AI, Machine Translation, and Human Translation in Rendering “The Story of an Hour”: A Comparative Quality Assessment - Wulansari, Atsani; Gunawan, Wawan; Safrina, Rd.; Arvianti, Gilang Fadhilia; Mazid, Sukron (Eralingua: Jurnal Pendidikan Bahasa Asing dan Sastra, 2026)
The rise of AI in recent times has significantly impacted the translation industry, igniting discussions about the respective roles of AI-driven machine translation and human expertise. However, the effectiveness of AI and machine translation in translating literary works remains a topic of debate, as literary translation should be linguistically accurate and preserve nuance, emotion, and cultural context. This study aims to observe the result of AI, Machine Translation, and humans in translating the short story entitled The Story of An Hour. This study analyses the translation method used by AI, Machine Translation (MT), and Human (HT) to translate a short story. Moreover, this research also determines the quality of the translation results from AI, MT, and HT. The research method used is qualitative and quantitaive. The data are collected from document analysis to observe the translation methods based on Newmark and questionnaire from Sutopo & Setya Budi to assess the quality of literary translation results. The research objects are the translation results of Chat GPT, DeepL, and human translator taken from fiksi lotus. The translation results are assessed concerning the accuracy, the sense of literature, acceptability, and readability. The results show that the significant translation methods applied in AI and machine translation are literal, faithful, communicative, and semantic translations. However, a human translator uses free translation, adaptation, and communicative translation. The quality result shows that human translators get higher accuracy, acceptability, sense of literature, and readability.