POST-EDITING MACHINE TRANSLATION OF ENGLISH-INDONESIAN BY EFL STUDENTS: A STUDY ON GRAMMATICAL COHESION IN ABSTRACT TRANSLATION

Machine translations offer several features that simplify the translation process. These include the ability to automatically adjust grammar and vocabulary from the source language to the target language, store word banks, and tailor the target language to specific fields. However, machine translation outputs still contain errors. Therefore, it is essential to perform post-editing to ensure grammatical and lexical cohesion and alignment between the source and target languages. This research aims to observe the quality of Google Translate and the result of Post-editing machine translation by EFL learners in terms of grammatical cohesion. This study used a descriptive qualitative. This study applied purposive sampling to choose the data. Three abstracts from three different Translation and Interpreting classes were chosen for the data. Then, the data were analysed by using the theory of grammatical cohesion and translation quality assessment. The result of the study shows that the grammatical cohesions found are mostly reference and conjunction. This study also finds that the quality of post-editing is better than the result of Google Translation as machine translation. The samples of data provides that mostly the score of post-editing is better observed from translation acceptability and readability. This study is restricted to the translation result of three abstracts only and the students’ post-editing effort which means that the findings may not fully represent the overall quality of translations from a grammatical cohesion. Future research could delve deeper into this topic by expanding the data sources and incorporating machine translation tools other than Google Translate.