THE ACCURACY OF CHATGPT IN TRANSLATING LINGUISTICS TEXT IN SCIENTIFIC JOURNALS

RUSMITA, AENI (2024) THE ACCURACY OF CHATGPT IN TRANSLATING LINGUISTICS TEXT IN SCIENTIFIC JOURNALS. S1 thesis, Universitas Mataram.

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Abstract

AI-generated Machine Translation, such as Neural Machine Translation, has transformed the traditional role of translators. There is a viral language model called ChatGPT. ChatGPT is a conversational variation of Natural Language Processing (NLP) Generative Pretrained Transformer (GPT) models. This research is aimed to analyze the accuracy of ChatGPT in translating linguistics text in scientific journals. The study employs qualitative approach and includes into quality assessment. The data source of this research is a National journal named Ranah focused on language and linguistics, Volume 12 number 1- 13 published in 2023. The data then analyzed using few theories. Snover’s theory in finding error rate (HTER) and translation quality index to measure translation accuracy by Schiaffino and Zearo. Through the analyzation result, it could be inferred that In the analysis of 2034 words using Snover's theory revealed specific categories of translation errors in ChatGPT with a total of 6% error, there were 15 insertion errors (0.73%), 26 deletion errors (1.32%), 72 substitution errors (3.54%), and 17 shifting errors (0.83%). With a total error of 6,4%, this brings ChatGPT's accuracy rate in translating linguistic scientific texts to 93,6%. Through the analyzation result, it could be inferred that ChatGPT successfully translates scientific text within excellent category .

Item Type:	Thesis (S1)
Keywords (Kata Kunci):	accuracy, ChatGPT, HTER, translation
Subjects:	L Education > LC Special aspects of education L Education > LC Special aspects of education > LC5201 Education extension. Adult education. Continuing education
Divisions:	Fakultas Keguruan dan Ilmu Pendidikan
Depositing User:	Meike Megawati
Date Deposited:	26 Jan 2024 02:10
Last Modified:	26 Jan 2024 02:10
URI:	http://eprints.unram.ac.id/id/eprint/44286

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