allows translation. Both adopt NLP. This study aims to determine the quality of the translation of both based on the TQA proposed by House. In addition, it assesses the level of similarity of the translation results and errors that occur based on the translation technique used. Translation samples were selected based on purposive sampling techniques, namely from a report chapter available on the internet in English. The samples were translated into Indonesian using Google Translate (GT) and ChatGPT (CG) and then analyzed using TQA. The results show that GT and CG have high similarities and insignificant error rates. This is possible because GT and CG continue to be developed over time to respond to and translate languages that are increasingly natural and resemble human language.

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Author Biographies

Heni Subagiharti, Universitas Asahan

Lecturer at Faculty of Teaching Training and Education, Asahan University.

Diah Syafitri Handayani, Universitas Sumatera Utara

Japanese Studies Program, Faculty of Vocational, Universitas Sumatera Utara

Dermawan Hutagaol, Universitas Al-Azhar Medan

Faculty of Agriculture, Universitas Al-Azhar Medan

Ahmad Laut Hasibuan, Universitas Muslim Nusantara Al Washliyah

 Department of English, Faculty of Postgraduate, Universitas Muslim Nusantara Al Washliyah

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Published

2025-06-10

How to Cite

Siregar, R., Subagiharti, H., Syafitri Handayani, D., Hutagaol, D., Hasibuan, A. L., Nuraida, N., & Sipahutar, E. (2025). A Comparative Analysis of Google Translate and ChatGPT Results Based on Translation Quality Assessment (TQA). International Journal of Educational Research Excellence (IJERE), 4(1), 328–337. https://doi.org/10.55299/ijere.v4i1.1175

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