Prediksi Jumlah Kebutuhan Biji Kopi Berdasarkan Pola Konsumsi Konsumen dengan Algoritma Apriori - Ridwan Sutri; Billy Hendrik; Rini Sovia (Bulletin of Computer Science Research, 2025)
Coffee bean prediction is needed for optimal inventory management to maintain efficiency. This data grouping is taken from customer shopping consumption patterns. Based on the research aims to predict the amount of coffee bean needs based on consumer consumption patterns by applying the Apriori algorithm. Utilization of processed transaction data can provide what steps should be taken in the future. Based on this, this study aims to predict the amount of coffee bean needs based on consumer consumption patterns with the Apriori algorithm. The Apriori algorithm forms association rules based on a combination of data indicators used. These data indicators are sourced from Freehand Coffee. Based on the use of the Apriori algorithm in predicting coffee bean needs based on consumer consumption patterns, the results showed that the Apriori algorithm is able to provide product recommendations in the form of associative or consumer transaction patterns by collecting transaction data and then experimenting with existing data indicators. The contribution of this research can help Freehand Coffee to estimate coffee bean needs and optimize stock management, this research also helps in selecting drinks based on consumer consumption.