WECHAT AUTO TRANSLATION: ANALISIS PENERJEMAHAN BAHASA MANDARIN DALAM INDUSTRI IMPOR
DOI:
https://doi.org/10.51878/academia.v6i4.16026Keywords:
Teknik Penerjemahan, Penerjemahan Mesin, Wechat, Komunikasi BisnisAbstract
The growth of globalization and cross-border business communication has increased the use of automatic translation, including the auto-translation feature in the WeChat application. However, automatic translation in business communication involving specialized terminology may produce inaccurate meanings due to limitations in understanding context and domain-specific knowledge. This study aims to analyze the translation techniques used by WeChat’s auto translation feature in Mandarin-to-Indonesian fruit import business communication and to compare its output with human translation. This study employed a qualitative approach with a case study design involving ten conversation samples between Indonesian importers and Chinese suppliers. The data were analyzed based on a classification of translation techniques. The results show that literal translation was found in 9 samples (90%), borrowing in 8 samples (80%), reduction in 8 samples (80%), and established equivalence in 6 samples (60%). Literal translation and borrowing tended to preserve the form of the source language, but they could produce unnatural or inaccurate translations when applied to fruit variety names, logistics terminology, and expressions requiring contextual understanding. Techniques that require adjustments in perspective, structure, and context, such as modulation, transposition, and adaptation, were also not always applied effectively by the system. Within the context of fruit import business communication through WeChat analyzed in this study, automatic translation still requires human editing and adjustment to improve meaning accuracy, readability, and the appropriateness of domain-specific terminology.
ABSTRAK
Perkembangan globalisasi dan komunikasi bisnis lintas negara meningkatkan penggunaan penerjemahan otomatis, termasuk fitur auto translation pada aplikasi WeChat. Namun, penerjemahan otomatis dalam komunikasi bisnis yang mengandung terminologi khusus berpotensi menghasilkan ketidaktepatan makna karena keterbatasannya dalam memahami konteks dan pengetahuan domain. Penelitian ini bertujuan menganalisis teknik penerjemahan yang digunakan oleh fitur auto translation WeChat dalam komunikasi bisnis impor buah dari bahasa Mandarin ke bahasa Indonesia serta membandingkan hasilnya dengan penerjemahan manusia. Penelitian menggunakan pendekatan kualitatif dengan desain studi kasus terhadap sepuluh sampel percakapan antara importir Indonesia dan pemasok Tiongkok. Data dianalisis berdasarkan klasifikasi teknik penerjemahan. Hasil analisis menunjukkan bahwa teknik penerjemahan literal ditemukan pada 9 sampel (90%), peminjaman (borrowing) pada 8 sampel (80%), reduksi pada 8 sampel (80%), dan kesepadanan lazim pada 6 sampel (60%). Penerjemahan literal dan peminjaman cenderung mempertahankan bentuk bahasa sumber, tetapi dapat menghasilkan terjemahan yang kurang alami atau tidak tepat ketika diterapkan pada nama varietas buah, istilah logistik, dan ungkapan yang membutuhkan pemahaman kontekstual. Teknik yang memerlukan penyesuaian perspektif, struktur, dan konteks, seperti modulasi, transposisi, dan adaptasi, juga belum selalu diterapkan secara efektif oleh sistem. Dalam konteks komunikasi bisnis impor buah melalui WeChat yang dianalisis, hasil penerjemahan otomatis masih memerlukan penyuntingan dan penyesuaian oleh penerjemah manusia untuk meningkatkan ketepatan makna, keterbacaan, dan kesesuaian terminologi bidang.
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References
Afandi, A. R., & Kurnia, H. (2023). Revolusi teknologi: Masa depan kecerdasan buatan (AI) dan dampaknya terhadap masyarakat. Academy of Social Science and Global Citizenship Journal, 3(1). https://doi.org/10.47200/aossagcj.v3i1.1837
Araghi, S., & Palangkaraya, A. (2024). The link between translation difficulty and the quality of machine translation: A literature review and empirical investigation. Language Resources and Evaluation, 58, 1093–1114. https://doi.org/10.1007/s10579-024-09735-x
Creswell, J. W., & Poth, C. N. (2024). Qualitative inquiry and research design: Choosing among five approaches (5th ed.). SAGE Publications. SAGE Publishing
Han, S., & Kang, D. (2022). A comparative evaluation of machine translation and human translation, and post-edited machine translation and revised human translation: Focusing on Korean-Russian translation. Interpreting and Translation Studies, 26(1), 195–219. https://doi.org/10.22844/its.2022.26.1.195 KCI
Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292, 114523. https://doi.org/10.1016/j.socscimed.2021.114523
Jung, J. (2023). Accuracy errors remaining uncorrected in post-edited output. Interpreting and Translation Studies, 27(3), 177–201. https://doi.org/10.22844/its.2023.27.3.177 KCI
Lee, J., & Choi, H. (2024). An analysis of errors in human translation, machine translation and post-edited machine translation outputs: A case of Korean-English legal translation. The Journal of Translation Studies, 25(1), 11–39. https://doi.org/10.15749/jts.2024.25.1.001
Liu, X., & Cui, Y. (2024). The impact of text type on Chinese-English translation effort: An investigation with reference to translation entropy. Humanities and Social Sciences Communications, 11, 676. https://doi.org/10.1057/s41599-024-03187-y
Maulidina, N. (2024). Komparasi teknik penerjemahan ChatGPT dan Bing Chat pada teks berita kesehatan jiwa Mawdoo3.com [Skripsi, UIN Syarif Hidayatullah Jakarta]. Repository UIN Syarif Hidayatullah Jakarta. https://repository.uinjkt.ac.id/dspace/handle/123456789/78272
Molina, L., & Hurtado Albir, A. (2002). Translation techniques revisited: A dynamic and functionalist approach. Meta, 47(4), 498–512. https://doi.org/10.7202/008033ar
Moslem, Y., Romani, G., Molaei, M., Kelleher, J. D., Haque, R., & Way, A. (2023). Domain terminology integration into machine translation: Leveraging large language models. In P. Koehn, B. Haddow, T. Kocmi, & C. Monz (Eds.), Proceedings of the Eighth Conference on Machine Translation (pp. 902–911). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.wmt-1.82
Priya, A. (2021). Case study methodology of qualitative research: Key attributes and navigating the conundrums in its application. Sociological Bulletin, 70(1), 94–110. https://doi.org/10.1177/0038022920970318
R?dzioch-Korkuz, A. (2023). Revisiting the concepts of translation studies: Equivalence in linguistic translation from the point of view of Peircean universal categories. Language and Semiotic Studies, 9(1), 33–53. https://doi.org/10.1515/lass-2022-0008
Shin, D., & Chon, Y. V. (2023). Second language learners’ post-editing strategies for machine translation errors. Language Learning & Technology, 27(1), 1–25. https://doi.org/10.64152/10125/73523
Song, H., & Xu, H. (2024). A deep analysis of the impact of multiword expressions and named entities on Chinese-English machine translations. In Findings of the Association for Computational Linguistics: EMNLP 2024 (pp. 6154–6165). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.357
Tekwa, K., & Liu, J. J. (2024). Linguistic minorities and crisis communication: Assessing the contribution of real-time machine-translated instant messaging during a cascading crisis. SAGE Open, 14(4). https://doi.org/10.1177/21582440241301126
Ulimaz, A., Cahyono, D., Dhaniswara, E., Arifudin, O., & Rukiyanto, B. A. (2024). Analisis dampak kolaborasi pemanfaatan artificial intelligences (AI) dan kecerdasan manusia terhadap dunia pendidikan di Indonesia. Innovative: Journal of Social Science Research, 4(3). https://j-innovative.org/index.php/Innovative/article/view/11544
Wang, B. (2023). On the pivotal role of cultural translation in the exchanges and mutual learning between civilizations. Critical Arts, 37(3–4), 166–176. https://doi.org/10.1080/25723618.2023.2269336
Wang, H., & Chen, N. (2021). A survey of the application of machine translation post-editing in Chinese language service providers. Journal of Beijing International Studies University, 43(5), 23–37. https://doi.org/10.12002/j.bisu.352 BISU Journal
Westney, D. E., Piekkari, R., Koskinen, K., & Tietze, S. (2022). Crossing borders and boundaries: Translation ecosystems in international business. International Business Review, 31(5), 102030. https://doi.org/10.1016/j.ibusrev.2022.102030
Yang, Y., Liu, R., Qian, X., & Ni, J. (2023). Performance and perception: Machine translation post-editing in Chinese-English news translation by novice translators. Humanities and Social Sciences Communications, 10, 798. https://doi.org/10.1057/s41599-023-02285-7
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