Pemanfaatan Internet of Things untuk Monitoring Deteksi Tanah Longsor

Authors

  • Danang Setiya Raharja Program Studi Teknik Sipil, Universitas Wijaya Kusuma Surabaya Author https://orcid.org/0009-0004-7793-1054
  • Soepriyono Program Studi Teknik Sipil, Universitas Wijaya Kusuma Surabaya Author
  • Andaryati Program Studi Teknik Sipil, Universitas Wijaya Kusuma Surabaya Author
  • Nia Saurina Program Studi Informatika, Universitas Wijaya Kusuma Surabaya Author https://orcid.org/0000-0001-5715-9037
  • Aris Setiawan Indras Pratama Program Studi Informatika, Universitas Wijaya Kusuma Surabaya Author

Keywords:

Early warning, Internet of Things, Landslides, Microcontrollers

Abstract

Landslides are one of the most common natural disasters in Indonesia. This disaster can cause significant material losses and casualties. Therefore, a landslide monitoring system must be an early warning system. Prevention is one of the important steps to reduce the negative impact of landslides. The existing landslide early warning system still needs improvement, including low accuracy and slow response in providing information. This research aims to create a product, which we have named DinSor, as a landslide early warning system by utilizing the Internet of Things (IoT). The proposed system uses IoT-based sensors to detect changes in ground conditions, including soil movement through ultrasonic sensors and the degree of soil water content through soil mixture sensors. The data generated by these sensors is then displayed on the website as graphs and numbers for analysis. The trial results show that the developed system has advantages in detecting potential landslides. The system's response in providing information has also proven to be accurate and precise, with warning times shorter than previous systems. When the sensor indicates a potential landslide, a warning message can be sent to the local regional disaster management agency via WhatsApp.

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Published

16/10/2024

How to Cite

[1]
“Pemanfaatan Internet of Things untuk Monitoring Deteksi Tanah Longsor”, jse, vol. 9, no. 4, Oct. 2024, Accessed: Dec. 12, 2024. [Online]. Available: http://jse.serambimekkah.id/index.php/jse/article/view/567

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