<![CDATA[Coffee plants are an important commodity in the agricultural sector but are vulnerable to various diseases that can affect productivity and crop quality. To quickly and accurately identify and classify diseases in coffee plants, a technology-based approach is needed to assist farmers in decision-making. This study aims to evaluate the use of the Decision Tree algorithm as a classification method in detecting diseases in coffee plants. Through a Systematic Literature Review (SLR), we collected data from five relevant journals and analyzed the effectiveness of Decision Tree in the disease classification process. The results show that the Decision Tree approach can achieve high accuracy in identifying coffee plant diseases and is easy to implement in the field. This research is expected to provide further insights for the development of decision support systems to help coffee farmers improve plant health and productivity.]]>
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