APPLICATION OF DATA MINING IN GROCERY SALES USING THE FP-GROWTH ALGORITHM
Abstract
Sales of basic needs today require the use of information technology. The problem that often occurs is providing the best service to customers with the right business strategy to avoid business losses. Business actors are required to determine strategies that can increase sales of the products being sold. It is often found that transaction data is always increasing but is often not utilized properly. Another way is to determine a basic food sales strategy using data mining techniques. The technique used is the Fp-Growth Algorithm, which is an algorithm that generates frequent itemsets which will later be useful in the process of determining rules that can generate a choice. The Fp-Growth Algorithm is a development of the Apriori Algorithm. It's just that the Fp-Growth Algorithm uses tree development in searching for the types of goods that are often purchased. The data used are 26 types of basic food products and 30 transaction data. In this study, the minimum support value was 30% and the minimum confidence value was 60%.
Keywords:Â Groceries, Data mining, Frequent itemset, Fp-Growth.
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A. Singh, J. Agarwal, and A. Rana, “Performance Measure of Similis and FP-Growth Algorithm,†Int. J. Comput. Appl., vol. 62, no. 6, pp. 25–31, 2013, doi: 10.5120/10085-4712.
A. R. Riszky and M. Sadikin, “Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan,†J. Teknol. dan Sist. Komput., vol. 7, no. 3, pp. 103–108, 2019, doi: 10.14710/jtsiskom.7.3.2019.103-108.
A. H. Nasyuha, Zulham, I. Jang Cik, M. Amin, S. Candra Setia, and D. Siregar, “An Integrated Multi Criteria Decision Making Method for Fashion Selection,†J. Phys. Conf. Ser., vol. 1424, no. 1, 2019, doi: 10.1088/1742-6596/1424/1/012030.
A. M. Bachtiar and M. Rivki, “Jurnal Sistem Informasi ( Journal of Information Systems ). 2/3 ( 2017 ), 90-96,†Tantangan Dan Hambatan Implementasi Prod. Uang Elektron. Di Indones. Stud. Kasus Pt Xyz, vol. 13, no. 1, pp. 38–48, 2017, [Online]. Available: https://jsi.cs.ui.ac.id.
N. Lestari, “Penerapan Data Mining Algoritma Apriori Dalam Sistem Informasi Penjualan,†Edik Inform., vol. 3, no. 2, pp. 103–114, 2017, doi: 10.22202/ei.2017.v3i2.1540.
F. Fitriyani, “Implementasi Algoritma Fp-Growth Menggunakan Association Rule Pada Market Basket Analysis,†J. Inform., vol. 2, no. 1, 2016, doi: 10.31311/ji.v2i1.85.
S. Nasreen, M. A. Azam, K. Shehzad, U. Naeem, and M. A. Ghazanfar, “Frequent pattern mining algorithms for finding associated frequent patterns for data streams: A survey,†Procedia Comput. Sci., vol. 37, pp. 109–116, 2014, doi: 10.1016/j.procs.2014.08.019.
M. Narvekar and S. F. Syed, “An optimized algorithm for association rule mining using FP tree,†Procedia Comput. Sci., vol. 45, no. C, pp. 101–110, 2015, doi: 10.1016/j.procs.2015.03.097.
G. Gunadi and D. I. Sensuse, “Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori Dan Frequent Pattern Growth ( Fp-Growth ) :,†Telematika, vol. 4, no. 1, pp. 118–132, 2012.
S. Liu and X. Jiyi, “An improved apriori algorithm based on matrix,†Proc. - 2020 12th Int. Conf. Meas. Technol. Mechatronics Autom. ICMTMA 2020, vol. 14, no. 5, pp. 488–491, 2020, doi: 10.1109/ICMTMA50254.2020.00111.
R. Yanto and R. Khoiriah, “Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat,†Creat. Inf. Technol. J., vol. 2, no. 2, p. 102, 2015, doi: 10.24076/citec.2015v2i2.41.
M. S.Mythili and A. R. Mohamed Shanavas, “Performance Evaluation of Apriori and FP-Growth Algorithms,†Int. J. Comput. Appl., vol. 79, no. 10, pp. 34–37, 2013, doi: 10.5120/13779-1650.
Meilani, B. Dwi, and W. Azmuri, “Penentuan Pola Yang Sering Muncul Untuk Penerima Kartu Jaminan Kesehatan Masyarakat,†Semin. Nas. "Inovasi dalam Desain dan Teknol., pp. 424–431, 2015.
Azhari and Anshori, “Pendekatan aturan asosiasi untuk analisis pergerakan saham,†Knowl. Creat. Diffus. Util., vol. 2009, no. semnasIF, pp. 183–189, 2009.
A. S. A. Alghamdi, “Efficient Implementation of FP Growth Algorithm-Data Mining on Medical Data,†Int. J. Comput. Sci. Netw. Secur., vol. 11, no. 12, pp. 7–16, 2011.
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