Rozak, Mohammad Abdul Rozak (2024) Rancang Bangun Sistem Monitoring Kelembapan Tanah, Getaran, Dan Pergeseran Guna Early Warning Adanya Bencana Longsor. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Alat monitoring tanah longsor ini dikembangkan untuk mengatasi masalah kurangnya sistem pemantauan real-time yang dapat mendeteksi getaran, pergeseran, dan kelembapan tanah sebagai indikator awal terjadinya tanah longsor. Penelitian terdahulu telah menghasilkan berbagai sistem monitoring dengan sensor yang berbeda, namun seringkali memiliki keterbatasan dalam integrasi data dan ketahanan perangkat di lapangan. Kelemahan dari penelitian terdahulu mencakup kurangnya ketahanan terhadap kondisi lingkungan yang keras dan keterbatasan dalam transmisi data yang andal. Solusi dalam penelitian ini melibatkan penggunaan sensor MPU6050, sensor kelembapan tanah kapasitif, dan modul SIM800L yang terintegrasi dengan mikrokontroler STM32, serta pemanfaatan panel surya untuk memastikan suplai daya yang berkelanjutan. Hasil proyek akhir menunjukkan bahwa sistem yang dirancang mampu memberikan performa yang andal dalam mendeteksi potensi tanah longsor yaitu akurasi sebesar 93.87% dan memberikan peringatan dini secara efektif dengan latensi maksimal 5 detik, sehingga dapat mendukung upaya mitigasi bencana secara optimal.
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This landslide monitoring tool was developed to overcome the problem of the lack of a real-time monitoring system that can detect vibrations, shifts, and Soil Moisture as early indicators of landslides. Previous research has produced various monitoring systems with different sensors, but often have limitations in data integration and device durability in the field. The weaknesses of previous research include the lack of durability against harsh environmental conditions and limitations in reliable data transmission. The solution in this study involves the use of the MPU6050 sensor, a capacitive Soil Moisture sensor, and a SIM800L module integrated with an STM32 microcontroller, as well as the use of solar panels to ensure continuous power supply. The results of the final project show that the designed system is able to provide reliable performance in detecting potential landslides, namely an accuracy of 93.87% and providing effective early warning with a maximum latency of 5 seconds, so that it can support disaster mitigation efforts optimally.
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