Implementasi Data Mining dalam Memprediksi Stok Herbal menggunakan Algoritma Apriori

Authors

  • Fitriana Harahap Universitas Potensi Utama, Medan
  • Nidia Enjelita Saragih Universitas Potensi Utama, Medan
  • Ester Dayanti Paskaria Situmeang Universitas Potensi Utama, Medan
  • Elida Tuti Universitas Potensi Utama, Medan
  • Erwin Ginting Universitas Potensi Utama, Medan
  • Wirhan Fahrozi Universitas Potensi Utama, Medan

DOI:

https://doi.org/10.30865/mib.v6i2.3937

Keywords:

Data Mining, Apriori, Herbs, Tanagra

Abstract

Nafii Store is one of the stores engaged in selling herbal products. With the large number of public requests for herbal products during the COVID-19 pandemic, stock availability is needed to increase sales transactions for these products. To avoid the limited supply of herbs, an information system is needed that can help store leaders to find out what kind of products should be increased in stock according to customer demand. The appropriate application to overcome these problems is the development of the concept of data mining. Based on the Nafii Store herbal sales data sample, which amounted to 24 transactions, this study will use a minimum support = 16% and a minimum confidence = 70%. The results of the determination of the Association Rules and testing with the Tanagra application that the pattern of herbal purchases are: If you buy Baarik Forest Honey 800 grams then buy Baarik Forest Honey 470 grams 80%, If you buy Black Seed with Ajwa Kurma stamps then buy Darusyifa Black Bitter Honey 83.3%, If buy Darusyifa Bitter Black Honey then buy Black Seed with Ajwa Dates stamped 83.3%. The results of this study can be used by the store management to make decisions on the availability of herbal products at the Nafii Store.

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Published

2022-04-25

Issue

Vol. 6 No. 2 (2022): April 2022

Section

Articles

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