Prediction of Frozen Food Sales Using Extra Trees Algorithm at Tjoean.Id Store

In today's digital era, sales prediction has become crucial for businesses to optimize inventory and meet market demand. This study aims to apply the Extra Trees algorithm in predicting frozen food sales at Tjoean.id store. By using historical sales data and variables such as date, product type, and sales quantity, this method is expected to provide accurate and beneficial predictions for business decision-making. The research results show that the Extra Trees algorithm can deliver predictions with a high level of accuracy, evidenced by the low values of Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE), which are 17.868500, 790.432020, and 28.114623 respectively. The implementation of this algorithm is expected to assist Tjoean.id in managing product stock according to sales predictions, thus reducing the risk overstocking or understocking. This research provides new insights into the use of the Extra Trees algorithm for sales predictions, especially in the frozen food industry.