Analysis of the Translation Accuracy and Acceptability of Dependent Clauses in Complex Sentences in BBC News World News Articles

This study aims to analyze the types of complex sentences and the translation accuracy and acceptability in BBC News’ World News. Complex sentences are classified based on Oshima and Hogue (2006) framework into adverbial, adjective, and noun clauses. The translation quality is evaluated using Nababan et al.'s (2012) assessment model through a Focus Group Discussion (FGD) within a descriptive qualitative approach. The results show that of the 85 complex sentence data points, the most dominant type is the adjective clause (35 data, 41,18%), followed by noun clauses (25 data, 29,41%), adverbial clauses (24 data, 28,24%), and (1,18%) containing both a noun clause and an adverbial clause. Regarding accuracy, 45 data points (52,94%) are accurate, 38 data points (44,71%) as less accurate, and 2 data points (2,35%) as inaccurate, yielding an average accuracy score of 2,51. For acceptability, 68 data points (80%) are acceptable, 17 data points (20%) as less acceptable, and none as not acceptable, yielding an average score of 2,8. These findings indicate that adjective and noun clauses tend to yield higher translation quality scores due to the availability of direct structural equivalents in Indonesian, while adverbial clauses present the most significant challenges owing to the nuanced relational meanings conveyed by subordinating conjunctions. Thus, the translation quality of complex sentences in BBC News is generally satisfactory, though greater attention to source text fidelity remains necessary, particularly in the translation of adverbial clauses.