Penerapan Data Mining Asosiasi pada Pola Transaksi dengan Metode Apriori

Nita Syahputri

Abstract


Indonesian business is a promising thing, the competition that occurs in the business of business people is always trying to be strategic and breakthroughs that can ensure the continuity of what they do. The youngest business cafe / restaurant, especially among young people to adults. The development of the Café / Restaurant business in Indonesia is growing rapidly, this can be seen from the many cafes / restaurants that have emerged which provide attractive interior design venues and offer a comfortable and pleasant atmosphere to gather with family and friends. Many competitors in business, especially in cafes / restaurants, require developers to find strategies that can increase sales, one of which is the use of transaction data.Data Mining is the process of extracting information from data sets through the use of algorithms and techniques involving the fields of statistics, machine learning, and database management system. A priori algorithms are a type of association rule in data mining. In this study using secondary data. The results of calculations and analysis of consumer research using Data Mining with the Apriori Algorithm method, overall from the sales sample data obtained 52 association rules that meet support above 20% and 50% confidence. Based on the test results using Rapidminer, it can be rejected by that the product that consumers are more interested in is the minimum confidence above 50%.

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References


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DOI: http://dx.doi.org/10.30645/j-sakti.v4i2.345

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