IMPLEMENTATION OF DATA MINING TO CATEGORIZE DAILY SALES TRANSACTION DATA USING K-MEANS CLUSTERING

Firahmi Rizky, Yohanni Syahra, Hevlie Winda Nazry S, Jufri Halim, Niver Niawati Lo'i

Abstract


This research aims to implement Data Mining techniques using the K-Means Clustering method to group daily sales transaction data at Indomaret. This clustering aims to determine Indomaret's sales profit every day. 

The data used in this research is daily sales transaction data at Indomaret. The K-Means Clustering process begins with random selection of cluster center points using the K-Means method and grouping data based on relevant attributes.

The results of this study show that K-Means Clustering can group daily sales transaction data effectively, producing several clusters that have unique characteristics. Each cluster represents a different market segment, which enables Indomaret management. Thus, the implementation of data mining using k-means clustering is proven.


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DOI: https://doi.org/10.3059/insis.v0i0.22936

DOI (PDF): https://doi.org/10.3059/insis.v0i0.22936.g13324

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