Sistem Monitoring Suhu Dan Kelembapan Udara Pada Aquaponik Berbasis Iot Menggunakan Metode K-Nearest Neighbors(KNN) Untuk Prediksi Kondisi Optimal Tanaman

Suhud, Muhammad Haris (2026) Sistem Monitoring Suhu Dan Kelembapan Udara Pada Aquaponik Berbasis Iot Menggunakan Metode K-Nearest Neighbors(KNN) Untuk Prediksi Kondisi Optimal Tanaman. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

This research aims to design and implement a temperature and humidity monitoring system for an aquaponic system based on the Internet of Things (IoT) integrated with the K-Nearest Neighbor (KNN) method to predict optimal plant growth conditions. The system uses a DHT22 sensor to measure air temperature and humidity, as well as a DS18B20 sensor to measure water temperature. All data is processed by the NodeMCU ESP8266 microcontroller and transmitted to the Firebase Realtime Database via the internet for real-time processing.The collected data is then preprocessed and normalized using the Min-Max Normalization method before being used in the classification process. The K-Nearest Neighbor (KNN) method is applied using Euclidean Distance to classify aquaponic environmental conditions into optimal and non-optimal categories. Experiments were conducted using different K values (K = 3, 5, and 7), and the best result was achieved at K = 3 with an accuracy of 86% based on the confusion matrix evaluation.The results show that the system is capable of performing real-time environmental monitoring while also providing accurate predictions of optimal plant conditions. This system enables users to remotely monitor aquaponic conditions and supports decision-making to maintain ecosystem stability

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