Selecting the Evaluator Assessing the Equivalence and the Acceptability
Figure 4.1 The translation equivalence chart
Based on the Figure 4.1, there were 56 utterances and 56 subtitles from 4 advertisements of Intel by different versions which were analyzed by the
researcher. The researcher previously assessed the subtitle according to the indicator whether they were equivalent, with the validation from the evaluator.
The result was that there were 31 subtitles that were equivalent and 25 subtitles that were not equivalent. In detail, the researcher found that the advertisement
number 1 with the code JFFH had 8 not equivalent and 5 equivalent translation subtitles, the advertisement number 2 with the code NM had 7 not equivalent and
11 equivalent translation subtitles, the advertisement number 3 with the code K had 4 not equivalent and 10 equivalent translation subtitles, the advertisement
number 4 with the code RAY had 6 not equivalent and 5 equivalent translation subtitles.
Keeping the value of not equivalent was 1 and equivalent was 2 in mind, it was found that the total score was 87 points and the average score was 1,6.
Therefore, with the score 1,6, the translation subtitle of Intel advertisements was categorized as equivalent.
Firstly, the researcher needed to explain the utterances and subtitles which were categorized as the equivalent translation, then in the following, the
researcher needed to explain the utterances and the subtitles which were categorized as the non-equivalent translation. The researcher provided some
examples to show his analysis and explanation. Assessing this equivalence aspect was based on Nida, Catford, and Nababan theories.