K-Means Algorithm Method for Clustering Best-Selling Product Data at XYZ Grocery Stores

Abstract

This study aims to utilize the K-means clustering algorithm in data mining to categorize sales data at XYZ Grocery store. The research is essential for understanding sales patterns and enhancing inventory management strategies. The research methodology involves implementing the K-means clustering algorithm to generate centroid values for each cluster, thereby creating groups of products based on their sales performance. The findings of this study are expected to provide insights into sales trends at the store. While the abstract provides a general overview, specific results and contributions of this research are not detailed. Further studies could offer a more in-depth understanding of the practical applications of these findings in improving store management and inventory control.

The Influence Of Digital Marketing On Competitive Advantage And Performance of Micro, Small And Medium Enterprises

“…Data analysis can then be performed using statistical techniques such as regression analysis to test the relationship between the independent variable (digital marketing) and the dependent variable (competitive advantage and business performance) (Ridzki et al, 2023). This analysis will help determine how much digital marketing affects MSMEs' competitive advantage and performance.…”