<![CDATA[Agriculture is an important sector in a country's economy and plays a vital role in providing food and industrial raw materials. The oil palm plantation industry has a huge economic impact. However, a challenge faced by palm oil producers is the selection of optimal seedlings. Poor-quality seedlings can result in reduced productivity, economic losses, and environmental impacts. Therefore, evaluating the feasibility of oil palm seedlings is very important. Proper selection of seedlings can increase plantation productivity and reduce losses caused by failure to plant unsuitable seedlings. This research aims to implement data mining using the C5.0 and CART algorithms in evaluating the feasibility of oil palm seedlings. Tests conducted on the determination of oil palm seedling eligibility resulted in 92% accuracy for the C50 algorithm while the CART algorithm resulted in 89% accuracy from a total of 97 data. Provides a better understanding of the effectiveness of the two algorithms in assisting decision-making related to planting and managing oil palm seedlings.]]>
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