Penelitian ini merekonstruksi Sistem Komunikasi Krisis dan Risiko Kebencanaan di Media Sosial dalam Pengurangan Risiko Bencana Tsunami Vulkanik di Indonesia. Riset difokuskan pada kasus Tsunami Selat Sunda pada tahun 2018 yang menelan 426 korban jiwa. Tragedi ini disebabkan oleh lemahnya situational awareness akibat ketidaksinkronan kebijakan peringatan dini tsunami vulkanik antar lembaga, lemahnya crisis response masyarakat di media sosial, dan rumor yang berkembang akibat kesenjangan digital masyarakat terdampak bencana. Metode penyelesaian masalah menggunakan Soft Systems Methodology (SSM) Multi Method, dengan penggunaan Social Network Analysis pada SSM tahap ke dua untuk memperkaya Rich Picture dan Textual Network Analysis pada SSM tahap ke lima untuk mempertajam perbandingan model konseptual dengan dunia nyata. Survei dengan instrumen berplatform Open Data Kit dilakukan tehadap 100 penduduk desa yang terkena dampak langsung atau tidak langsung tsunami menghasilkan visualisasi crisis sensing network selama bencana dari perspektif publik. Wawancara mendalam dengan 22 orang yang mewakili 15 pemangku kepentingan nasional dan lokal utama menghasilkan crisis sensing network dari perspektif pemerintah. Riset ini merekomendasikan beberapa hal. Pertama, rekomendasi secara akademis, yaitu mengintroduksi collective intelligence sebagai pengembangan dari Social Mediated Crisis Communication dengan kolaborasi pengelolaan media sosial antar lembaga dan partisipasi masyarakat dalam komunikasi risiko dan krisis khususnya peringatan dini bencana. Kedua, kontribusi secara metodologis yaitu elaborasi varian baru SSM multi method yang memperkaya penerapan SSM dalam riset berbasis digital. Ketiga, rekomendasi secara praktis/ sosial; mengusulkan amandemen UU kebencanaan No.24/2007 dengan menambahkan tsunami non-tektonik (vulkanik) ke dalam tipe krisis/bencana tsunami; dan mempertegas peran institusi TNI dan Polri dalam komunikasi risiko dan krisis.
This study reconstructs the Crisis Communication System on Social Media for Disaster Risk Reduction of Volcanic Tsunami Disaster in Indonesia. Research is focused on the case of the Sunda Strait Tsunami in 2018 which claimed 426 lives. This tragedy was caused by weak situational awareness due to the out-of-synchronization of volcanic tsunami early warning policies between institutions, the weak crisis response of the community on social media, and rumors that developed due to the digital divide of the community affected by the disaster. The problem solving method uses the Soft Systems Methodology (SSM) Multi Method, with the use of Social Network Analysis in the second stage of SSM to enrich the Rich Picture and Textual Network Analysis in the fifth stage of SSM to sharpen the comparison of conceptual models with the real world. The survey using the Open Data Kit platform instrument was conducted on 100 villagers who were directly or indirectly affected by the tsunami, resulting in a visualization of the crisis sensing network during the disaster from a public perspective. In-depth interviews with 22 people representing 15 key national and local stakeholders produced a crisis sensing network from a government perspective. This research recommends several things. First, academic recommendations, namely introducing collective intelligence as a development of Social Mediated Crisis Communication with collaborative social media management between institutions and community participation in crisis communication, especially disaster early warning. Second, the methodological contribution, namely the elaboration of a new multi-method SSM variant which enriches the application of SSM in digital-based research. Third, practical/social recommendations; proposed an amendment to the Law on Disasters No.24/2007 by adding a non-tectonic (volcanic) tsunami to the type of tsunami crisis/disaster; and reinforce the role of TNI and Polri institutions in crisis communication.Keywords: Social Media, Crisis Communication, Volcanic Tsunami, SSM Multi-Method, Social Network Analysis (SNA), Textual Network Analysis (TNA) |
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