<![CDATA[This research discusses the implementation of the Artificial Neural Network (ANN) method in the broiler poultry farming sector to optimize the environmental conditions of chicken coops at PT. Gunawan Farm. The system is designed to assist farmers in monitoring, analyzing, and providing automatic recommendations to maintain the ideal coop conditions that support optimal growth and productivity of broiler chickens. The study begins with data collection from PT. Gunawan Farm, which includes parameters such as temperature, humidity, chicken age, lighting, density, and water supply. The collected data are processed and trained using the feedforward backpropagation algorithm of ANN. The model is then tested to evaluate its accuracy in predicting and recommending the coop conditions.The results show that the ANN model is capable of predicting the coop condition accurately and providing precise recommendations, such as increasing or decreasing temperature, lighting, density, or water supply. The system helps farmers to make faster and more efficient decisions in maintaining environmental stability, thus improving broiler productivity and reducing the risk of decreased livestock quality.]]>
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