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Produk Jurnalisme Data di Media Digital pada Masa Pandemi Yusuf, Ainun; Yusuf, Ainun Jariah; Ahmad, Nyarwi
IPTEK-KOM : Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi Vol 25 No 2 (2023): Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi)
Publisher : BPSDM Kominfo & Prodi Ilmu Komunikasi UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/iptekkom.25.2.2023.187-204

Abstract

The localization of data journalism in Indonesia has also produced data-driven news. Localization and the context of COVID-19 can encourage the formation of data-driven news different from the investigative and complex nature of data journalism products. This article aims to assess the news elements of data journalism products in 317 data-driven COVID-19 news in online media in Indonesia, namely Katadata.co.id, Kompas.id, and Tirto.id. The analytical framework used in this study is based on the concept of news elements of data journalism products (Zamith 2019; Ojo and Heravi 2018; Loosen, Reimer, and De Silva-Schmidt 2020). The results of the quantitative content analysis show that data-driven COVID-19 news in the three online media in Indonesia is characterized by news sources that tend to rely on pre-analyzed open sources, less complex data visualization and interactive features, and weak implementation of source and process transparency. This study concludes that the data journalism developed in Indonesia during the COVID-19 pandemic is the daily data journalism model shaped by the availability of easily accessible and free data and software.