Pengembangan Sistem Self-Order Kafe Berbasis Web dengan Fitur Promo Bundling Menggunakan K-Means Clustering
- Salsa Nurul Laeli Universitas Mercu Buana, DKI Jakarta, Indonesia
-
Ruci Meiyanti
*
Universitas Mercu Buana, DKI Jakarta,
Indonesia
(*) Corresponding Author
Abstract
Digital transformation in the culinary sector faces various operational challenges at Titik Teh Cafe, Kuningan Regency, including long queues at the cashier, order inaccuracies caused by manual communication using handy talkies, and the lack of sales data analysis for 256 menu variants serving an average of 92 customers per day. These problems reduce service efficiency and hinder data-driven decision-making processes. This study aims to develop a web-based self-ordering system using the K-Means Clustering algorithm for the promo bundling feature through an iterative prototyping approach. The system was developed using the Laravel framework, MySQL database, and UML modeling to support system design and implementation. The K-Means method was implemented using sales frequency parameters to form two clusters, namely popular and non-popular menu clusters. The resulting system provides self-ordering and digital payment features while reducing dependence on waiters and minimizing manual communication between cashiers and the kitchen. In addition, the clustering-based promotional feature provides menu popularity analysis to support more effective business strategies and targeted promotional decisions. This system improves the operational efficiency of Titik Teh Cafe and serves as a model for digital transformation in culinary businesses in Indonesia through the integration of self-ordering services and sales analysis.
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