Clustering Tingkat Penjualan Menu (Food and Beverage) Menggunakan Algoritma K-Means

Hadi Syahputra; Liga Mayola; Dodi Guswandi

doi:10.35134/komtekinfo.v9i1.274

Authors

Hadi Syahputra Universitas Putra Indonesia YPTK Padang
Liga Mayola Universitas Putra Indonesia YPTK Padang
Dodi Guswandi Universitas Putra Indonesia YPTK Padang

DOI:

https://doi.org/10.35134/komtekinfo.v9i1.274

Keywords:

Data Mining, K-Means Algorithm, Grouping, F&B Menu

Abstract

Menu planning in a restaurant is part of the sales strategy. Each menu has a different level of sales. To determine the effectiveness of sales and raw materials, restaurants need knowledge of what menus need to be maintained and vice versa. An analysis that can determine the sales level menu is the analysis of the k-means algorithm data mining clustering method. The source of research data is from the history of menu sales transactions for 1 year, then analyzed by the k-means algorithm. The information found is in the form of popular F&B menus and sales level menus. The purpose of this study is to group the data menu on the level of sales (Food and Beverage). The method used is the Clustering method with the performance of the K-Means algorithm. The results showed that the clustering method with the K-Means algorithm gave a significant output in grouping sales data. The research contribution provides knowledge in the form of information in conducting sales data management

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