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Journal : The Indonesian Journal of Computer Science

Analisis Dinamika Tren Otoritas Keagamaan: Studi Kasus di Twitter Indonesia Tahun 2009-2019 Naila Nabiha Qonita; Taufik Edy Sutanto; Nur Inayah
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3862

Abstract

Religious authority refers to individuals vested with governance over religious matters, such as kiai, ulama, and ustaz within the context of Islamic faith. In the age of social media, where freedom of expression prevails, anyone can initiate discussions on various topics, including religion. However, this freedom often raises doubts about truthfulness or validity of opinions concerning religious topics because not all information originates from credible religious authorities. This study analyzes trend dynamics of religious authority in discussions about Islam on Twitter between 2009 and 2019, using Katz centrality and Laplacian centrality. According to both methods, the findings indicate that dominance in religious conversations tends not to be held by religious authorities, with the average percentage of religious authority appearances only 14.24% in Katz centrality and 12.42% in Laplacian centrality. Results of this study are intended to serve as reference for government policy-making related to religious moderation education to public.
Analisis Dinamika Komunitas Warganet Twitter Terkait Diskusi Agama Islam Tahun 2009-2019 Fillah Arjuna, Ahmad Salik; Nur Inayah; Taufik Edy Sutanto
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4170

Abstract

Twitter, as a popular social media in Indonesia, is a platform for users to form communities and share information, including about Islam. Opinions generated through this platform can change perceptions about the teachings and practices of Islam in Indonesia. This study aims to understand the structure and evolution of the Muslim community on Twitter through an analysis of community dynamics during 2009-2019. The data was transformed into a graph-shaped network and analyzed using two community detection methods: Louvain and Leiden. Content analysis such as n-grams, hashtags and word clouds were applied to identify the topics of the 3 largest communities. Leiden was shown to produce a higher average modularity value: 0.837, compared to Louvain: 0,833. This research provides deep insights into the community dynamics and discussion topics of Islam in Indonesia on social media, which can serve as a basis for policy makers and academics in managing social and religious issues.