Temperature is a crucial factor in fish egg hatching, as fluctuations can reduce hatching rates and increase larval abnormalities. This study aims to build an IoT-based temperature control system for a fish egg incubator prototype and analyze the resulting temperature stability against the specified setpoint values. The system was constructed using a DS18B20 temperature sensor characterized by high accuracy (R² = 0.9997), an ESP32 microcontroller as the data-processing and control center, a Peltier TEC-12706 element as a cooling actuator, and a relay module as an automatic switch. The control method employed was ON-OFF, with three setpoint ranges: 27-28°C, 27-29°C, and 27-30°C. Temperature data was transmitted to the Supabase cloud database and displayed in real-time on a web dashboard deployed on the Vercel platform. The results showed that the control system maintained the best temperature stability at the 27-29°C range, with a standard deviation of 0.308°C, an overshoot of 0.063°C, and a steady-state error of 0.006°C. The IoT monitoring system performed reliably, as evidenced by a 100% data transmission success rate and an average delay of 2-3 seconds. In the hatching test of 50 catfish eggs, the controlled system yielded a 90% hatching rate with an average hatching time of 19 hours, significantly better than the uncontrolled treatment, which achieved only 82% within 24 hours. This research proves that the IoT-based temperature control system effectively improves the success and efficiency of the fish egg hatching process

Keywords: DS18B20, ESP32, Fish Egg Incubator, Internet of Things (IoT), Temperature Control