PERANCANGAN SISTEM DETEKSI DINI BANJIR BERBASIS IOT DENGAN PENDEKATAN MULTI-SENSOR DAN NOTIFIKASI WHATSAPP
Abstract
Pemantauan ketinggian air secara manual mengakibatkan keterlambatan informasi mitigasi banjir. Penelitian ini merancang sistem deteksi tingkat risiko banjir berbasis Internet of Things (IoT) dengan pendekatan multi-sensor menggunakan metode Prototype. Mikrokontroler ESP32 difungsikan sebagai unit pemroses utama yang terintegrasi dengan sensor ultrasonik, raindrop, dan water flow YF-S201. Data sensor dikirimkan via protokol HTTP POST ke basis data MySQL, divisualisasikan pada dashboard Laravel, dan dinotifikasikan via WhatsApp. Pengujian fungsionalitas sensor ultrasonik menghasilkan Mean Absolute Error (MAE) 1,10 cm dan error rate 0,91%. Integrasi multi-sensor berhasil mengklasifikasikan status Normal, Waspada, dan Bahaya berdasarkan ambang batas Siaga lokal secara real-time dengan jeda transmisi dashboard 10 detik. Hasil penelitian membuktikan sistem multi-sensor mampu meningkatkan efektivitas pemantauan hidrometeorologi secara akurat.
Manual water level monitoring results in delayed flood mitigation information. This study designed an Internet of Things (IoT)-based flood risk detection system with a multi-sensor approach using the Prototype method. The ESP32 microcontroller functioned as the main processing unit integrated with ultrasonic, raindrop, and YF-S201 water flow sensors. Sensor data was transmitted via HTTP POST protocol to a MySQL database, visualized on a Laravel dashboard, and notified via WhatsApp. Ultrasonic sensor functional testing resulted in a Mean Absolute Error (MAE) of 1.10 cm and an error rate of 0.91%. Multi-sensor integration successfully classified Normal, Alert, and Danger statuses based on local Alert thresholds in real-time with a 10-second dashboard transmission delay. The research results prove the multi-sensor system can accurately improve hydrometeorological monitoring effectiveness.
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