Transitivity Patterns in Cisarua Landslide Coverage by The Jakarta Post: A Corpus-Assisted Analysis - Yulizar Komarawan; Zewitra Zewitra; Khoirun Nisaa' Arnoi; Novi Yuliawati (Jurnal Bahasa Inggris Terapan, 2026)
This study investigates the representation of the Cisarua landslide in news media through corpus-assisted transitivity analysis within the framework of Systemic Functional Linguistics. It focuses on identifying the dominant processes, participants, and circumstances employed in the news reports to construct disaster representations. A qualitative approach using discourse analysis was employed in this study. The data consisted of news reports about the Cisarua landslide published in The Jakarta Post from 25 to 31 January 2026. The collected news texts were compiled into a corpus consisting of 5,601 words and analyzed using UAM CorpusTool. The analysis involved clause segmentation, transitivity annotation, frequency calculation, and concordance or Key Word in Context analysis. The findings identified 1,799 transitivity elements, comprising participants, processes, and circumstances. Participants were the most frequent category with 921 occurrences (51.2%), followed by processes with 578 occurrences (32.1%), and circumstances with 300 occurrences (16.7%). The analysis also revealed the dominance of several participant roles and process types in the corpus. Material processes appeared most frequently with 339 occurrences (18.8%), while relational and verbal processes were also commonly identified in the news reports. Among the participant roles, Goal was the most frequent (28.7%), followed by Actor (18%), indicating that the reports foregrounded affected entities and highlighted the actions of agents. In addition, location circumstances were the most dominant circumstance category, with 207 occurrences (11.5%). The findings show that the disaster news reports primarily emphasized disaster events, institutional responses, affected entities, and landslide-related contextual information.