Dalam dunia peternakan modern, teknologi berperan penting dalam meningkatkan efisiensi dan keberhasilan budidaya ternak. Salah satu tantangan utama adalah menjaga stabilitas suhu, kelembaban, serta kualitas udara pada inkubator, sekaligus memastikan pemberian pakan dilakukan secara tepat waktu dan sesuai kebutuhan. Anak ayam sangat rentan terhadap perubahan suhu dan kelembaban, sehingga kesalahan dalam pengaturan dapat menyebabkan stres, dehidrasi, bahkan kematian. Selain itu, gas amonia dari kotoran ayam juga berisiko mengganggu kesehatan pernapasan dan pencernaan. Oleh karena itu, penelitian ini merancang sistem monitoring berbasis Internet of Things (IoT) dengan metode fuzzy logic yang mampu mengolah data sensor secara real-time untuk menghasilkan keputusan yang lebih adaptif dan fleksibel. Sistem dibangun menggunakan Arduino Uno R4 WiFi yang terhubung dengan sensor DHT22 untuk membaca suhu dan kelembaban, sensor MQ135 untuk mendeteksi kadar amonia, serta sensor ultrasonik untuk memantau ketersediaan pakan. Data yang diperoleh ditampilkan melalui Firebase sehingga dapat dipantau secara jarak jauh menggunakan aplikasi. Metode penelitian yang digunakan adalah Research and Development (R&D) melalui tahap analisis kebutuhan, perancangan, implementasi, serta pengujian sistem. Hasil pengujian menunjukkan bahwa sensor DHT22 memiliki rata-rata error suhu sebesar 0,396% dan kelembaban 0,706%, sedangkan sensor ultrasonik setelah kalibrasi memiliki error 2,105%. Sistem fuzzy logic dengan 27 rule base berhasil mengendalikan kipas, lampu, serta motor servo pemberi pakan secara otomatis pada jam 07:00, 14:00, dan 21:00. Pada kondisi suhu 34°C, kelembaban 35%, dan amonia 250 ppm, hasil fuzzy memberikan output pakan kategori “banyak” dengan nilai defuzzifikasi 67,5 yang konsisten dengan perhitungan manual.
In modern poultry farming, technology plays a crucial role in improving efficiency and ensuring the success of livestock rearing. One of the main challenges is maintaining stable temperature, humidity, and air quality in the incubator, while also ensuring that feeding is carried out on time and according to the chicks’ needs. Newly hatched chicks are highly vulnerable to fluctuations in temperature and
humidity, where improper regulation can lead to stress, dehydration, or even death. In addition, ammonia gas from chicken waste poses significant risks to the respiratory and digestive health of the chicks. Therefore, this research designs an Internet of Things (IoT)-based monitoring system using fuzzy logic, which is capable of processing sensor data in real time to produce more adaptive and flexible
decision-making.The system was developed using an Arduino Uno R4 WiFi connected to a DHT22 sensor for temperature and humidity measurement, an MQ135 sensor to detect ammonia levels, and an ultrasonic sensor to monitor feed availability. The data collected is displayed through Firebase, enabling remote monitoring via a mobile application. The research method applied is Research and
Development (R&D), consisting of needs analysis, system design, implementation, and performance testing. The test results show that the DHT22 sensor achieved an average error rate of 0.396% for temperature and 0.706% for humidity, while the ultrasonic sensor, after calibration, produced an error rate of 2.105%. The fuzzy logic system, consisting of 27 rule bases, successfully controlled the fan, lamp, and feed servo motor automatically at 07:00, 14:00, and 21:00. Under the condition of 34°C temperature, 35% humidity, and 250 ppm ammonia, the fuzzy system produced a feed output categorized as “high” with a defuzzification value of 70.00, which was consistent with manual calculations. Overall, the system has proven effective in maintaining incubator stability, reducing chick mortality risks, and
facilitating farmers in performing remote monitoring and control. This study provides a practical and innovative solution to support the modernization of poultry farming.