PENERAPAN ALGORITMA APRIORI UNTUK MENENTUKAN POLA PENJUALAN BARANG HARIAN PADA MINI MARKET AYU

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dc.contributor.authorSyafitri, Ulfa
dc.contributor.supervisorRisanto, Joko
dc.date.accessioned2023-05-04T08:06:41Z
dc.date.available2023-05-04T08:06:41Z
dc.date.issued2023-01
dc.description.abstractThe amount of compettion, especially in the daily sales, requires the owners of shop to find strategies to increase daily sales, namely by knowing the pattern of daily sales so that owners can implement appropriate steps to increase selling power. Sales transactions can be used to determine the pattern of daily sales. Sales patterns can be processed into information by applying data mining methods with association rule techniques with a priori algorithms. Processing of daily goods sales transaction data of 7092 transaction data with a minimum support of 20 and a minimum of 50% confidence resulted in 32 association rules. In the lift ratio test, there are 12 association rules with a value of more than 1, meaning that there is a dependency between the antecedent and the consequent so that the rule can be used as a prediction of the appearance of a daily item due to the appearance of other daily items and can be used as a reference in recommending daily items.en_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10976
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectApriorien_US
dc.subjectAssociation Ruleen_US
dc.subjectData Maningen_US
dc.subjectDaily Salesen_US
dc.subjectMarket Basket Analysisen_US
dc.titlePENERAPAN ALGORITMA APRIORI UNTUK MENENTUKAN POLA PENJUALAN BARANG HARIAN PADA MINI MARKET AYUen_US
dc.typeArticleen_US

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