IMPLEMENTASI ALGORITMA APRIORI DALAM MENENTUKAN POLA PEMBELI CUSTOMER
DOI:
https://doi.org/10.55606/jitek.v3i2.1519Keywords:
Data mining, a priori algorithm, if associationAbstract
CV. Syahfira Bakery and Cake is a business engaged in the production of cakes, pastries and bread. The more a business develops, the transactions that occur daily also increase. However, sometimes the sales transaction data is not fully utilized properly by administrative staff and company owners. In fact, if it is processed and used by administrative staff and supervised by business owners, then sales data will have a major influence on product sales in the future. Data processing can be done using data mining techniques, these data sets can produce new information, one of which is customer purchasing patterns. Syahfira Bakery and Cake is a cake, sponge and bread shop that has not fully utilized data for determining sales business strategies. With these problems, it is necessary to use transaction data to be processed with the Apriori algorithm so that it can provide new knowledge that can be utilized by shop owners. Based on the research that has been done, from the 20 processed transaction data, results are obtained that meet a minimum support of 30% and a minimum confidence of 70% and one rule is obtained, namely if a customer buys chocolate jam products, he will buy plain bread
References
R. R. Putra dan C. Wadisman, “Implementasi Data Mining Pemilihan Pelanggan Potensial Menggunakan Algoritma K Means,” INTECOMS: Journal of Information Technology and Computer Science, vol. 1, no. 1, hlm. 72–77, 2018.
A. Sulistiyawati dan E. Supriyanto, “Implementasi Algoritma K-means Clustring dalam Penetuan Siswa Kelas Unggulan,” Jurnal Tekno Kompak, vol. 15, no. 2, hlm. 25–36, 2021.
D. Marlina, N. F. Putri, A. Fernando, dan A. Ramadhan, “Implementasi Algoritma K-Medoids dan K-Means untuk Pengelompokkan Wilayah Sebaran Cacat pada Anak,” J. CoreIT, vol. 4, no. 2, hlm. 64, 2018.
J. O. Ong, “Implementasi algoritma k-means clustering untuk menentukan strategi marketing president university,” 2013.
F. Yunita, “Penerapan Data Mining Menggunkan Algoritma K-Means Clustring Pada Penerimaan Mahasiswa Baru,” Sistemasi: Jurnal Sistem Informasi, vol. 7, no. 3, hlm. 238–249, 2018.
G. Gustientiedina, M. H. Adiya, dan Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” Jurnal Nasional Teknologi Dan Sistem Informasi, vol. 5, no. 1, hlm. 17–24, 2019.
A. N. Khormarudin, “Teknik Data Mining: Algoritma K-Means Clustering,” J. Ilmu Komput, hlm. 1–12, 2016.
A. N. Khormarudin, “Teknik Data Mining: Algoritma K-Means Clustering,” J. Ilmu Komput, hlm. 1–12, 2016.
M. N. M. Ediyanto dan N. Satyahadewi, “Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis,” Bimaster: Buletin Ilmiah Matematika, Statistika dan Terapannya, vol. 2, no. 02, 2013.
M. Z. Hossain, M. N. Akhtar, R. B. Ahmad, dan M. Rahman, “A dynamic K-means clustering for data mining,” Indonesian Journal of Electrical engineering and computer science, vol. 13, no. 2, hlm. 521–526, 2019.
R. Muliono dan Z. Sembiring, “Data Mining Clustering Menggunakan Algoritma K-Means Untuk Klasterisasi Tingkat Tridarma Pengajaran Dosen,” CESS (Journal of Computer Engineering, System and Science), vol. 4, no. 2, hlm. 272–279, 2019.
N. Rohmawati, S. Defiyanti, dan M. Jajuli, “Implementasi Algoritma K-Means Dalam Pengklasteran Mahasiswa Pelamar Beasiswa,” Jurnal Ilmiah Teknologi Infomasi Terapan, vol. 1, no. 2, 2015
