IoT Innovation System and Environmental Classification of Hermetia Illucens Larvae in Malang City - Afrianto, Eko; Ursaputra, Lionardi (Badan Perencanaan Pembangunan Kota Malang, 2024)
This study presents an innovative intelligent system based on the Internet of Things (IoT) designed to monitor and classify the environmental conditions of Hermetia illucens larvae in real-time. This system integrates several sensors to measure important parameters such as temperature, humidity, and media height, which are then processed using the K-Nearest Neighbor (K-NN) algorithm. The K-NN algorithm groups environmental data into three categories: optimal, moderate, and poor, which will help identify the best conditions for larval growth. Data obtained from the system is automatically sent to a mobile application via an IoT network, allowing users to monitor the development of larval conditions anytime and anywhere. Testing showed a classification accuracy of 87.7%, making this system a potential tool in supporting the biodegradation process of organic waste more efficiently.