<![CDATA[Crude oil is an important energy source that experiences significant price fluctuations due to various factors such as geopolitics and global market dynamics. Research conducted by Muhammad Reynaldi in 2024 using the title ‘‘Crude Oil Price Prediction Using the CART (Classification and Regression Tree) Algorithm’’, aims to disseminate examples of crude oil price predictions carefully and easily interpreted. The problem faced in this study is the difficulty of predicting crude oil prices due to fluctuations determined by many external factors. The purpose of this study is to create a more accurate prediction method with traditional methods, and to assist decision making in the energy sector. The results of the study show that the CART solving procedure for predicting crude oil prices with an MSE value of 0.892, an MAE value of 0.700, an RSME value of 0.944, and an R-square value of 0.957. This study places significance on overcoming the challenges of crude oil price fluctuations and provides simple solutions for governments, companies, and energy industry players.]]>
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