Perancangan Sistem Monitoring Kualittas Air dan Automasi pH Pada Kolam Ikan Nila Berbasis IoT Dengan Algoritma K-Nearset Neighbor (KNN)

Abstract

Water quality is a critical factor in aquaculture as it directly affects fish health and growth. Parameters such as pH, temperature, and turbidity must be monitored regularly to maintain optimal environmental conditions. This study aims to design a real-time water quality monitoring system based on the Internet of Things (IoT), integrated with an automatic pH adjustment feature using the K-Nearest Neighbor (KNN) algorithm. The system utilizes an ESP32 microcontroller connected to pH, temperature, and turbidity sensors, and transmits the collected data to a cloud-based real-time database. The KNN algorithm is employed to analyze historical data and predict pH regulation needs based on detected patterns. The results indicate that the system can effectively monitor water conditions and perform timely automated responses to pH fluctuations, thus supporting a healthy aquaculture environment. Additionally, the system offers a web-based interface that allows users to visualize data, track historical records, and download daily