IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK REKOMENDASI PRODUK DI TOKO LM MART

Abstract

LM Mart is one of the BumDesa shop businesses located on Jl Raya Purwodadi-Semarang Km.13, Godong sub-district, Grobogan Regency. The products sold include various basic food items (nine basic commodities) for general community needs. Data is stored in the LM Mart store database. One of them is increasing transaction data. With the increasing volume of data at LM Mart, the analyst's function of analyzing data manually must be replaced by computer-based applications. The problem with the LM Mart Store is that traders lack the ability to observe consumers' desires and needs, which of course will have an impact on increasing product sales. Besides that, sales transaction data, if processed, can produce useful information which can become a sales strategy to improve marketing. The FP-Growth algorithm will be used for the association approach in this research. The FP-Growth algorithm is a development of the apriori algorithm, it corrects the shortcomings of the apriori algorithm. To obtain a frequent item set, the a priori algorithm must generate candidates. From the research results, calculations using RapidMiner with a Support value of 30% and a Confidance value of 80% with transaction data of 800 records produced 36 rules.