DETERMINATION FOR CONSUMER PATTERNS IN BEVERAGE PRODUCT SALES USING THE FREQUENT PATTERN GROWTH ALGORITHM
(1) Department of Computer Science, Mercu Buana University
(2) Department of Computer Science, Mercu Buana University
Corresponding Author
Abstract
The culinary business is now increasingly developing and competition is increasing, so it requires a strategy to market the products to be sold. In the business sector, the results of the implementation of FP-Growth algorithm data mining can help business people find opportunities from consumption trends so that culinary business people can find out what types of products currently have the highest rating in the community so that managers can provide menu recommendations so they can increase sales turnover. The data required is a certain period of transaction data which is analyzed to produce product recommendations by the association rules. The design of this application uses HTML as the base system used in making websites, PHP as a means to develop websites, and SQL as a medium for data storage and processing. The testing process begins with the login process, then determines the support and confidence parameters, and determines the transaction time period. From the conclusion, managers can determine marketing strategies by increasing the stock of raw materials in beverage products that have the highest itemset value. Then the product with the lowest itemset value can provide promos or discounts on the purchase of goods to attract consumer buying interest.
Keywords
References
A. Junaidi, “Implementasi Algoritma Apriori dan FP-Growth Untuk Menentukan Persediaan Barang,” J. Sisfokom (Sistem Inf. dan Komputer), vol. 8, no. 1, hal. 61–67, 2019.
B. Mulyawan dan T. Sutrisno, “Product recommendation system on building materials shopping using FP-Growth algorithm Product recommendation system on building materials shopping using FP-Growth algorithm,” hal. 0–6, 2020.
A. N. Sagin dan B. Ayvaz, “Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector,” Southeast Eur. J. Soft Comput., vol. 7, no. 1, 2018.
A. Ikhwan et al., “A novelty of data mining for promoting education based on FP-growth algorithm,” Int. J. Civ. Eng. Technol., vol. 9, no. 7, hal. 1660–1669, 2018.
M. I. Perangin-angin, A. H. Lubis, dan A. Ikhwan, “Association Rules Analysis on FP-Growth Method in Predicting Sales,” Int. J. Recent Trends Eng. Res., vol. 3, no. 10, hal. 58–65, 2017.
Mustakim et al., “Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau,” J. Phys. Conf. Ser., vol. 1114, no. 1, 2018.
M. I. Ghozali, R. Z. Ehwan, dan W. H. Sugiharto, “Analisa Pola Belanja Menggunakan Algoritma Fp Growth, Self Organizing Map (Som) Dan K Medoids,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 8, no. 1, hal. 317–326, 2017.
M. Muslihudin dan A. Larasati, “Perancangan Sistem Aplikasi Penerimaan Mahasiswa Baru di STMIK Pringsewu Menggunakan PHP dan MYSQL,” J. TAM ( Technol. Accept. Model ), vol. 3, no. 1, hal. 12–23, 2014.
D. Firdaus, “Penggunaan Data Mining dalam Kegiatan Sistem Pembelajaran Berbantuan Komputer,” J. Format, vol. 6, no. 2, hal. 91–97, 2017.
F. Satria, Pemrograman WEB (HTML, CMS dan JavaScript). Yogyakarta: Andi Offset, 2016.
M. M. A. Fauzi, Program Database Visual Basic 6 and SQL Server 2000. Yogyakarta, 2013.
O. Muhammad Muslihudin, Analisis Dan Perancangan Sistem Informasi Menggunakan Model Terstruktur Dan UML. Yogyakarta: Andi Offset, 2016.
R. Amelia dan D. P. Utomo, “Analisa Pola Pemesanan Produk Modern Trade Independent Dengan Menerepakan Algoritma Fp. Growth (Studi Kasus: Pt. Adam Dani Lestari),” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, hal. 416–423, 2019.
F. Paper, U. Salamah, E. Maulana, dan U. M. Buana, “Development of Art Performance Tickets Information System At,” hal. 29–39.
Article Metrics
Abstract View
: 232 times
Download : 59 times
DOI: 10.56327/ijiscs.v5i2.982
Refbacks
- There are currently no refbacks.
