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Bagus Cakra Jati Kesuma
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Metode Fuzzy Pada Akuaponik Deep Water Culture Berdasarkan Derajat Keasaman Dan Ketinggian Air Bagus Cakra Jati Kesuma; Tibyani Tibyani; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Aquaponics is an excellent cultivation choice to apply, this system grows in a mutually beneficial environment. The existence of fish, plants and bacteria is very important. These elements create a mutually beneficial relationship called a symbiotic mutualism. In an aquaponics system, pH and water level are mutually controlled components to be maintained at a certain level for aquaponical optimization, it underlies the existence of a control system by implementing a fuzzy method for processing the data of acidity and aquarium water level. Then it will be processed in Arduino Uno microcontroller. The input data was obtained from respondents using questionnaires which processed into the value of the input of membership degree, then it enter in the implication process, the implication function used is min, go into the composition of the fuzzy system rule is max, from the advanced inference engine in the defuzzification process obtained the fixed value for the pump output. Testing of pH and ultrasonic sensors reveal that the sensor works in a low error rate. In testing of fuzzy Mamdani method, the fuzzy processing of the system and manually testing is done by analyzing that the fuzzy formula applied to the system can produce an output corresponding to the fuzzy calculation. From data obtained samples can be concluded that the output of the system in accordance with the undertaken design. It is proved by comparing to the output value of the system equal to the output of the manual calculation, and has a 100% accuracy on fuzzy testing performed.
Co-Authors Mochammad Hannats Hanafi Ichsan Tibyani Tibyani