LOGICO SEMANTIC RELATION ANALYSIS OF CLAUSE COMPLEX IN CNN NEWS

Abstract

This study deals with Logico Semantic Relation in CNN News text. The objectives of this study is to discover the types of Logico Semantic Relation of Clause Complex Used in CNN News and to know the dominant type  of logical semantic systems interpreted in CNN News.  The researcher applied qualitative approach and used content analysis design.  The technique of collecting data was documentation. The data of the research was Logico Semantic Relation meanwhile the news text of CNN was as the data source of the research.  The data were analyzed by data reduction, data display, and conclusion drawing/verification. The findings showed that (1) The types of Logico Semantic Relation used in the five news texts of CNN were Expansion (Elaboration, Enhancement, and Extension) and Projection (Locution). The total number of Logico Semantic Relation was 201 or 100% which consisted of 153 items or 76,10% of expansion and 48 items or 23,90% of projection.  (2)  Expansion (Elaboration) was the most dominant type among all kinds of Logico Semantic Relation which appeared in 92 times or 45,80%. The second rank was projection (locution) that was 48 times or 23,90%. The third position was expansion (Enhancement) which occurred 33 times or 16,40%. Meanwhile, Expansion (Extension) appeared 28 times or 13,90%, and the last one was projection (idea), which had no percentage (0 times or 0.00%). The researcher concludes that there are two types of Logico Semantic Relation used in the CNN news text, those are Expansion (Elaboration, Enhancement, and Extension) and Projection (Locution). The most dominant type of Logico Semantic Relation that appears in the text is Expansion (Elaboration).