Penerapan Data Mining untuk Klasifikasi Penjualan Baju Muslim Dimasa Pandemi Covid-19 Menggunakan Metode Algoritma C4.5
Studi Kasus: Garaya Collection
Abstract
During this Covid-19 pandemic, it has become a global pandemic that continues to experience an increase in daily infection rates in Indonesia. The most obvious example is the decline in the income turnover of MSME actors, this impact requires a special strategy to increase sales during the pandemic. Garaya Collection store is a store that is engaged in selling Muslim clothes, but from the various types of clothes that are sold, not all of them are necessarily sold and are not selling well. Sales data, purchases of goods, incoming goods, and unexpected goods expenditures at the Garaya Collection Store are not well structured, so the data only functions as a store archive and is not used for developing sales strategies. Therefore, it is necessary to apply the classification using the C4.5 algorithm data mining method at the Garaya Collection Store. The C4.5 algorithm can be applied to the Garaya Collection Store to determine the sales of clothes that are selling very well, selling well, and not selling well. Application of the C4.5 Algorithm method at the Garaya Collection Store, namely the classification of sales data stock. Then using the C4.5 Algorithm method on rapidminer, it is done by entering data on categories, brands of goods, prices, selling times, and selling well. Storage of data taken through MS.EXCEL, the data is connected to the rapidminer tools and will be processed and in the form of a decision tree. After that, rapidminer will generate which ones are sold, sold, and not sold well.
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