<![CDATA[In catfish farming it is very important to pay attention to the quality of pond water, including the level of acidity of pond water, and the level of turbidity in the pond. However, some catfish breeders have started to be preoccupied with other activities for quite a long time so that water quality control cannot be controlled anymore. The purpose of this research is to produce a prototype or design of a monitoring and control system for acidity and turbidity levels in pool water that can run automatically and can be monitored remotely using the internet. This study aims to make a prototype control for controlling the pH of catfish pond water using an Arduino Uno as a microcontroller and a pH meter sensor and turbidity sensor. This study uses the fuzzy logic control method. Fuzzy method calculations are performed using two input parameters, namely water turbidity and water pH. The output of the fuzzy calculation results is in the form of a timer, which is the length of time it takes to drain the pool water. The Fuzzy Sugeno method was chosen to control the degree of acidity of the water according to the needs of catfish by draining the water for a duration determined from the results of Fuzzy Sugeno calculations as the z center point. The results of the pH and turbidity sensor readings will be displayed on the LCD and then by Arduino it will be sent to Esp8266 to be forwarded to the user via the Blynk application. Based on the research that has been done, an automatic pH adjustment system has been built and can be accessed through the Blynk application. The accuracy of the pH sensor can read the value of the degree of acidity with an average error of 2.053% so that it can be said that the sensor works quite well because the sensor can still read changes in the degree of acidity in different waters even though the changes are quite small. The turbidity sensor used also has fairly good reliability with an average error of 8.057%. Testing the calculation of the Sugeno method is carried out by comparing the calculation results of Fuzzy Logic Control with the results of Matlab calculations.]]>
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