Abstract
Feeding carp manually results in disruption of fish growth so that fish yields are not optimal. If the feed is given too much then the rest of the fish feed will become a source of bacteria. Therefore, it is necessary to design an Internetof Things (IoT)-based carp feeder monitoring sistem that can work automatically based on the time and amount of fish feed that has been determined. In this study, the research method used is the waterfall method. The IoT-based automatic carp feeder monitoring sistem uses a Wemos D1 R1 microcontroller, RTC, LCD, servo motor, ultrasonic sensor, buzzer and Blynk. The results of this study are tools for monitoring automatic feeding at a predetermined time. Fish feed was given twice a day at 6:00 and 18:00 with feed weight 2% of the total fish biomass. Ultrasonic sensor accuracy in reading fish feed distance is 95.63%, accuracy in feeding fish is 90.47%, buzzer accuracy for warning if fish feed is running low is 100%. The amount of fish feed consumed for 3 weeks automatically was 152 grams and 107 grams manually. The difference in fish changes for manual feed is 10 grams and automatically is 15 grams.
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