Data Mining Implementation Of Electronic Products Sales Using Apriori Algorithm (Case Study Of Fokus Komputer Shop)

Abstract

Focus Komputer Store is one of the computer shops in Bengkulu City which is the destination for consumers in looking for computer-related goods and providing computer service services. Every day the sales transaction data in stores continues to grow and causes a very large data storage. Most sales transaction data are only used as archives without being put to good use. The process of selecting goods is carried out by taking into account the pattern of purchases in the previous month so that a list of items that must be provided is more extensive to meet current consumer needs. The problem is market interest or consumer needs are always changing depending on uncertain conditions. The process of selecting goods to fill stock is a very complicated process and takes a long time because you have to read the sales archives that were made the previous month. For this reason, it is necessary to have an application that can provide recommendations on what items are currently in demand by consumers based on last month's sales data. Applications that can be used for the process of extracting previous data are data mining applications. Data mining is an analysis of reviewing data sets to find unexpected relationships and summarize data in different ways that are understandable and useful to the data owner. To be able to get results that are more relevant to needs, applications must use suitable algorithms, one of which is the Apriori algorithm. The a priori algorithm is an algorithm that searches for frequent itemsets using the association rule technique. The application can be used as a sales cashier application at the Computer Focus store and can display the results of a priori algorithm calculations based on sales data that has been input into the application. The application that the author has built still has many shortcomings, especially in terms of appearance and data. The author hopes that there are criticisms and suggestions that can help in developing applications so that they are even better.