@phdthesis{repoupi144373,
          school = {Universitas Pendidikan Indonesia},
           title = {PERANCANGAN EARLY WARNING SYSTEM (EWS) UNTUK DETEKSI DINI BENCANA BANJIR BERBASIS INTERNET OF THINGS TERINTEGRASI PLATFORM MOBILE APPS DAN WEBSITE},
            year = {2025},
            note = {ID SINTA Dosen Pembimbing:
Resa Pramudita: 6688224},
           month = {July},
             url = {https://repository.upi.edu/},
        abstract = {Banjir merupakan bencana alam yang kerap melanda wilayah Indonesia, terutama di daerah rendah dan sekitar aliran sungai. Sistem peringatan dini (Early Warning System/EWS) dibutuhkan untuk memberikan informasi potensi banjir secara cepat dan akurat. Penelitian ini bertujuan merancang sistem EWS berbasis Internet of Things (IoT) yang terintegrasi dengan aplikasi mobile dan website guna meningkatkan kesiapsiagaan masyarakat dan pemerintah. Sistem dirancang menggunakan mikrokontroler ESP32 yang terhubung dengan sensor ultrasonik, sensor hujan, dan sensor aliran air untuk memantau tinggi muka air, intensitas curah hujan, serta debit air secara real-time. Data dikirim ke Firebase dan ditampilkan melalui antarmuka aplikasi Android dan platform web.
Pengembangan sistem dilakukan dengan metode Rapid Application Development (RAD) dan diuji menggunakan pengujian alpha dan beta. Hasil pengujian menunjukkan sistem mampu memberikan notifikasi otomatis kurang dari 5 detik setelah mendeteksi kondisi rawan. Uji beta yang melibatkan 100 warga menunjukkan bahwa 91\% responden merasa sistem mudah digunakan dan 94\% menyatakan informasi yang diberikan sangat membantu dalam mengambil tindakan mitigasi. Sistem ini terbukti efektif dalam mempercepat penyampaian informasi kebencanaan dan meningkatkan respon masyarakat terhadap potensi banjir.

Floods are one of the most frequent natural disasters in Indonesia, especially in lowland areas and river basins. An Early Warning System (EWS) is essential for delivering flood risk information quickly and accurately. This study aims to design an IoT-based Early Warning System integrated with a mobile application and website platform to enhance disaster preparedness for both communities and local authorities. The system is built using an ESP32 microcontroller connected to ultrasonic, rainfall, and water flow sensors to monitor water levels, rainfall intensity, and discharge in real-time. Data is transmitted to Firebase and displayed through an Android application and web interface.
The system was developed using the Rapid Application Development (RAD) method and evaluated through alpha and beta testing. The results show that the system can automatically send alerts in under 5 seconds after detecting flood indicators. Beta testing involving 100 community respondents revealed that 91\% found the system easy to use, and 94\% stated that the information provided was helpful in taking preventive measures. The system has proven effective in accelerating disaster information delivery and improving community responsiveness to flood threats.},
          author = {Luthfi Maulana, - and Resa Pramudita, -},
        keywords = {Early Warning System, Internet of Things, ESP32, Firebase, Banjir.

Early Warning System, Internet of Things, ESP32, Firebase, Flood.}
}