Perbandingan Algoritma Apriori Dan Fp Growth Terhadap Market Basket Analysis Pada Data Penjualan Bakery

Muhammad Fathurrahman(1*), Adi Rizky Pratama(2), Tohirin Al-Mudzakir(3),

(1) Universitas Buana Perjuangan, Karawang, Indonesia
(2) Universitas Buana Perjuangan, Karawang, Indonesia
(3) Universitas Buana Perjuangan, Karawang, Indonesia
(*) Corresponding Author

Abstract


Tight competition in the business world makes bakery business people have to think harder in developing strategies to face this competition. In addition, the problems experienced by business people are having difficulty knowing consumer purchasing patterns due to limitations in analyzing bakery transaction data. So in this problem it is necessary to apply the Market Basket analysis method to find out consumer buying patterns. Market basket analysis is a methodology for analyzing consumer buying habits by finding associations between several different items that consumers place in a shopping basket that they buy in a particular transaction. The results in this study on the combination pattern obtained from the association method with the a priori algorithm, namely having the highest confidence combination pattern is Alfajores, then you also buy coffee with a confidence value of 54.06%, and if you buy cake, you also buy coffee with a confidence value of 52.69%. . While the results of the combination pattern obtained from the association method with the fp-growth algorithm are if you buy Pastry then you also buy Coffee with a confidence value of 55.21%, and if you buy Cookies then you also buy Coffee with a confidence value of 51.84..

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DOI: https://doi.org/10.30645/kesatria.v4i2.161

DOI (PDF): https://doi.org/10.30645/kesatria.v4i2.161.g160

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