Learning Model for Local Wisdom-based Prophet's Hadith Translation

Abstract

Google Translate is a famous translation machine among students. It is just that in the Arabic-Indonesian translation, they still need to re-edit the translation. This means that there is a problem with the quality of the machine translation results, so the accuracy still needs to be improved. Therefore, it is essential to research Arabic-Indonesian translation learning. The purpose of this study is to describe the forms of Arabic-Indonesian machine translation errors. In addition, this study also offers the Ngalodern method, Indonesian local wisdom, so that students can improve the quality of Arabic-Indonesian translation. The method used in this research is descriptive analysis and uses an eclectic combination of theories to achieve the objectives of this study. There are three stages of this research. First, providing data through selected questionnaires and interviews. Second, the data analysis uses the translational equivalent method to determine the exact equivalent of meaning, while the distributional method is used to describe the level of grammatical errors. Third, is the presentation of data in the form of a table of the percentage of errors in translation cases in the field of Islam. Ngalodern, Indonesian local wisdom as an effort to improve the quality of Arabic-Indonesian translation is described descriptively. There are two findings from this research namely, The first is a description of translation errors at the level of morphemes, words, phrases, and clauses. Second, Ngalodern learning on Arabic-Indonesian translation with critical literacy based on the Sundanese culture in the field of education. In conclusion, Ngalodern learning can improve the learner's ability to edit Arabic-Indonesian machine translation results.