Penerapan Logika Fuzzy Tsukamoto pada Rancang Bangun Sistem Deteksi Kekeruhan Air Budi Daya Ikan Lele - Rizki, Muhammad; Darnila, Eva; Agusniar, Cut (Universitas Methodist Indonesia, 2025)
This study develops a water quality monitoring system for catfish farming using the Internet of Things (IoT) and Fuzzy Tsukamoto logic. This system consists of a Turbidity Sensor to measure turbidity levels, a DS18B20 sensor to monitor temperature, and a pH meter to measure water acidity levels. Data from the sensors is sent in Realtime to Firebase and displayed in an Android application based on Kodular. The Fuzzy Tsukamoto method is used to analyze data, determine the water quality status whether the water value is Clean, Normal, or Turbid based on predetermined parameters. Based on 14 tests, the system showed an accuracy level of 85.7%, with 12 matching results. In addition, this system is able to provide automatic notifications to users if there are significant changes in water conditions. As a result, this system can help fish farmers monitor water quality efficiently, as well as make decisions about when is the right time to change pond water.