AN ANALYSIS OF ENGLISH-INDONESIAN CODE-MIXING USED BY MARION JOLA Nurmin F. Samola (a), Agustine C. Mamentu (b), Viona C. Kemur (c)
(a)English Language Education Department, Faculty of Language and Arts, Universitas Negeri Manado, Tondano, Indonesia
(b)English Language Education Department, Faculty of Language and Arts, Universitas Negeri Manado, Tondano, Indonesia
(c)English Language Education Department, Faculty of Language and Arts, Universitas Negeri Manado, Tondano, Indonesia
Abstract
This study analyzed Marion Jola^s usage of code mixing in a YouTube video. The writer used the theory proposed by Muysken to identify the different types of code mixing found in the utterance of Marion Jola and to figure out her reasons of using code mixing. Since the data were taken in the form of spoken words rather than numerical data, the author then applied descriptive qualitative method to answer the research questions. 44 data of code mixing were found as a result of the analysis. There were 13 data classified as insertion type, 14 data classified as alternation type and 17 data identified as congruent lexicalization type. Furthermore, this study discovered nine reasons of Marion Jola mixing code based on Hoffmann theory. 1) talking about a particular topic 13 times, 2) quoting somebody else 3 times, 3) being emphatic about something 1 time, 4) interjection 2 times, 5) repetition used for clarification 2 times, 6) intention for clarifying the speech content for interlocutor 4 times, 7) expressing group identity 5 times, 8) to soften or strengthen request or command 2 times, 9) because of lexical need 15 times and there is no data found concerning the reason to exclude other people when a comment is intended for only limited audience. The lack of equivalent lexicon between the languages is the most frequent cause of language mixing among bilingual or multilingual individuals and Marion Jola is one of them.
Keywords: sociolinguistics, code mixing, Marion Jola, YouTube Video
Topic: Optimization Research Based on Local Resources