IMPLEMENTASI ALGORITMA APRIORI UNTUK PREDIKSI STOK PERALATAN TULIS PADA TOKO XYZ

Abstract

For school children, offices, and students stationery is needed. Because stationery are needs to take notes important things. Although in the current digitalization era learning materials can be obtained online to minimize the use of stationery, it doesn't rule out the possibility that stationery are needed indeed for other activities. Therefore, stores that provide various types of stationery must be able to know the level of purchases on products ?
products that are more often purchased by consumers so that the supply of stock products can be more focused on products that are more often purchased by consumers. At this writing, the author uses the Apriori algorithm that performs itemset frequencies to get association rules that meet the minimum support requirements and minimum confidence requirements with a number of itemset in the overall transaction to achieve the percentage of support and the percentage of confident value in determining items that are often sold in every transaction. By using the Apriori algorithm which has an accuracy rate of around 70%, it can predict the stock of product sales at the XYZ store. The purpose of applying the Apriori algorithm at this writing is to find out the level of purchases on products that are more often purchased by consumers based on existing transaction data to provide a more efficient stock of sales products.