Penerapan Data Mining Untuk Menganalisis Penjualan Produk Menggunakan Algoritma Apriori Berbasis WEB

Authors

  • Syarief Afifi Sumantri Universitas Negeri Medan
  • Hermawan Syahputra Universitas Negeri Medan

DOI:

https://doi.org/10.55606/jurrimipa.v2i2.1532

Keywords:

Data Mining, Apriori Algorithms, Transaction Data, Websites

Abstract

This study aims to determine the best selling food and beverage products at Caffe Kopi Kito. Data mining is the process of extracting useful information and patterns from very large data. Data mining includes data collection, data extraction, data analysis, and data statistics. The Apriori algorithm is a classic algorithm in data mining. This algorithm is used to see the intensity of occurrence of the relevant itemset or frequent items or association rules. This study uses consumer transaction data for 30 days in January 2023. Transaction data will be collected first based on the day and number of transactions, then the transaction data that has been collected will be grouped according to each item, the data that has been grouped will be carried out a priori algorithm process to determine the most dominant product. Then a system design will be carried out whose result will be a website. The results showed that using the website-based a priori algorithm could determine the most dominant product at Caffe Kopi Kito and make it easier for users to determine the most dominant product. Based on the results of product sales analysis at Cafee Kopi Kito, it can be concluded that working on the a priori algorithm on Caffe Kopi Kito using a website can be said to have the result of a product combination and in the future it can be used to create the best-selling menu packages at Cafee Kopi Kito.

References

Ade, H., (2016): Pemodelan UML Sistem Informasi Monitoring Penjualan dan Stok Barang (Studi Kasus: Distro Zhezha Pontianak, Jurnal Khatulistiwa Informatika, 4(2).

Agus, N., T. H., (2016): Implementasi Algoritma Apriori Untuk Analisa Penjualan Dengan Berbasis Web, Jurnal Simetris, 7(2). 701-706.

Desak, M, D, U, P., S. B., (2017): Penerapan Data Mining Pada Penjualan TAN’S BAKERY Menggunakan Algoritma Apriori, Jurnal TIK, 3(2). 164-174.

Desti, F. (2016): Implementasi Data Mining untuk Menentukan Kombinasi Media Promosi barang Berdasarkan Perilaku Pembelian pelanggan Menggunakan Algoritma Apriori, Annual Research Seminar , 2(1). 473.

Gama, A. W. O., Putra, I. K. G. D., & Bayupati, I. P. A. (2016). Majalah ilmiah teknologi elektro. Majalah Ilmiah Teknologi Elektro (Vol. 15).

Gunadi, G., & Sensuse, D. I. (2016). Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori dan Frequent Pattern Growth (FP-Growth) : Studi Kasus Percetakan PT. GRAMEDIA. Telematika MKOM, 4(1), 118–132.

Khairul U., (2015): Analisa Data Mining Dalam Penjualan Sparepart Mobil Dengan Menggunakan Metode Algoitma Apriori, Jurnal Sistem Informasi, ISSN : 2085–1367.

Muhammad, F., F. A, S., (2019): Analisis Algoritma Apriori Pada Pemesanan Konsumen Di Café The L.CO Coffe, Jurnal SAINTEK, 1(1). 52-57.

Santosa, B. (2007). Data Mining: Teknik Pemanfaatan Data untuk Keperluan Bisnis. Yogyakarta: Graha Ilmu.

Tika, D, A., T, I, H., I, K., (2017): Analisis Data Mining Menggunakan Algoritma Aprioti Untuk Meningkatkan Cross Selling Dan Up Selling (Studi Kasus Rumah Makan Mas Nur Perwakarta), Jurnal TIK.

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Published

2023-10-30

How to Cite

Syarief Afifi Sumantri, & Hermawan Syahputra. (2023). Penerapan Data Mining Untuk Menganalisis Penjualan Produk Menggunakan Algoritma Apriori Berbasis WEB. JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM, 2(2), 135–146. https://doi.org/10.55606/jurrimipa.v2i2.1532