MACHINE LEARNING SMART PACKAGING PENGIRIMAN TELUR AYAM BERBASIS INTERNET oF THINGS (IoT) MENGGUNAKAN ALGORITMA C.45 DENGAN PLATFORM THINGSPEAK

Abstract

In the era of Industry 4.0, the integration of Machine Learning and the Internet of Things (IoT) plays a crucial role in enhancing the efficiency and safety of logistics processes. This research aims to develop a Smart Packaging system for the shipment of chicken eggs utilizing Machine Learning with the C.45 algorithm and IoT-based on the ThingSpeak platform. The system integrates Node-MCU (ESP8266) as the central processing unit, the DHT11 sensor to monitor temperature and humidity within the packaging, the Vibration Sensor SW-420 to detect potential damage to eggs during shipment, and the Unblock Neo6m-V2 GPS Module for real-time location tracking. The C.45 algorithm is employed to process data and make intelligent decisions regarding the condition of the eggs and the shipping environment. Sensor data is collected and transmitted to the ThingSpeak platform through the Wi-Fi connection provided by Node-MCU. The C.45 algorithm is applied to analyze the data, provide predictions regarding egg conditions, and make decisions for further actions during the shipping process. Experiments were conducted to evaluate the system's accuracy using RapidMiner software. The results indicate that the system is capable of predicting egg conditions with a high level of accuracy, enabling responsive actions to situations that may affect egg quality during shipment. The implementation of Machine Learning and IoT technologies in this chicken-egg shipping system is expected to enhance the quality of delivered products, optimize logistical processes, and provide an intelligent solution to ensure the sustainability of the food product supply chain.