Translation Analysis Of Subject Found In The Casual Vacancy Into Perebutan Kursi Kosong

• Main Authors: Damayanti, Ita (Author), , Dr. Dwi Haryanti, M.Hum (Author), , Mauly Halwat Hikmat, Ph. D (Author)
• Format: Book
• Published: 2016-05-05.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Connect to this object online
• Notes: https://eprints.ums.ac.id/43390/1/PUBLICATION%20ARTICLE.pdf; https://eprints.ums.ac.id/43390/2/FRONT%20OF%20PAGE.pdf; https://eprints.ums.ac.id/43390/3/CHAPTER%20I.pdf; https://eprints.ums.ac.id/43390/7/CHAPTER%20II.pdf; https://eprints.ums.ac.id/43390/8/CHAPTER%20III.pdf; https://eprints.ums.ac.id/43390/9/CHAPTER%20IV.pdf; https://eprints.ums.ac.id/43390/11/CHAPTER%20V.pdf; https://eprints.ums.ac.id/43390/12/BIBLIOGRAPHY.pdf; https://eprints.ums.ac.id/43390/15/APPENDIX.pdf; https://eprints.ums.ac.id/43390/14/PERNYATAAN%20PUBLIKASI.pdf
• Keywords: L Education (General); P Philology. Linguistics

This research aims to identify the linguistic form of subject of the sentences and to describe the equivalence of the Indonesian translation found in The Casual Vacancy into Perebutan Kursi Kosong. The type of this research is descriptive qualitative. The object of this research is the translation of subject found in The Casual Vacancy into Perebutan Kursi Kosong. The data are all sentences consisting of subject and the data source is a novel entitled The Casual Vacancy by J.K Rowling. The researcher uses the documentation as method to collect the data. Then to prove the validity of the data, the writer uses triangulation where the data sources are the novel and informant. The results of the research show that first, there are 4 kinds of subject, namely; noun, pronoun, gerund, and noun phrase. First, there are 34 or 0.74% data belongs to translation shift of noun, it consists of level shift 24 or 0.5% data, intrasystem shift 8 or 0,2% data, and class shift 2 or 0.04% data. Secondly, there are 792 or 17.5% data which belongs to translation shift of pronoun consists of 505 or 11.1% of class shift, 104 or 2.3% data of level shift, and 183 or 4% of structural shift. The third is gerund. The writer only finds 2 or 0.04% data that belongs to class shift of gerund. The last, 781 or 17.2% data that belongs to translation shift of noun phrase consists of 153 or 3.46% data of level shift, 3 or 0.06% data of class shift, and 621 or 13.7% data of structural shift. Second, there are 4536 or 99.98% data that belongs to equivalent translation and only 1 data or 0.02% data is included non equivalent translation. Keywords: Translation, Translation shift, subject, equivalent