Determination of Sales Pattern of Photocopier Spare parts On CV. Andalan Using FP-Growth Algorithm

Abstract

CV. ANDALAN engaged in goods and services based in Jakarta, a company that sells photocopier spare parts. The growing competition in the business world demands developers to find something that can increase sales and marketing of products in their company, one of which is by utilizing technology to help predict the spare parts that are most often in demand by consumers. So far CV. ANDALAN lack of analyzing the inventory of spare parts in the warehouse, besides that the company does not know if the previous year's sales products are more increased than the following year, and what products are the best-selling in the company while the amount of data is so large can be a problem and overwhelmed in calculating the products in the company. Therefore, a new innovation is needed that can provide a strategic information that is data mining. With the holding of associations on photocopier spare parts transactions using FP-Growth algorithm, CV. ANDALAN is expected to immediately know what products are most in demand by consumers. So it is expected to increase the sales of photocopier spare parts, so as not to occur losses on CV. ANDALAN.