The Use of Apriori Algorithm in the Formation of Association Rule at Lotteria Cibubur
DOI:
10.33395/sinkron.v4i2.10526Keywords:
Data mining, Menu, Apriori Algorithm, Database, association ruleAbstract
Lotteria as one of the franchises that produce sales data every day, has not been able to maximize the utilization of that data. The sale data storage is still not optimal. By utilizing sales transaction data that have been stored in the database, the management can find out the menus purchased simultaneously, using the association rule. Namely, data mining techniques to find the association rules of a combination of items. The process of searching for associations uses the help of apriori algorithms to produce patterns of the combination of items and rules as important knowledge and information from sales transaction data. By using the minimum support parameters, the minimum and the month period of the sales transaction to find the association rules, the data mining application generates association rules between items in April 2019, where consumers who buy hot / ice coffee will then buy float together with support of 16% and 100% confidence. Knowing which menu products or items are the most sold, thus lotteria Cibubur can develop a sales strategy to sell other types of menu products by examining the advantages of the most sold menu with other menus and can increase the stock of menu ingredients.
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References
Kanti, S., & Indrajit, R. E. (2017). Implementasi Data Mining Penjualan Handphone Oppo Store Sdc Tanggerang Dengan Algoritma Appriori. Seminar Nasional Sains Dan Teknologi, November, 1–2.
King, D. G., Young, W. E. V., Clarke, A. J., Cain, A. J., & Dimbleby, G. W. (1966). The Lanhill Long Barrow, Wiltshire, England: An Essay in Reconstruction. Proceedings of the Prehistoric Society, 32, 73–85. https://doi.org/10.1017/S0079497X00014341
Listriani, D., Setyaningrum, A. H., & Eka, F. (2018). PENERAPAN METODE ASOSIASI MENGGUNAKAN ALGORITMA APRIORI PADA APLIKASI ANALISA POLA BELANJA KONSUMEN (Studi Kasus Toko Buku Gramedia Bintaro). Jurnal Teknik Informatika, 9(2), 120–127. https://doi.org/10.15408/jti.v9i2.5602
Pahlevi, O., & Sugandi, A. (2019). Penerapan Algoritma Apriori Dalam Pengendalian Kualitas Produk. Jurnal & Penelitian Teknik Informatika, 3.
Putra, J. L., Raharjo, M., Sandi, T. A. A., Ridwan, R., & Prasetyo, R. (2019). Implementasi Algoritma Apriori Terhadap Data Penjualan Pada Perusahaan Retail. Jurnal Pilar Nusa Mandiri, 15(1), 85–90. https://doi.org/10.33480/pilar.v15i1.113
Rismayanti, Damayanti, F., & Khairunnisa. (2019). Penerapan Data Mining Algoritma C4 . 5 dalam Menentukan Rekam Jejak Kinerja Dosen STT Harapan Medan. 3, 99–104.
Santoso, H., Hariyadi, I. P., & Prayitno. (2016). Data Mining Analisa Pola Pembelian Produk. Teknik Informatika, 1, 19–24. http://ojs.amikom.ac.id/index.php/semnasteknomedia/article/download/1267/1200
Saw, B. M. (2019). Penerapan algoritma apriori dalam pembentukan association rule di lotteria cibubur.
Yanto, R., & Khoiriah, R. (2015). Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat. Creative Information Technology Journal, 2(2), 102. https://doi.org/10.24076/citec.2015v2i2.41