Klasifikasi Telur Ayam Berbasis IoT Menggunakan Sensor Cahaya dan Sensor Berat dengan Notifikasi Real-Time Melalui Telegram

The manual process of classifying chicken eggs remains a challenge in the poultry industry because it is inefficient, inconsistent, and requires high operational costs. This study aims to develop an automatic chicken egg classification system based on the Internet of Things (IoT) using a light sensor (LDR) to detect quality and a weight sensor (Load Cell HX711) to measure egg mass in real-time. By using the ESP32 microcontroller as the main controller, the sensor data are processed and automatically sent through the Telegram application. The methodology used is an experimental method that includes hardware design, software development, and direct system testing. The results of this study show that the system is able to detect and classify eggs automatically with stable performance. The load cell sensor has high accuracy with a weighing difference of less than 1 gram, while the LDR sensor is able to detect egg quality with fairly high accuracy, and the servo motor successfully separates eggs based on quality and weight according to the system logic. The integration of hardware and software runs optimally, where Telegram notifications can send classification result data in real-time within only 1–3 seconds. Although the system is still a prototype, testing proves that the use of IoT is effective in improving the efficiency of the chicken egg sorting process.