Dynamics of Arabic-to-Indonesian Machine Translation on Social Media: A Content Analysis of Al Jazeera Channel - Afif Al Habib; Muhammad Azhar (Journal of Practice Learning and Educational Development, 2026)
In the current era of globalization, translation plays a pivotal role in bridging cross-linguistic and cross-cultural communication across all sectors. The essence of translation lies in conveying the meaning and intent of the source language into the target language using equivalents that are accurate, clear, and natural. This research offers both theoretical and practical benefits. Theoretically, it is expected to enhance insights and scholarly discourse regarding the quality of Arabic-Indonesian machine translation on social media platforms. A descriptive qualitative method was employed in this study to collect and analyze descriptive data in the form of linguistic phenomena. By utilizing documentation and content analysis techniques on five news posts from the "Al Jazeera Channel" Facebook account, this study successfully interpreted the quality of machine translation as it occurs naturally. Based on the analysis of the machine-translated texts, the results indicate that the translation quality is categorized as less accurate with an average score of 2.2, less acceptable with a score of 2.0, and possesses a moderate level of readability with a score of 2.4. These issues stem from fatal lexical errors, contextually inappropriate word choices, and deviations from standard Indonesian grammatical rules. The conclusion of the analysis of machine translation on the "Al Jazeera Channel" Facebook account shows that the quality is less accurate, less acceptable, and moderately readable, necessitating a profound evaluation, particularly regarding diction selection and conformity with linguistic standards.