Implementasi Algoritma K-Means Clustering pada Penjualan Sepatu Futsal Merk Specs
DOI:
https://doi.org/10.62383/polygon.v2i3.198Keywords:
Data Mining, Clustering, K-Means, SpecsAbstract
Sport is an activity that is popular and needed by all levels of society to fulfill a healthy lifestyle. Sports cannot be separated from the equipment or equipment used to complete the activity. One of the sports that is often popular, especially among teenage boys, is Futsal. Futsal shoes are equipment that is really needed to support the continuity of this activity. Various brands of futsal shoes are often found on the Indonesian market today. One of them is the Specs brand of futsal shoes. .In this case, the author analyzes sales of Specs brand futsal shoes to determine the grouping of product sales. The method that will be used to solve the problem that will be examined is one of the data mining methods, namely the data grouping method using the K-Means algorithm. The K-Means algorithm is a grouping algorithm that can group a number of data into certain data groups. In this research, sales data is grouped into 2 clusters, namely best-selling and non-selling data. This clustering test was carried out using MS Excel with several processes which then produced several groups of sales data on Specs brand futsal shoes and implemented using the Weka application to find the effectiveness of grouping data on sales of Specs brand futsal shoe products.
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