Pengembangan Sistem Informasi Early Warning System Banjir Berbasis Internet of Things Menggunakan REST API dan WhatsApp Gateway

Afriza Akhid Khoiruddin (Universitas Muria Kudus, Kudus)

JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Vol 7 No 4 (2026): July 2026

Flooding is one of the most frequent natural disasters caused by increasing rainfall intensity and overflowing rivers, highlighting the need for a monitoring system capable of providing timely and accurate information. This study aims to develop an Internet of Things (IoT)-based Early Warning System (EWS) for flood monitoring that enables real-time water level observation and automatic early warning notifications. The proposed method involves the design of a hardware system using the A02YYUW ultrasonic sensor and ESP32 microcontroller, the development of a REST API-based backend using PHP Native and MySQL, and a web-based monitoring dashboard integrated with the WhatsApp Gateway through the Fonnte API. Water level data collected by the sensor are processed using a .-based classification method to determine three alert levels: NORMAL, ALERT, and DANGER. The processed data are then transmitted to the server in JSON format via a Wi-Fi network. Subsequently, the backend validates the authentication token, stores the data in the database, displays real-time information on the monitoring dashboard, and automatically sends WhatsApp notifications when the water level reaches the ALERT or DANGER status. The experimental results demonstrate that the proposed system operates successfully in an integrated manner, covering sensor data acquisition, data transmission, database storage, dashboard visualization, and automatic notification delivery. The A02YYUW ultrasonic sensor achieved an average measurement error of 0.89%, indicating high measurement accuracy and stability. Therefore, the developed system can serve as an effective solution for real-time flood monitoring and early warning, providing fast, accurate, and easily accessible information to the community. The main contribution of this study is the development of an integrated flood early warning system that combines the waterproof A02YYUW ultrasonic sensor, ESP32 microcontroller, PHP Native-based REST API, web-based monitoring dashboard, token-based authentication, and WhatsApp Gateway into a unified architecture for secure real-time monitoring and early warning dissemination.