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THE QUALITY OF TRANSLATION BY MACHINE AND HUMAN IN SELECTED “SUKSES DAILY” VIDEOS ON YOUTUBE (COMPARATIVE ANALYSIS)

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This study aims to compare the translation quality between machine and
human, particularly in the context of selected “Sukses Daily” videos on YouTube.
In achieving these goals, this research uses mixed-method approaches. It is
analyzed based on the Translation Quality Assessment (TQA) model by Nababan
et al. (2012): accuracy, acceptability, and readability. Meanwhile, the data was
collected through questionnaires distributed to the informants.
The analysis shows that human translation generally outperforms machine
translation in terms of accuracy, acceptability, and readability. The research finds
that human translation is better at understanding complex context, recognizing
nuances in language, and adapting to the appropriate language style for the target
language. The research evidence shows that out of 43 data that have been
evaluated, machine translation has an average score for the accuracy of the
translation of 1.48 out of 3. The average score for the acceptability of the
translation is 1.81 out of 3, and the average score for readability is 1.99 out of 3.
Overall, the average score of the machine translation quality is 1.7, which
indicates that the translation has poor quality. Meanwhile, the human translation
has an average score of 1.65 out of 3 for accuracy. The average score for the
acceptability of the translation is 2.52 out of 3, and the average score for
readability is 2.72 out of 3. Overall, the average score of human translation quality
is 2.61, which indicates that the translation has good quality. This research is
expected to provide insights into the quality of machine translation and human
translation on YouTube, and to offer new ideas for future researchers to further
investigate the specific quality of machine or human translation. The researchers
hope that this study will contribute to the advancement of knowledge in the field
of translation and encourage further research in this area.

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Availability

Detail Information

Series Title

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Call Number

BSI 2023 MUH t

Publisher

Makassar : Fak. Adab & Humaniora UIN Alauddin., 2023

Collation

xv, 87 hlm.; 30 cm

Language

English

ISBN/ISSN

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Classification

BSI 2023 MUH t

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Human Translation
Translation Quality Assessment
Machine Translation

Specific Detail Info

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Statement of Responsibility

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