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Rizki Ramadhansyah
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Computer Science & IT

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The Menu Clustering At Doktor Kopi Using K-Means Algorithm To Increase Sales Septian Simatupang; Monsyah Juansen; Rizki Ramadhansyah; Taufiqurrahman; Windi Saputri Simamora
INFOKUM Vol. 12 No. 04 (2024): Engineering, Computer and Communication, November 2024
Publisher : Sean Institute

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Abstract

Coffee Doctoris a coffee shop with a variety of menus and a strategic location in Medan City, this coffee shop is currently developing a strategy to increase sales of their products. Effective menu arrangement is an important factor in increasing product sales in coffee shops or cafes. This study aims to optimize sales by utilizing the K-Means algorithm to group menus based on customer purchasing patterns. The sales data analyzed includes product types, purchase frequency, and revenue contributions from each menu. Through the clustering process, menus can be grouped into several categories, such as the best-selling, medium and less popular menus. The results of this clustering are used to design a more structured menu arrangement strategy, such as arranging menu positions on the list, special promotions, or eliminating less effective menus. The implementation of the K-Means algorithm shows that a data-based menu arrangement strategy can improve customer experience and significantly drive product sales. Thus, this study provides a practical contribution for coffee shop or cafe managers to optimize sales through a technology and data-based approach.
Co-Authors Monsyah Juansen Septian Simatupang Taufiqurrahman Windi Saputri Simamora