Analysis of Food Menu Purchasing Patterns in Campus Canteens Using the Apriori Algorithm in Data Mining
DOI:
https://doi.org/10.30865/ijics.v9i2.8919Keywords:
Apriori, data mining, campus cafeteria, purchasing pattern, market basket analysisAbstract
This study aims to identify purchasing patterns of food menus in the campus cafeteria of STMIK Mulia Darma by applying the Apriori algorithm within the data mining framework. The background of this research is based on the increasing volume of transaction data that remains underutilized in supporting managerial decision-making. The Apriori algorithm is employed to uncover associations between items frequently purchased together by calculating their support and confidence values. A dataset of 20 daily digital transactions was used as the basis for analysis. The results revealed a single valid association rule that met the minimum threshold: Nasi Goreng,Teh Manis with a support value of 15% and a confidence value of 60%. This finding indicates a strong tendency in student consumption behavior, which can be leveraged for marketing strategies such as menu bundling and predictive inventory management. The study demonstrates that the Apriori algorithm can offer practical and strategic insights in the context of a campus cafeteria and holds potential for further development using larger datasets and more advanced analytical methods.
References
Wikipedia Contributors, “Affinity analysis,” 2025.
Wikipedia Contributors, “Apriori Algorithm,” 2025.
A. Setiawan and R. Mulyanti, “Market Basket Analysis dengan Algoritma Apriori pada Ecommerce Toko Busana Muslim Trendy ( Market Basket Analysis with Apriori Algorithms in Ecommerce Trendy Muslim Clothing Stores ),” vol. 8, pp. 11–18, 2020.
V. Syahrul Bashiir and A. Witanti, “Market Basket Analysis Apotek Berbasis Web Menggunakan Metode Algoritma Apriori,” Informatics Artif. Intell. J., vol. 1, no. 2, p. 59, 2024.
R. Agrawal and R. Srikant, “Fast algorithms for mining association rules,” in Proc. 20th Int. Conf. Very Large Data Bases (VLDB), Santiago, Chile, 1994, pp. 487–499.
D. E. Saputro, A. Wulandari, and A. Prasetyo, “Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall,” J. Ilm. Komput. dan Inform., vol. 13, no. 1, pp. 15–23, 2024, [Online]. Available: https://www.researchgate.net/publication/391288122
F. Rahman and M. Indra, “Optimizing Customer Purchase Insights: Apriori Algorithm for Effective Product Bundle Recommendations,” Brill. Res. J., vol. 9, no. 1, 2024, [Online]. Available: https://jurnal.itscience.org/index.php/brilliance/article/view/4981
T. Rahman and M. Indra, “Penerapan Data Mining untuk Optimalisasi Menu Kantin Kampus Menggunakan Algoritma Apriori,” J. Teknol. dan Sist. Inf., vol. 12, no. 1, pp. 33–40, 2024.
N. Astuti, I. Fauzi, and R. Wulandari, “Analisis Pola Pembelian Makanan Mahasiswa Menggunakan Apriori untuk Rekomendasi Paket Menu,” in Proceedings of Seminar Nasional Teknologi Informasi dan Komunikasi (SENTIKA), 2024, pp. 51–58.
T. Prasetya, J. E. Yanti, A. I. Purnamasari, A. R. Dikananda, and O. Nurdiawan, “Analisis Data Transaksi Terhadap Pola Pembelian Konsumen Menggunakan Metode Algoritma Apriori,” INFORMATICS Educ. Prof. J. Informatics, vol. 6, no. 1, p. 43, 2022, doi: 10.51211/itbi.v6i1.1688.
P. M. S. Tarigan, J. T. Hardinata, H. Qurniawan, M. Safii, and R. Winanjaya, “Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Persediaan Barang,” J. Janitra Inform. dan Sist. Inf., vol. 2, no. 1, pp. 9–19, 2022, doi: 10.25008/janitra.v2i1.142.
P. W. Rahayu, I. N. Bernadus, and A. I. Datya, “Penerapan Data Mining Dalam Mengetahui Pola Transaksi Pembelian Obat Menggunakan Algoritma Apriori Di Apotek Kharisma Farma Tiga,” J. Komput. dan Inform., vol. 12, no. 1, pp. 44–55, 2024, doi: 10.35508/jicon.v12i1.13154.
A. E. Noviyanti and S. Juanita, “Rekomendasi Paket Pakaian Berdasarkan Pola PenjualanMenggunakan Algoritma Apriori,” J. SISFOTENIKA, vol. 14, no. 2, pp. 129–139, 2024, [Online]. Available: https://stmikpontianak.org/ojs/index.php/sisfotenika
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