Implementationi of Apriorii and Fp-Growth Algorithms on Car Dealer Parts Sales with Association Rules

Abstract

Data¹ mining is the process of discovering¹ interesting and useful patterns and relationships¹ in large volumes of data to produce¹ valuable information. This information can help company leaders make decisions in various business areas. Company leaders can then develop strategies to face competition¹ in the business world, one¹ of which is the business¹ of selling car¹ parts. The¹ availability of information systems related to car parts purchase transactions can be used to determine the association¹ of parts stored¹ in theⁱ database.ⁱ The collection¹ of transaction data¹ can then be analyzed¹ usingⁱ the data mining¹ process with the aprioriⁱ and fp-growth algorithms usingⁱ RapidMiner,ⁱ which will produce informationⁱ about a set of spareⁱ parts thatⁱ are alwaysⁱ purchased togetherⁱ more accurately,ⁱ easily, andⁱ quickly. Using theⁱ information generated, managementⁱ can use this informationⁱ as oneⁱ of theⁱ inputs in makingⁱ strategicⁱ decisions in facing businessⁱ competition,ⁱ such as strategiesⁱ for promotional needs, buyer segmentation,ⁱ inventory stock,ⁱ spare partsⁱ placement, or observing customerⁱ shopping patterns.