Market Basket Analysis Pada Mini Market Ayu Dengan Algoritma Apriori

  • erlin elisa universitas putera batam
Keywords: Data Mining, Market Basket Analysis, Association Rules, Apriori Algorithms


Data mining is a technique to extract new information from the data warehouse, information is considered very important and valuable because by mastering the information so easily to achieve a goal, this makes everyone competing to obtain information, as well as on trading businesses such as minimarket Ayu in Kota Batam. Minimarket is located close to the home of the population, this certainly affects the level of sales, with the daily sales activities, sales transaction data will continue to grow, causing data storage is greater. Sales transaction data is only used as an archive without being put to good use. Basically the data set has very useful information. The analysis of market basket with Apriori Algorithm is one method of data mining which aims to find the pattern of association based on consumer spending pattern, so that it can be known what items are purchased simultaneously. The result of this research found that the highest support and confidence value is Oil and Milk with a support value of 42.85% and confidence of 85.71%.


[1] Subarsono, D. (2014). Perbedaan Pelayanan Pada Ritel Tradisional Dengan Ritel Modern Di Kota Cirebon ., 2(2).
[2] Subarsono, D. (2014). Perbedaan Pelayanan Pada Ritel Tradisional Dengan Ritel Modern Di Kota Cirebon ., 2(2).
[4]. Fauzy, M., & Asror, I. (2016). Penerapan Metode Association Rule Menggunakan Algoritma Apriori Pada Simulasi Prediksi Hujan Wilayah Kota Bandung, II(2).
[5] Wulandari, H. N. (2014). Pemanfaatan Algoritma Apriori untuk Perancangan Ulang Tata Letak Barang di Toko Busana.
[6] Santoso, H., Hariyadi, I. P., & Prayitno. (2016). Data Mining Analisa Pola Pembelian Produk. Teknik Informatika, (1), 19–24.
[7] Jiawei Han And Micheline Kamber. (2006). “ Data Mining : Concepts and Techiques ”. San Fransisco : Morgan Kaufmann Publishers
[8] Gamarra, C., Guerrero, J. M., & Montero, E. (2016). A knowledge discovery in databases approach for industrial microgrid planning. Renewable and Sustainable Energy Reviews, 60, 615–630.
[9] Gunadi, G., & Sensuse, D. I. (2012). Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori Dan Frequent Pattern Growth ( FP-GROWTH ), 4(1).
[10] Putro, A. N. S., Ernawati, & Wisnubhadra, I. (2016). Market Basket Analysis Pada Magister Teknik Informatika , Universitas Atma Jaya Yogyakarta, 978–979
[11] Buulolo, E. (2017). ImplementasiI Algoritma Apriori Pada Sistem Persediaan Obat ( Studi Kasus : Apotik Rumah Sakit Estomihi ).
[12] Solnet, D., Boztug, Y., & Dolnicar, S. (2016). An untapped gold mine? Exploring the potential of market basket analysis to grow hotel revenue. International Journal of Hospitality Management, 56, 119–125.
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