RANCANG BANGUN KAPAL PEMBERI PAKAN IKAN BANDENG BERBASIS IOT MENGGUNAKAN METODE FUZZY MAMDANI
Abstract
Milkfish (Chanos chanos) farming is a strategic aquaculture sector in Indonesia that requires efficient feed management and water quality monitoring. Conventional feeding has limitations, including uneven feed distribution, inconsistency in feed quantity, and inability to respond to changes in water conditions in real time. This study aims to design and implement an Internet of Things (IoT)-based milkfish feeding boat prototype that integrates remote navigation control with adaptive feeding automation using the Fuzzy Mamdani method.
The system uses an ESP32 microcontroller as the main control unit and local web server, connected to a water pH sensor, turbidity sensor, and HC-SR04 ultrasonic sensor. Boat navigation is controlled by two 12V DC motors through BTS7960 drivers, while feed distribution is actuated by an MG995 servo motor installed on a funnel-shaped hopper. The Fuzzy Mamdani method uses water pH and turbidity levels as input variables and feed quantity as the output variable, consisting of three categories: Little, Medium, and Much, represented by nine IF-THEN inference rules. The control and monitoring interface is implemented through a web dashboard accessible via a smartphone browser in real time.
Testing results showed average sensor errors of 0.66% for pH, 2.69% for turbidity, and 2.09% for ultrasonic measurements. The navigation system successfully performed eight movement patterns, while ten web server test scenarios were successfully completed. Mapping of the 13 × 7 meter pond was also successfully completedKeywords
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DOI: https://doi.org/10.31284/j.jreec.2026.v6i2.9572
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