Peningkatan Penjualan Oriental Cafe Menggunakan Algoritma Apriori

Abstract

Service improvement is the most important aspect in business processes, one of which is in the field of food and beverage sales. Oriental cafe is one of the restaurants engaged in food and beverage. Sales in 2020 decreased by 13% due to decreased customer interest in providing product packages that affect customer service. Provision of a package system can be done by studying customer habits in buying food and beverages. One of the alternatives used is Data Mining, namely market basket analysis, market basket analysis can create product patterns that are often purchased by customers so that they can become rules for making product package systems. In this study, the data was tested using the association rule with an a priori algorithm. The a priori algorithm has the advantage of being simpler in data processing and can handle quite large data. From the results of the discussion and data analysis carried out, it can be concluded that by applying the a priori algorithm in determining the combination between itemsets with a minimum support of 30% and a minimum of 70% confidence, one association rule is found, which has the highest support and confidence value if the customer places an order for the Mineral menu. , Fish and Rice simultaneously with a support value of 30% and a confidence value of 100%. Thus, if there are customers who buy minerals, the probability of those customers buying fish, rice is 100%.

Keywords

• Penjualan, Market Basket Analysis, Data mining, Asosiasi, Apriori