Red chili farmers on the East Coast of North Sumatra still rely on manual calculations to determine the use of NPK Biru 16 Mutiara fertilizer, often leading to inaccurate and inefficient fertilizer application. This study proposes the Backpropagation method within Artificial Neural Networks (ANN) as a solution to analyze fertilizer needs more precisely. The method enables the system to learn from historical data and plant growth patterns, providing accurate recommendations for the type and amount of fertilizer required. The implementation of ANN in this context not only enhances agricultural efficiency but also supports environmental sustainability by minimizing excessive fertilizer usage.
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