ANALISA DATA MINING ASSOSIASI FP-GROWTH PADA PENJUALAN PRODUK DI TOKO RITEL AGUNG - Subagja Putra Pratama (Politeknik Bisnis Indonesia, 2023)
Quick decision-making based on data, facts, and knowledge has become a necessity for companies in implementing strategies to increase competitiveness. To create a fast strategy with measurable analysis, one can use sales data mining techniques from time to time. The research was carried out using the fp-growth association data mining method and the RapidMiner application as a mining tool for processing sales data for a one-year period (June 2021 - May 2022) with a total of 13734 sales transactions and a total of 49360 records. Data mining in this study resulted in 6 rules association with a minimum support value of 0.001 and a minimum confidence value of 0.01 and produced the 42 lowest association rules with a minimum support value of 0.001 and a minimum confidence value of 0.5. The discovery of the association rules can be used as a consideration in making product sales strategy decisions quickly and accurately so that companies can increase sales and competitiveness.