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All Journal Jurnal Samudra Geografi International Journal of Geography, Social, and Multicultural Education (IJGSME) Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian
Rosyid Shidiq Hidayatulloh
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Humanities Earth & Planetary Sciences Education Environmental Science Social Sciences Other

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PERAN STRATEGIS PEMUDA DALAM MITIGASI BENCANA DI INDONESIA: A SYSTEMATIC LITERATURE REVIEW Yonatan Yolius Anggara; Dyah Respati Suryo Sumunar; Nursida Arif; Rosyid Shidiq Hidayatulloh
Jurnal Samudra Geografi Vol 8 No 2 (2025)
Publisher : Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jsg.v8i2.11383

Abstract

Abstract: Indonesia, as a disaster-prone country, requires effective disaster mitigation efforts. Youth participation in disaster mitigation has increased significantly over the past few decades, marked by their involvement in various preparedness activities and policy advocacy. This study aims to identify, analyze, and summarize the contributions of youth in disaster mitigation, as well as explore the supporting factors and challenges they face, through a systematic literature review. The findings indicate that youth play an important role across several scales: individual scale, pre-disaster, during disaster, post-disaster, and community scale. The factors driving youth involvement include system support, individual capacity, as well as motivation and active participation. However, there are challenges that hinder youth engagement, such as limited resources, system weaknesses, and a lack of awareness and participation from the community. This study recommends developing community-based disaster mitigation and utilizing social media as a campaign tool. These findings underscore the importance of empowering youth to play an active role in disaster mitigation in a more structured and sustainable manner.
Analyzing Public Sentiment on The 2024 'Galodo' Disaster Using Natural Language Processing (NLP) Yonatan Yolius Anggara; Dyah Respati Suryo Sumunar; Nurul Khotimah; Rosyid Shidiq Hidayatulloh
International Journal of Geography, Social, and Multicultural Education Vol. 3 No. 2 (2025): 1 October 2025
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ijgsme.v3n2.p1-12

Abstract

This study investigates public sentiment during flash floods (Galodo) in West Sumatra by analyzing Twitter data using Natural Language Processing (NLP) via text2data.com. The research applies Latent Dirichlet Allocation (LDA) for topic modeling to identify dominant themes in public discussions. Findings indicate that 97.9% of sentiments expressed were positive, primarily centered on disaster impacts, situational updates, flood causes, and community reactions to government-led disaster management efforts. The study underscores social media’s influence in shaping public discourse during crises. A key contribution of this research is its integration of LDA-based topic modeling with sentiment analysis, specifically targeting Twitter discussions on flash floods in West Sumatra. This methodological approach offers valuable insights into how communities communicate and perceive natural disasters through digital platforms. The results suggest that social media fosters constructive dialogue during environmental emergencies, which can inform crisis communication strategies and enhance disaster response policies. By examining public sentiment and discussion trends, the study highlights the potential of social media analytics for improving disaster management frameworks. The predominance of positive sentiments reflects community resilience and engagement, providing policymakers with data-driven perspectives to optimize emergency responses. This research advances understanding of digital communication patterns during disasters, demonstrating the utility of NLP and topic modeling in crisis-related social media analysis.Ultimately, the findings emphasize the importance of leveraging social media data to gauge public sentiment, enabling more effective disaster communication and policy adaptations in vulnerable regions like West Sumatra.
A Regime-Aware Deep Learning for Long-Term Hydrometeorological Disaster Forecasting (2008–2029): A PELT-LSTM Framework Applied to Indonesia Yonatan yolius anggara; Rosyid Shidiq Hidayatulloh; Nurul Khotimah; Bambang Syaeful Hadi; Suhadi Purwantara
Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Vol. 23 No. 1 (2026): Volume 23 No 1, June 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jg.v23i1.49495

Abstract

Indonesia's escalating hydrometeorological disaster frequency demands robust predictive frameworks capable of capturing non-stationary climate dynamics. This study aimed to analyze statistical correlations among disaster types and generate long-term flood frequency projections using advanced computational methods applied to national disaster data. Pearson correlation analysis was first conducted to quantify inter-disaster relationships, revealing strong associations between extreme weather, floods, and landslides (r = 0.79–0.86), alongside inverse relationships with drought. The Pruned Exact Linear Time (PELT) algorithm subsequently identified three significant regime shifts in 2012, 2017, and 2022, confirming the progressive non-stationarity of Indonesia's disaster patterns. A Long Short-Term Memory (LSTM) deep learning model was then trained on these regime-structured data to generate predictive forecasts. The model achieved high directional accuracy, successfully capturing the 2025 peak and 2026 decline, with an RMSE of 816.67 and MAPE of 43.77%. Projections for 2027–2029 estimate flood events reaching 2,278, 2,542, and 2,021 incidents respectively, indicating a sustained high-frequency disaster regime that necessitates urgent adaptive infrastructure and evidence-based climate resilience planning.
Co-Authors Bambang Syaeful Hadi Dyah Respati Suryo Sumunar Nursida Arif NURUL KHOTIMAH Suhadi Purwantara Yonatan yolius anggara Yonatan Yolius Anggara