2020SinkrOnOpen access

The Use of Apriori Algorithm in the Formation of Association Rule at Lotteria Cibubur

Ovi Liansyah, Henny Destiana

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Abstract

Lotteria as one of the franchises that produce sales data every day, has not been able to maximize the utilization of that data. The sale data storage is still not optimal. By utilizing sales transaction data that have been stored in the database, the management can find out the menus purchased simultaneously, using the association rule. Namely, data mining techniques to find the association rules of a combination of items. The process of searching for associations uses the help of apriori algorithms to produce patterns of the combination of items and rules as important knowledge and information from sales transaction data. By using the minimum support parameters, the minimum and the month period of the sales transaction to find the association rules, the data mining application generates association rules between items in April 2019, where consumers who buy hot / ice coffee will then buy float together with support of 16% and 100% confidence. Knowing which menu products or items are the most sold, thus lotteria Cibubur can develop a sales strategy to sell other types of menu products by examining the advantages of the most sold menu with other menus and can increase the stock of menu ingredients.

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Lotteria as one of the franchises that produce sales data every day, has not been able to maximize the utilization of that data. The sale data storage is still not optimal. By utilizing sales transaction data that have been stored in the database, the management can find out the menus purchased simultaneously, using the association rule. Namely, data mining techniques to find the association rules of a combination of items. The process of searching for associations uses the help of apriori algorithms to produce patterns of the combination of items and rules as important knowledge and information from sales transaction data. By using the minimum support parameters, the minimum and the month period of the sales transaction to find the association rules, the data mining application generates association rules between items in April 2019, where consumers who buy hot / ice coffee will then buy float together with support of 16% and 100% confidence. Knowing which menu products or items are the most sold, thus lotteria Cibubur can develop a sales strategy to sell other types of menu products by examining the advantages of the most sold menu with other menus and can increase the stock of menu ingredients.

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Available abstract

Lotteria as one of the franchises that produce sales data every day, has not been able to maximize the utilization of that data. The sale data storage is still not optimal. By utilizing sales transaction data that have been stored in the database, the management can find out the menus purchased simultaneously, using the association rule. Namely, data mining techniques to find the association rules of a combination of items. The process of searching for associations uses the help of apriori algorithms to produce patterns of the combination of items and rules as important knowledge and information from sales transaction data. By using the minimum support parameters, the minimum and the month period of the sales transaction to find the association rules, the data mining application generates association rules between items in April 2019, where consumers who buy hot / ice coffee will then buy float together with support of 16% and 100% confidence. Knowing which menu products or items are the most sold, thus lotteria Cibubur can develop a sales strategy to sell other types of menu products by examining the advantages of the most sold menu with other menus and can increase the stock of menu ingredients.

Key concepts: Association rule learning, Apriori algorithm, Database transaction, Transaction data, Affinity analysis, Computer science, Data mining, Association (psychology)

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