DATA MINING UNTUK PROMOSI PRODUK MENGGUNAKAN METODE ASSOCIATION RULE PADA LOTTE GROSIR
Kata Kunci:
sales, a priori, transaction, association rulesAbstrak
Implementation of association rules on Mini data is a method used to explore data and analyze transaction data at Lotte Mart. Purchase transactions made by consumers are analyzed using the a priori algorithm. In this study it is known that the data processed is data taken from a certain time span, but it is hoped that it can represent the entire population at Lotte Mart. The results of this study found that there are several transactions that can be used as a basis for promoting products sold at Lotte Mart, this information is taken based on the results of data processing using a support value of 30%. All the antecedents found in the priori algorithm that form association rules are like if a consumer buys plain bread and free-range chicken eggs at the same time then there is a 95% chance that the customer will buy a car and the frequency of this transaction is 55%. The association rule which is the most likely rule to occur is when a customer buys plain bread and Belfoods Fav in the same transaction, the customer will buy crab sticks. The author hopes that Lotte Mart management can use the recommendations of this research to increase sales and reduce goods being discarded or returned to suppliers
Referensi
Alma, E., Utami, E., & Wahyu Wibowo, F. (2020). Implementasi Algoritma Apriori untuk Rekomendasi Produk pada Toko Online Implementation of Apriori Algorithms for Product Recommendations at Online Stores. Citec Journal, 7(1).
Arnomo, S. A. (2021). Market Basket Analysis pada Barang Minimarket dimasa Pandemi Market Basket Analys for Minimarket Goods in Pandemi. 9(2), 127–131. https://doi.org/10.26418/justin.v9i2.43243
Elisa, E. (2018). Market Basket Analysis Pada Mini Market Ayu Dengan Algoritma Apriori. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 2(2), 472–478. https://doi.org/10.29207/resti.v2i2.280
Gusrizaldi, R., & Komalasari, E. (2016). Analisis Faktor-Faktor Yang Mempengaruhi Tingkat Penjualan Di Indrako Swalayan Teluk Kuantan. Valuta, 2(2), 286–303.
Iskandar, A., Muttaqin, M., Dewi, S. V., Jamaludin, J., Irawati, H. M., Prianto, C., Siregar, R. S., Siregar, M. N. H., Chamidah, D., & Sinambela, M. (2021). Statistika Bidang Teknologi Informasi. Yayasan Kita Menulis.
Junaidi, A. (2019). Implementasi Algoritma Apriori dan FP-Growth Untuk Menentukan Persediaan Barang. 08, 61–67.
Kaur, H., & Singh, K. (2013). Market basket analysis of sports store using association rules. International Journal of Recent Trends in Electrical & Electronics, 3(1), 81–85.
Lestari, N., Gunawan, R. F., Informasi, S., Bangek, S., Tangah, K., & Sumatera, W. (2021). Implementasi Data Mining untuk Menentukan Pola Penjualan dengan Market Basket Analysis. Information System Research Journal, 1.
Mardi, Y. (n.d.). Jurnal Edik Informatika Data Mining: Klasifikasi Menggunakan Algoritma C4. 5 Data mining merupakan bagian dari tahapan proses Knowledge Discovery in Database (KDD). Jurnal Edik Informatika.
Masnur, A. (2015). Analisa Data Mining Menggunakan Market Basket Analysis untuk Mengetahui Pola Beli Konsumen. SATIN-Sains Dan Teknologi Informasi, 1(2), 32–40.
Mulya, Di. P. (2019). Analisa Dan Implementasi Association Rule Dengan Algoritma Fp-Growth Dalam Seleksi Pembelian Tanah Liat (Studi Kasus Di Pt. Anveve Ismi Berjaya). Jurnal Teknologi Dan Sistem Informasi Bisnis, 1(1), 47–57. https://doi.org/10.47233/jteksis.v1i1.6
Pohan, H. I., & Siswanto, B. (2021). Penerapan Association Rule Mining Pada Rekomendasi Bundling Produk Minimarket Menggunakan Oracle Data Miner. Jurnal Komputer Dan Informatika, 9(2), 154–159. https://doi.org/10.35508/jicon.v9i2.5145
Pujiarini, E. H. (2019). Analisis asosiasi untuk menentukan strategi promosi perguruan tinggi dengan algoritma apriori. Jurnal Informatika Dan Komputer (JIKO), 4(1), 45–51. http://jurnal.undhirabali.ac.id/index.php/jutik/article/view/1525
Wahyuningtias, Y., & Rusdiansyah, R. (2019). Analisis Penerapan Asosiasi Untuk Menentukan Transaksi Penjualan Pada What’S Up Café Dengan Metode Algoritma Apriori. Jurnal Riset Informatika, 1(4), 181–186. https://doi.org/10.34288/jri.v1i4.92
