Skip to content
Research Article Open access CC BY 4.0

Application of a Web-Based Landslide Mitigation Information System (Sensor-Ku) in Kalongan Village Semarang, Central Java

Zahra Yulia Putri, Salsa Bella Anjani, Alika Pevi, Dilean Zeva, Sri Hapsari Wahyuningtyas, Aprelia Dwi Hapsari, Ika Pantiawati, Hugi Cherlyawati, Slamet Isworo

Journal of Geography, Environment and Earth Science International · pp. 138–146 · Published 14 Nov 2023

10.9734/jgeesi/2023/v27i11730

Abstract

Background and Objectives: Kalongan is one of the villages in Ungaran District with a potential landslide risk of 2% of its territory. Landslides occur along roadways and in residential areas, endangering the environment and damaging the infrastructure. A web-based early warning system application is the Landslide Early Warning System (Sensor-Ku) which is applied at the research location. This study intends to detect and provide real-time information on the likelihood of landslides, specifically to the people of Kalongan Village. Methods: This research creates a web-based monitoring and early warning system, as well as its implementation on an experimental microservice architecture, to provide landslide risk mitigation information to Kalongan residents. Results: According to the research, the landslide early warning system (LEWS) provides a solution by integrating many modules, such as recording dynamic variability, handling multi-scale data sets, extracting important trigger information about the onset of potential landslides, and broadcasting multi-level data. warning. This research also combines a real-time landslide early warning system.  Conclusion: The Landslide Early Warning System (LEWS) Program is effective in reducing the risk of landslides. Some of the issues found when running the program include the costs of maintaining the landslide early warning equipment, which must be managed by the Kalongan village community.

Disaster mitigation landslide early warning system (LEWS) potential risk Kalongan Village

References (19)

  1. 1 Disaster Resilience Indicators for Benchmarking Baseline Conditions [DOI]
  2. 2 Geographical landslide early warning systems [DOI]
  3. 3 Environmental Management Strategy in Mining Activities in Forest Area Accordance with the Based Justice in Indonesia
  4. 4 The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management [DOI]
  5. 5 Disaster preparedness of local governments in Panay Island, Philippines [DOI]
  6. 6 Landslides: An emerging model for ecosystem and soil chronosequence research [DOI]
  7. 7 Joint pre- and post-disaster planning to enhance the resilience of critical infrastructures [DOI]
  8. 8 Integrated community emergency management and awareness system: A knowledge management system for disaster support [DOI]
  9. 9 Negotiated participatory action research for multi-stakeholder implementation of early warning systems for landslides [DOI]
  10. 10 Challenges of Higher Educational Documentary Institutions in Supporting Merdeka Belajar Kampus Merdeka Program [DOI]
  11. 11 Capacity Enhancement Indicators [DOI]
  12. 12 Estimation of landslide prone zones around the Semarang Fault based on by combining the slope stability analysis and HVSR microtremor methods [DOI]
  13. 13 Analysis of Environmental Vulnerability in The Landslide Areas (Case Study: Semarang Regency) [DOI]
  14. 14 Living with Landslides: Perceptions of Risk and Resilience in Far West Nepal [DOI]
  15. 15 Regional Government Authority in the Implementation of Natural Disaster Management [DOI]
  16. 16 Institutional Strengthening and Capacity Building: A Case Study in Indonesia [DOI]
  17. 17 The Landslide Handbook - A Guide to Understanding Landslides [DOI]
  18. 18 The Nature of Landslide Hazard Impact [DOI]
  19. 19 Real-time Landslide Monitoring, Detection and Early Warning System for Tangni Landslide [DOI]

Cited by 0

No indexed citations yet.

Related research

Article metrics

Real usage data collected on this platform.

30

Page views

0

PDF downloads

4

Outbound clicks

0

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.