Learning Model for Local Wisdom-based Prophet's Hadith Translation - Nugraha, Tubagus Chaeru; Lukman, Fahmy; Amalia, Rosaria Mita (Perhimpunan Intelektual Muslim Indonesia, 2022)
Google Translate is widely used among students for translation purposes, but its Arabic-Indonesian translations often require significant re-editing due to issues with accuracy and quality. These limitations highlight the need for improved translation learning methods to enhance the quality of Arabic-Indonesian translations. This study aims to analyze the types of errors found in Arabic-Indonesian machine translation and introduce the Ngalodern method, rooted in Indonesian local wisdom, to improve translation quality. A descriptive analysis method was employed, combining eclectic theories to achieve the study’s objectives. The research was conducted in three stages; first, data collection through questionnaires and interviews; second, data analysis using the translational equivalent method to identify accurate meanings and the distributional method to describe grammatical errors; and third presenting the data in tables showing the percentage of translation errors in Islamic studies texts. The Ngalodern method was described in a descriptive framework. The study identified translation errors at the levels of morphemes, words, phrases, and clauses. Additionally, Ngalodern learning, based on Sundanese cultural wisdom and critical literacy, was developed as a teaching strategy for Arabic-Indonesian translation improvement in educational contexts. The findings demonstrate that Ngalodern learning significantly enhances students’ ability to edit and improve Arabic-Indonesian machine translation results. This method offers a culturally relevant and effective approach to developing translation skills.