<![CDATA[This study designs and implements an input recommendation system for smallholder coffee agribusiness to close productivity and efficiency gaps. The objective is to assess how decision analysis guides farmers toward input combinations aligned with goals, budget constraints, and field risks. The methodology applies decision analysis: candidate input allocations are formulated; evaluation criteria (yield, total cost, risk exposure, ease of implementation) are specified; criterion weights are elicited through structured judgments; scores are normalized and aggregated; and sensitivity analysis tests robustness to weight and price changes. Results show that the recommendation-based alternative consistently outperforms conventional practice on most criteria, raising productivity while lowering cost per unit of output and reducing risk under volatile weather. Stability of rankings across sensitivity tests indicates durable performance across diverse farmer preferences. The findings highlight the need for targeted technical assistance and financing aligned with recommended inputs to support sustained adoption and scalable replication across regions.]]>
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