Rancang Bangun Internet of Things (IoT) Monitoring Curah Hujan menggunakan Kalibrasi Regresi Linear

Abstract

Rainfall is one of the most important weather parameters to monitor because it affects various activities, especially in the agricultural sector. Manual rainfall measurement has limitations in terms of real-time monitoring and automatic data storage. Therefore, a rainfall monitoring system capable of measuring and transmitting data in real time is required. This study aims to design and develop an Internet of Things (IoT)-based rainfall monitoring system using a tipping bucket sensor calibrated with a linear regression method to improve measurement accuracy. The research method consisted of hardware design, software implementation, tipping bucket sensor calibration, and system testing. The developed system utilizes an ESP32 microcontroller as the main controller, a DHT22 sensor to measure temperature and humidity, a tipping bucket sensor to measure rainfall, a LoRa module for data communication, and Firebase Realtime Database for data storage. Sensor calibration was performed using a linear regression method based on the relationship between the number of tips and the reference water volume. The results showed that linear regression analysis produced the equation Y = 1.4276X − 0.1671 with a coefficient of determination (R²) value of 0.9993. The equation was implemented in the system to improve rainfall measurement accuracy. The testing results demonstrated that the system was capable of measuring temperature, humidity, and rainfall, as well as transmitting data to Firebase in real time. Furthermore, the tipping bucket sensor measurements were found to be close to the reference water volume values. Therefore, the developed system can be used as an alternative IoT-based weather monitoring system capable of providing more accurate and real-time rainfall data.