Abstract
Sales are a crucial aspect for companies, including PT Mustika Jaya Lestari, which uses sales predictions to determine which products will sell in the future. However, sometimes predictions can go wrong, such as when a product that is predicted to increase actually decreases. This research aims to optimize sales by utilizing the K-Nearest Neighbor (K-NN) method to predict sales results. The K-NN method works by classifying new data based on its proximity to old data. This research produces graph visualization to predict sales with 90% accuracy and 10% error, using 762 test data and 2285 training data.
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