Salsabila Arju, Muhammad Fadhil Husein, Badriyyah Sa’adah, Annisa Mah Rejeki

ANALISIS KEAKURATAN HASIL TERJEMAHAN CHATGPT MENGGUNAKAN TEKNIK BACK TRANSLATION

Introduction

Analisis keakuratan hasil terjemahan chatgpt menggunakan teknik back translation. Studi ini menganalisis keakuratan terjemahan ChatGPT dari teks Arab ke Indonesia menggunakan teknik back translation. Hasilnya menunjukkan ChatGPT akurat, singkat, dan lebih efisien.

Abstract

In the world of translation, language translators often experience several challenges in the translation process. These can be found in differences in sound, writing, grammar, and local culture and values of a language. As time progresses and with the emergence of new technology based on artificial intelligence, translators or individuals involved in foreign languages are increasingly assisted in their translation tasks. This study aims to analyze the extent of accuracy in using ChatGPT for translating Arabic texts into Indonesian. It is a qualitative-descriptive research. The data collection method involves using literacy study methodology. The research findings indicate that ChatGPT can accurately translate Arabic into Indonesian without any grammatical errors or semantic inaccuracies. There are only a few differences observed in word choice, which are deemed to be shorter, concise, and more efficient in translation than Google Translate.

Review

This paper addresses a timely and relevant topic concerning the application of artificial intelligence in translation, specifically focusing on ChatGPT. The abstract introduces the prevalent challenges in translation and positions AI tools as a significant aid for linguists. The stated aim is clear: to analyze the accuracy of ChatGPT in translating Arabic texts into Indonesian. The research is characterized as qualitative-descriptive, utilizing a "literacy study methodology" for data collection, although the specific application of the "back translation technique" mentioned in the title is not elaborated upon in the abstract's description of the methodology. The findings presented are notably strong, claiming that ChatGPT can accurately translate Arabic into Indonesian "without any grammatical errors or semantic inaccuracies." This is a very high bar for any machine translation system, especially for complex language pairs, and such an assertion typically requires robust evidence and specific error categorization or quality metrics to be credible. While the abstract mentions "only a few differences observed in word choice," this seems to contradict the earlier claim of absolute accuracy. Furthermore, a brief comparison with Google Translate is mentioned, suggesting ChatGPT is "shorter, concise, and more efficient," but the criteria or methodology for this comparative assessment are not detailed, making it difficult to evaluate the validity of this claim. While the premise of evaluating advanced AI in translation is commendable, the abstract raises more questions than it answers regarding the rigor and specific findings of the study. For a journal publication, the claims of flawless translation would require extensive empirical data, a clear definition of "accuracy," detailed error analysis, and a transparent methodology for both the translation and the comparison with other tools. Without a more explicit description of how the back-translation technique was applied, the nature of the "literacy study," the size and characteristics of the Arabic text corpus, and the precise metrics used for evaluation, the abstract leaves the reader skeptical about the generalizability and robustness of the presented conclusions.

Full Text

Comments

You need to be logged in to post a comment.