IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI UNTUK MENENTUKAN PERSEDIAAN BARANG - Ahmed Arifi Hilman Rahman; Zaehol Fatah (CV. Denasya Smart Publisher, 2025)
Entrepreneurs engaged in the shopping sector have promising prospects because they can serve the lower and upper middle classes and provide convenience for people to buy everyday goods without having to go to supermarkets or convenience stores. However, if the availability of goods or materials needed is not optimally guaranteed, there may be a shortage of goods or materials needed. This also happens in some stores, where customers often run out of stock of various products and equipment they are looking for, but this is due to the lack of inventory management habits in the store. In this case, it is about finding out what products and needs are needed by store customers. This dataset uses several variables such as transaction date, product name, and sales or purchase amount by applying the apriori algorithm. The apriori algorithm is a type of association rule in data mining that is used to analyze and find correlation patterns. The data used in this study is a sample of 100 sales transaction data. The final association rule obtained from the transaction data is