Monitoring pH And Turbidity of Crayfish Pond Using Website and Automation Controlling Using Sugeno Fuzzy Logic Method

Abstract

Crayfish, particularly Cherax Quadricarinatus, hold significant potential for aquaculture due to their high market value and substantial demand both domestically and internationally. The growth of freshwater crayfish is heavily influenced by the pond environment. Several environmental factors affect this growth, including water turbidity, pH, dissolved oxygen, temperature, and ammonia levels. This study focuses on monitoring water turbidity and pH using DFRobot Tubidity SEN0189 and PH-4502C sensors, and displaying the results on a monitoring website. Additionally, a pump filter and aerator are employed as actuators for control. The control method used is Sugeno Fuzzy Logic, which makes control system decisions when sensors detect pH and turbidity values outside the optimal range for crayfish ponds: 6-8 for pH and 5-25 NTU for turbidity. The Sugeno Fuzzy Logic method used has inputs based on sensor readings, each with three membership degrees; for pH, Acid (0-6.5), Neutral (6-8), and Base (7.5-14); and for turbidity, Clear (0-5 NTU), Turbid (4-15 NTU), and Very Turbid (14-25 NTU). The outputs control the pump filter and aerator, with two membership degrees: Off, On, and On-Extended. The sensors have successfully measured pond turbidity with an error of 4.76% and pH with an error of 0.9%. The control system has been successfully implemented, with the pump filter and aerator activating in response to measured conditions in the crayfish pond.