Analysis of Goods Stock Using the Apriori Algorithm to Aid Goods Purchase Decision Making - Azis, Nur; Sucipto, Purwo Agus; Herwanto, Agus; Munthe, Era Sari; Irwanto, Dola (Politeknik Ganesha Medan, 2024)
After the covid-19 pandemic outbreak and the high uncertainty index during the covid-19 pandemic. The business world is experiencing a huge impact in addition to the sluggish interest of buyers is also limited in its movement. On this occasion, the researcher intends to provide an overview that can help business people, especially in purchasing goods that are useful for filling the stock of goods in the warehouse. To get maximum results and minimum error rate. Researchers use the Apriori Algorithm in analyzing stock items and use the Tanagra version 1.4 application. Research data used the sales history of the past 1 year here the data used is between May 2022 and April 2023. With a total itemset of 375. But after applying the Golden Rule (threshold), there are only 10 products with sales reaching 1623 items. This research produces a final ordered association based on the minimum support and minimum confidence that has been determined, namely 12 rules with a combination of 2 itemsets with a confidence value of 100%.