Implementasi Algoritma Frequent Growth (FP-Growth) Menentukan Asosiasi Antar Produk
DOI:
https://doi.org/10.30865/json.v4i1.4894Keywords:
Sales, Data Mining, Association Rules, Frequent Itemset, FP-Growth, FP-TreeAbstract
Data accumulation is caused by the amount of transaction data stored. By utilizing the sales transaction data in the database, the data can be further processed into useful information for managers to make decisions. With the existence of data mining, it is hoped that it can help the Leaning Shop to find the information contained in the transaction data into new knowledge. Association Rule, which is a procedure in Market Basket Analysis to find relationships between items in a data set or it can be said that this association rule aims to find a collection of items that often appear at the same time and display them in the form of consumer habits in shopping. The FP-Growth algorithm is an algorithm that can be used to determine the data set that appears most often (frequent itemset) in a data, in the search for frequent itemset in a data set by generating a prefix-tree structure or often called the FP-Tree. From the test results it can be concluded that the application of data mining using the FP-Growth Algorithm can be used to analyze consumer spending patterns.
References
Kusrini and Emha Taufiq Luthfi, Algoritma Data Mining, 1st ed., Theresia Ari Prabawati, Ed. Yogyakarta: ANDI, 2009.
Erwin, "Analisis Market Basket Dengan Algoritma Apriori dan FPGrowth," vol. 4, Juli 2009.
Kennedi Tampubolon, Hoga Saragih, and Bobby Reza, "Implementasi Data Mining Algoritma Apriori Pada Sistem Persediaan Alat-Alat Kesehatan," Informasi dan Teknologi Ilmiah (INTI), vol. 1, Oktober 2013.
Nugroho Wandi, Rully A Hendrawan, and Ahmad Mukhlason, "Pengembangan Sistem Rekomendasi Penelusuran Buku dengan Penggalian Association Rule Menggunakan Algoritma Apriori (Studi Kasus Badan Perpustakaan dan Kearsipan Provinsi Jawa Timur)," JURNAL TEKNIK ITS, vol. 1, September 2012.
Fajar Astuti Hermawati, Data Mining, 1st ed., Putri Christian, Ed. Yogyakarta: ANDI, 2013.
David Samuel, "Penerapan Stuktur FP-Tree dan Algoritma FP-Growth dalam Optimasi Penentuan Frequent Itemset," Institut Teknologi Bandung, vol. 1, 2008.
Juanta Madus, Afriyudi , and Irwansyah , "Aplikasi Penentuan Waris Pada Perangkat Mobile Menggunakan Java (J2ME)," Jurnal Ilmiah, April 2012.
Nurjaya Mirwan, Hari Gusmita Ria, and Yusuf Durrachman, "Aplikasi Pencarian Makna Kata Dalam Bahasa Indonesia Dengan Teknologi Java 2 Micro Edition (J2ME)," 2006.
Emha Taufiq Luthfi and Kusrini, Algoritma Data Mining. Yogyakarta: Andi Offset, 2009.
Daniel T Larose, Discovering Knowledge in Data : An Introduction to Data Mining. New Jersey: John Wiley & Sons, 2005.
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