Translating Causative Have and Get: A Comparative Study between Google Translate Translation and Human Translation
DOI:
https://doi.org/10.33541/jet.v11i1.6652Keywords:
Causative, Google Translate, tperiphrastic, translationAbstract
Technological advances have made the ability to translate no longer exclusively belong to humans. Today, machine translation has turned into a tool with superior performance to convert text between languages without the need for human intervention. One of the translation research foci is the studies of causative translation, especially from English to several other languages. Yet, it might be interesting to compare the translation of that topic by human and machine translation. This study investigates the comparison of Google Translate and humans in terms of causative translation from English into Indonesian. The data were obtained from six English novels and their translations in Indonesian. To analyze the data, 100 clauses with causative have and get were selected from English novels and translated by Google Translate into Indonesian. The result showed that the translation and strategies used between Google Translate of causative have and get had similarity with human translation in relation to causative-to-causative translation. Through the investigation, the result is expected to be beneficial for further studies in the translation of causative have and get related to their translations into Indonesian analytic or morphological causative. Furthermore, the result of strategies compared is expected to be beneficial to the translation study regarding machine and human translation in causative, especially from English into Indonesian.
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