SALES DATA ANALYSIS USING TIME SERIES, APRIORI ALGORITHM, AND PROPHET

Abstract

This article presents a study on sales data from a computer store, using three tools: (1) application of the Apriori algorithm to identify association rules and consumption patterns; (2) time series analysis to understand how the data behaves over time, at different scales; and (3) application of the Prophet algorithm to decompose the historical sales series and make a prediction. The application of these tools together allowed for a more in-depth analysis of sales, including the detection of consumption behaviors and the identification of temporal patterns over time. The results provide valuable information for the company's strategic decision-making.