Analisa Data Penjualan Untuk Memprediksi Penjualan Barang Menggunakan Algoritma Asosiasi Dan Apriori - Utomo, Agung Tri (JATISI, 2024)
Data mining serves as a pivotal instrument for enhancing business performance through the utilization of information gleaned from information systems. This research employs association algorithms, notably the Apriori algorithm, to examine concurrent purchasing patterns at OnlyThrift.id, a thrift clothing store located in Salatiga. The investigation entails an analysis of sales transactions spanning one year, with the Apriori algorithm utilized to unearth association rules among items. Findings reveal the Apriori algorithm's capability to furnish solutions with commendable accuracy in discerning combinations among itemsets and aiding in the formulation of more optimal inventory arrangements. Disparities in processing time and the quantity of rules generated between the Apriori and FP-Growth algorithms are observed, with Apriori demonstrating swifter processing time albeit yielding a reduced number of rules. The research underscores the significance of implementing association algorithms, particularly Apriori, to optimize sales patterns and inventory management practices. It is envisaged that this study will provide value to researchers by expanding insights into association algorithm analysis and offering tangible solutions for enhancing business performance, particularly within the sales sector. Keywords — Data mining, association algorithms, apriori algorithm, purchasing patterns