<![CDATA[Feed is the single largest cost component in Nile tilapia aquaculture, frequently accounting for more than sixty percent of total production costs. However, in most Indonesian smallholder operations, feed is still dispensed manually based on visual estimation. Existing Internet of Things feeders reported in the literature generally automate the timing of feed delivery but do not provide feedback on the actual amount of feed dispensed. They are also rarely evaluated in a Recirculating Aquaculture System, where uneaten feed increases the load on the biofilter. This study addresses this limitation by designing, implementing, and experimentally evaluating an Internet of Things based automatic feeder with closed loop gravimetric dosing integrated into a Recirculating Aquaculture System for Nile tilapia culture. The system combines an ESP32 microcontroller, a load cell sensor, a servo actuated feed gate, a BTS7960 controlled direct current auger, and a real time clock scheduling module. A web based interface enables real time adjustment of feed ration and feeding schedule. The feeder was evaluated over ten dispensing cycles using a target ration of fifty grams, and its performance was compared with manual feeding during a rearing trial. Gravimetric dosing achieved an average error of two point four percent and an average dosing accuracy of ninety seven point six percent, with an average deviation of one point two grams per feeding cycle. During the rearing trial, the experimental group consumed twelve kilograms of feed, whereas the control group consumed fourteen kilograms, representing a feed reduction of fourteen point three percent. The experimental group also achieved a feed conversion ratio of one point four six, compared with two point zero zero in the control group. Survival reached ninety two point five percent in the experimental group and eighty one percent in the control group. Mean individual body weight increased from two hundred forty five grams in the control group to two hundred eighty grams in the experimental group. Size uniformity also improved, with the coefficient of variation decreasing from fifteen percent to eight percent. These findings demonstrate that integrating gravimetric feedback into an Internet of Things based feeder provides measurable feed savings beyond scheduling automation alone and offers a practical and appropriate technology solution for small scale Nile tilapia production in Recirculating Aquaculture Systems.]]>
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