Landslide Risk Reduction via Early Warning System in Sambirejo Village, Indonesia

Sambirejo Village, located in Wonosalam District, Jombang Regency, Indonesia, is an area with moderate to high landslide vulnerability, triggered by a combination of extreme rainfall, geological conditions, and land-use practices. This study aims to design and implement an Early Warning System (EWS) as a proactive measure for disaster mitigation and preparedness. The research methodology includes geological surveys and fracture mapping, landslide characterization, and the planning and installation of the EWS. The developed system comprises wireless sensors that monitor ground motion (extensometers), slope gradient (tiltmeters), and rainfall, all of which are connected to a real-time monitoring dashboard. The EWS successfully provides continuous data on ground motion and rainfall, which can be used to establish warning thresholds. For example, a “Warning” level can be activated if rainfall exceeds 50 mm/day, and an “Alert” level if the rate of ground motion exceeds 2 cm/day in combination with continuous rainfall. The highest alert, “Evacuation Warning,” is issued if ground motion shows exponential acceleration. This mechanism provides a scientific basis for village governments and the Regional Disaster Management Agency (BPBD) to make timely evacuation decisions. The development and implementation of the EWS have proven to be an effective solution for mitigating landslide risks at the study site. The application of this technology can significantly reduce the potential for loss of life and property damage. Furthermore, the implementation of the EWS enhances the preparedness of both the local community and the Jombang BPBD in responding to landslide threats, thereby reducing the risk of casualties and material losses

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Publication Details

Journal
RSF Conference Series Engineering and Technology
Published
2025-10-15
DOI
https://doi.org/10.31098/cset.v4i1.1018
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Landslide Risk Reduction via Early Warning System in Sambirejo Village, Indonesia

Nandra Eko Nugroho, Wana Kristanto, Eko Teguh Paripurno, I Putu Gema Bujangga Waisnawa et al.
RSF Conference Series Engineering and Technology
Data Mining and Machine Learning Applications
article

Landslide Risk Reduction via Early Warning System in Sambirejo Village, Indonesia

Nandra Eko Nugroho, Wana Kristanto, Eko Teguh Paripurno, I Putu Gema Bujangga Waisnawa, Awang Hendrianto Pratomo, Purbudi Wahyuni, Monica Warih Widi Krisanti
article en

Abstract

Sambirejo Village, located in Wonosalam District, Jombang Regency, Indonesia, is an area with moderate to high landslide vulnerability, triggered by a combination of extreme rainfall, geological conditions, and land-use practices. This study aims to design and implement an Early Warning System (EWS) as a proactive measure for disaster mitigation and preparedness. The research methodology includes geological surveys and fracture mapping, landslide characterization, and the planning and installation of the EWS. The developed system comprises wireless sensors that monitor ground motion (extensometers), slope gradient (tiltmeters), and rainfall, all of which are connected to a real-time monitoring dashboard. The EWS successfully provides continuous data on ground motion and rainfall, which can be used to establish warning thresholds. For example, a “Warning” level can be activated if rainfall exceeds 50 mm/day, and an “Alert” level if the rate of ground motion exceeds 2 cm/day in combination with continuous rainfall. The highest alert, “Evacuation Warning,” is issued if ground motion shows exponential acceleration. This mechanism provides a scientific basis for village governments and the Regional Disaster Management Agency (BPBD) to make timely evacuation decisions. The development and implementation of the EWS have proven to be an effective solution for mitigating landslide risks at the study site. The application of this technology can significantly reduce the potential for loss of life and property damage. Furthermore, the implementation of the EWS enhances the preparedness of both the local community and the Jombang BPBD in responding to landslide threats, thereby reducing the risk of casualties and material losses

RSF Conference Series Engineering and TechnologyVol. 4(1)
Universitas Pembangunan Nasional Veteran Yogyakarta (ID)
Openalex Percentile: Top 33%
Data Mining and Machine Learning Applications
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