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Growing Science » Authors » Bengkel Bengkel

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1.

Strengthening disaster mitigation of mount Sinabung through the integration of local wisdom and social resilience: a participatory study in Karo Regency Pages 169-180 PDF Download PDF

Authors: Riri Rezeki Hariani, Badaruddin Badaruddin, Bengkel Bengkel, Irmayani Irmayani

doi 10.5267/j.jpm.2025.10.002

🔑 Keywords: Disaster Mitigation, Local Wisdom, Social Resilience, Mount Sinabung, Karo Community

Abstract:
This study aims to develop a disaster mitigation model for the eruption of Mount Sinabung based on the integration of local wisdom from the Karo community and social resilience theory. The recurring eruptions since 2010 have resulted in complex socio-ecological impacts, yet existing mitigation approaches have tended to be technocratic and lacked contextual relevance. This research employs a descriptive qualitative approach within a constructivist paradigm, relying on in-depth interviews, observation, documentation, and Focus Group Discussions (FGDs) as data collection techniques. Data analysis is conducted using the Miles, Huberman, and Saldana model, encompassing data reduction, presentation, and conclusion drawing. The main finding of this study is the formulation of the RiRi Model, which comprises four components: Respect (recognition of local knowledge), Initiation (active community participation), Runggun (optimization of traditional social networks), and Integration (collaboration between local and modern approaches). This model offers a more inclusive mitigation strategy, rooted in the cultural values of the Karo community, and capable of holistically strengthening community resilience. The study also reveals that local wisdom practices such as aron, runggu, and the use of jambur hold strategic potential as community-based disaster mitigation instruments. By synergizing social, cultural, and technical dimensions, the RiRi Model is expected to serve as an alternative framework for national disaster mitigation policy that is more adaptive, sustainable, and responsive to local contexts.
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Journal: JPM | Year: 2026 | Volume: 11 | Issue: 1 | Views: 559

 

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