<![CDATA[Implementation of the Naïve Bayes algorithm on sales data to determine consumer buying patterns in canteens is an approach that seeks to overcome the limited understanding of consumer behavior in canteens. The goal of this approach is to analyze sales data and identify purchasing patterns to gain insight into consumer behavior, optimize sales strategies, and improve customer satisfaction. By applying the Naïve Bayes algorithm to sales data, this research seeks to identify factors that influence consumer behavior, such as price, convenience, and menu offerings, and provide insights that can be used to optimize menu offerings, pricing strategies and resource allocation. Additionally, the approach seeks to increase customer satisfaction and differentiate canteens from competitors by personalizing menu offerings and enhancing the overall customer experience. This research also aims to contribute to the field of consumer behavior research by applying the Naïve Bayes algorithm to canteen sales data, potentially providing insights that can be applied in other contexts. Overall, the application of the Naïve Bayes algorithm to canteen sales data can provide a data-driven approach to understanding consumer behavior and improving sales strategy and customer satisfaction.]]>
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