Data Mining Menentukan Pola Penjualan Kunci- Kunci Antik Dan Assesoris Rumah Dengan Algoritma Apriori

Ella Lumbantoruan

doi:10.47065/mis.v2i2.1220

Ella Lumbantoruan * Universitas Budi Darma, Indonesia

DOI: https://doi.org/10.47065/mis.v2i2.1220

Keywords: Penjualan, Data Mining, Algoritma Apriori

Abstract

Sales are a business or concrete steps taken to transfer a product, whether in the form of goods or services. This research is motivated by the observations and experiences of researchers, problems that occur at UD. Suto whose service is not fast enough because of the accumulation of underutilized sales notes, and there is no research that is used to find out important information in order to increase sales and service. Sales activities at UD. The running Suto continues to cause accumulation of data because of the many sales transactions that occur every day and the longer it will increase.

The solution made in this study is to utilize sales transaction data so that the data is useful, it needs to be processed with a certain algorithm. This is done by processing the accumulated transaction data into useful information. By looking at the mapping of sales patterns, the relationship between items purchased by consumers can help managers determine product item displays based on consumer needs.

The priori algorithm is a data mining technique that is used to find high frequency patterns between itemset sets called the association rule function. A priori algorithms are part of data mining, which is the activity of collecting data and using old data to find regularities, patterns or relationships in data. The Apriori algorithm will form a predetermined number of frequent itemsets based on two parameters, namely support and confidence. The results of the itemset relationship between goods can be used to increase sales

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