Errors Analysis of Google Translate: A Case Study of Translation Subject

Abstract

In college activities, there are many assignments related to English, both in the form of reading articles and assignments to make translations. In dealing with such assignments, students often depend on the use of GT (Google Translate). GT is one of the most popular MT (Machine Translation) because of its speed in translating and also because of the many languages that can be used as references both as source languages and target languages. GT can translate hundreds of source languages and hundreds of others into target languages in seconds. GT can also translate through photos. In addition to the speed and sophistication of GT, the accuracy of translation must be a special consideration. This study aims to reveal some errors made by GT in translating texts from Indonesian to English as the target language. The sentences translated amounted to 30 sentences taken randomly from various sources on the internet. The data collection method used was participatory observation and documentation. Direct observation was carried out by researchers being directly involved in the collection, especially in checking the translations made by GT. The data analysis method used was Categorization based on the theory of Error Analysis of MT. The results of this study are as follows. From 30 sentences as source data translated by GT, there were 13 GT errors or 43.3%. Of these errors, the most were errors in Incorrect Grammar and Structure as many as 6 errors or 20%. Furthermore, errors in Lexical Error as many as 4 errors or 13.3%. Furthermore, followed by Incoherence translation data which had 2 errors or 6.6% and the last was Extraneous translation as many as 1 error or 3.3%.