| Summary: | This research is conducted to analyze the shopping basket by using association rules in
the retail area, more specically in a home goods sales company such as appliances, computer
items, furniture, and sporting goods, among others. With the rise of globalization
and the advancement of technology, retail companies are constantly struggling to maintain
and raise their prots, as well ordering the products and services that the customer
wants to obtain. In this sense, they need a new approach to identify different objectives
in order to be more competitive and successful, looking for new decision-making
strategies. To achieve this goal, and to obtain clear and efficient strategies, by providing
large amounts of data collected in business transactions, the need arises to intelligently
analyze such data in order to extract useful knowledge that will support decision-making
and, an understanding of the association patterns that occur in sales-customer behavior.
Predicting which product will make the most prot, products that are sold together, this
type of information is of great value for storing products in inventory. Knowing when a
product is out of fashion can support inventory management effectively. In this sense,
this work presents the rules of association of products obtained by analyzing the data
with the FPGrowth algorithm using the Orange tool.
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