Apriori Algorithm and Business Intelligence Methods for Bookstore’s Customer Preferences Analysis

Abstract

This study explores the use of a priori algorithm in analyzing sales transaction
data at Rony Jaya Bookstore. By combining data mining and business
intelligence, the study successfully uncovered significant customer buying
patterns, which were then used to support strategic decision-making. The
results of the analysis showed that there was a close relationship between
certain book categories, such as Fiction Books and Educational Books with a
confidence level of 87.5%, as well as Non-Fiction Books and Educational
Books with a confidence level of 88.89%. These findings provide valuable
insights into developing marketing strategies, such as creating custom
promotional packages and arranging product layouts in stores to make them
more appealing to customers. This research also highlights the importance of
ensuring data quality so that the resulting analysis is more accurate and
relevant. Overall, the study offers a practical guide for Rony Jaya Bookstore
and other businesses looking to leverage data mining and business intelligence
technologies to improve efficiency and customer satisfaction.