<![CDATA[The development of information technology provides significant opportunities in data management to help make more accurate business decisions. One method used is data mining, especially the K-Nearest Neighbor (K-NN) technique which is quite effective in classification and forecasting based on past data. This study aims to apply the K-NN technique to predict sales of the most popular books and scriptures at the Assyarif Book Store, located at the Salafiyah Syafi'iyah Islamic Boarding School in Sukorejo. It is hoped that this method can help in planning stock and identifying products that are most in demand by customers. This study uses a quantitative approach with observation, interviews, and documentation collection methods. The data used include price, quantity sold, initial stock, and final stock. The results of the analysis using Euclidean Distance show that the K-NN technique is able to predict sales categories (best-selling or not-selling) with an accuracy level of 75% obtained from cross-validation testing, so it can be an effective solution to support sales management and data-based decisions.]]>
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