Identifying the Level of Data Journalism Literacy and Skills of Local Media Journalists in Indonesia - Suherman, Ansar; Maulana, Harry Fajar; Lawelai, Herman (Jurnal The Messenger, 2024)
Introduction: Datafication still plagues Indonesian journalists, especially local ones, skewing news validity and neutrality. Indonesian journalists from 13 local media were surveyed and interviewed for this study. This study relied on several studies that suggest journalists may deliver more accurate, objective, and unbiased news by expanding their datafication capacity. As digital technology advances and social media spreads misinformation, it becomes critical. Methods: Mixed-methods experimentation and triangulation. Indonesia has 13 native media representing its diversity. Using regional media, this study can illustrate data journalism literacy levels in different locations, including those with differing technology and education. We chose material based on data journalism approaches including data visualization, infographics, and data-driven reporting. This ensures study-relevant respondents. Findings: Indonesian media's poor data literacy has a big impact. Data-driven journalism in local media is poor due to data analysis incompetence. Access and chances for journalists to develop data skills are major issues. Clearly, formal training is needed. Another factor is local media's focus on reporting speed over data analysis. Lack of technology and institutional support hinders local journalist data literacy projects. Originality: Previous studies on Indonesian journalists' datafication knowledge and abilities are scarce and fragmented. Despite data journalism's growing popularity in newsrooms and academic status, comprehensive study is needed to define it.