a Implementasi Data Mining Analisis Terhadap Data Penjualan Produk Herbal Dengan Metode Algoritma Apriori dan Fp Growth

Abstract

Abstract – Business Center Jakarta Barat 2 is very diverse, such as Extra Food products, Ethawa Goat Milk, Synergic Herb Oil, Sari Kurma, and many more. Every month, serves many sales transactions. Every problem with the sale of herbal products in the HNI-HPAI business center is recorded every minute, every day, every week and even years. So that the data will accumulate more and can come from manual processes or computational processes. To find out the herbal products with the most sales and the linkage of herbal products, one of the algorithms in the data mining algorithm is needed, namely the Apriori Algorithm and FP-Growth to be able to find out the sales data for herbal products by calculating manually and RepidMiner Software, herbal products that appear simultaneously and can it is known which product brands are the most superior and are most in demand by the public, namely by calculating sales transaction data for 2020-2021 with 30% support and 60% confidence, we will get the final association results, namely EGM and MHS with 50% support and 66 Confidence, 7% and MHS and EGM with 50% Support and 85.7% Confidence results from the calculation of the Apriori Algorithm and FP-Growth on transaction data for 1 year of EGM and MHS.

Keywords: Data Mining, Sales, Apriori, FP-Growth, Association Rule