Detection of Water Quality Fluctuation Patterns with Fuzzy Logic Controller

Abstract

The quality of pond water greatly affects the success rate of fish survival. Temperature, pH, and oxygen are the 3 main things that cause changes in fluctuation patterns in gourami ponds, so it is necessary to detect fluctuation patterns in pond water quality to maintain the balance of the fish's aquatic environment, prevent premature fish deaths, and optimize fish farming results. The objectives of this study are 1) to detect patterns of changes in water quality; 2) to classify fluctuations as normal, unstable, or dangerous; and 3) to provide recommendations and automatic actions to turn on the heater, cooler, and aerator. The method used is fuzzy with inputs in the form of temperature, pH, and oxygen and outputs including circulation pumps, aerators, heaters and the status of pond water quality conditions. The results of the study showed that: 1) the device is able to detect patterns of changes in water quality where changes in water quality occur at critical hours, namely 04:00, 12:00–14:00, 21:00, and 01:00–03:00 which are influenced by temperature, pH, and oxygen conditions, 2) The status of water quality conditions is divided into three statuses, namely safe, unstable, and dangerous; and 3) The circulation pump, aerator, and heater turn on when the status condition is unstable and dangerous and will turn off when the pool condition is in a safe status.