<![CDATA[Abstrak Budidaya maggot Black Soldier Fly (BSF) menjadi salah satu solusi alternatif dalam pengelolaan limbah organik sekaligus sumber pakan berprotein tinggi. Namun, kondisi lingkungan seperti suhu dan kelembapan sangat memengaruhi pertumbuhan dan kestabilan budidaya maggot. Penelitian ini bertujuan untuk mengembangkan sistem monitoring dan pengendalian suhu serta kelembapan berbasis Internet of Things (IoT) secara real-time pada budidaya maggot. Sistem dikembangkan menggunakan mikrokontroler ESP32 yang terintegrasi dengan sensor DHT22 dan soil moisture untuk memantau kondisi lingkungan budidaya. Sistem juga dilengkapi dengan aktuator berupa lampu, ultrasonic mist maker, kipas DC, buzzer, LCD, serta notifikasi Telegram untuk pengendalian otomatis dan monitoring jarak jauh. Pengujian sistem dilakukan melalui pengujian akurasi sensor, pengendalian otomatis, respons waktu sistem, dan monitoring notifikasi berbasis IoT. Hasil penelitian menunjukkan bahwa sensor DHT22 memiliki nilai error suhu sebesar 0,00%–3,75% dan error kelembapan sebesar 0,00%–3,90%. Sensor soil moisture memiliki nilai error maksimum sebesar 3,92%. Sistem mampu menjaga kondisi lingkungan pada rentang suhu optimal 30°C–36°C dan kelembapan 60%–70% dengan waktu respons 1–2 menit. Selain itu, Telegram Bot berhasil mengirimkan notifikasi monitoring secara real-time. Abstract Black Soldier Fly (BSF) maggot cultivation has become an alternative solution for organic waste management and a high-protein feed source. However, environmental conditions such as temperature and humidity significantly affect maggot growth and cultivation stability. This study aims to develop an Internet of Things (IoT)-based monitoring and control system for real-time temperature and humidity management in maggot cultivation. The system was developed using an ESP32 microcontroller integrated with DHT22 and soil moisture sensors to monitor environmental conditions. The system also utilized actuators including lamps, ultrasonic mist makers, DC fans, buzzers, LCDs, and Telegram notifications for automatic control and remote monitoring. System performance was evaluated through sensor accuracy testing, automatic control testing, response time analysis, and IoT-based notification monitoring. The results showed that the DHT22 sensor achieved temperature measurement errors ranging from 0.00%–3.75% and humidity measurement errors ranging from 0.00%–3.90%. The soil moisture sensor produced a maximum error value of 3.92%. The system successfully maintained environmental conditions within the optimal range of 30°C–36°C and 60%–70% humidity with a response time of 1–2 minutes. In addition, the Telegram Bot successfully delivered real-time monitoring notifications remotely.]]>
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