Analysis of the Application of Customer Purchase Mining Data on Paint Sales Using Apriori Algorithm (Case Study: PT Indowarna Cemerlang Indonesia)

Abstract

Sales transaction data is one thing that can be used for making business decisions. Most sales transaction data is not reused, and is only stored as an archive and only used for making a sales report. Paint sales data is one science that can be applied in cases like this. Sales transactions that are not utilized properly can be extracted and reprocessed into useful information using data mining techniques. Using one of the data mining methods, namely the a priori algorithm, sales transaction data can be reprocessed so that it can produce a consumer buying pattern. This consumer buying pattern will later help companies make business decisions. PT Indowarna Cemerlang Indonesia is a company engaged in the paint trade, where the main activity is selling various wall paints, oil / wood paints, NC paints (car paints), epoxy paints (floor paints), depo-proof (anti leaked). PT Indowarna Cemerlang Indonesia does not reuse sales transaction data resulting from its sales activities. This data is only used as a reference for making sales reports and as an archive only, causing accumulation of data and unknown paint brands that are often sold or those that are of interest to customers. Therefore, the author takes the title application of data mining analysis of customer purchase patterns in paint sales using a priori algorithm. By doing this research, it is expected to provide results in the form of information that can be useful for related parties and can design sales strategies to increase company turnover.