Proper Names in Sherlock Holmes Novel `The Sign Of Four` into Its Indonesian Translation (Translation Techniques and Quality) - Yunita Widiyantari; Aprilia Koni Surya Atmaja; Nur Saptaningsih (English Language and Literature International Conference (ELLiC) Proceedings, 2017)
The research focuses on the translation of proper names in the novel entitled Sherlock Holmes: The Sign of Four. The objectives of this research are to obtain the kinds of proper names, the way they are translated into Indonesian, and the impacts of the translation techniques on the quality of translation in terms of accuracy and acceptability. This research is a descriptive qualitative research with single embedded-case study. To collect the data, the researcher applied purposive sampling technique. The primary data were obtained by using content analysis and the secondary data were obtained through questionnaires. In content analysis, the researcher collected the data by listing and classifying proper names found in the novel and its translation. The researcher found 239 data in the novel.This research finding shows that the kinds of proper names found are 66 personal names (consists of 48 gender specific names, 2 real person names, 11 nicknames and titles, 2 relationship noun, 1 title used without name and 2 pet names), 104 geographical terms (consisting of 97 names of continents, islands, countries, states, cities, towns, mountain and rivers and 7 names of institutions and departments), 46 names for things (consists of 19 names of nationality and tribe, 6 names of community, 7 religious names, 6 names of dates and 8 names of art works and literatures), 23 other names (unidentified names). Those are translated into Indonesian by using 7 techniques of translation: copy, rendition, transcription, calque, deletion, addition, substitution. Besides that, the translator also applies the combination technique of those single techniques into 6 combinations. From the 239 data of proper names, 233 data (97.48%) are accurate, a datum (0.41%) is less accurate, and 5 data (2.09%) are inaccurate. Meanwhile, from the acceptability level, there are 214 data (89.52%) are acceptable translation, three data (1.25%) are less acceptable, and 22 data (9.20%) are unacceptable.