Implementasi Data Mining dalam Menganalisis Pola Pembelian Produk Toko Oleh-Oleh Umrah dan Haji
Main Article Content
One of the methods that is often applied in Data Mining technology is the Association Rule Mining technique. The Association Rule Mining method aims to find patterns of relationships between items sold in a database and in the retail business is often referred to as Market Basket Analysis. Market Basket Analysis is an analysis method used to understand consumer behavior by identifying purchase patterns from transaction data, besides that this method can also be useful for maintaining the inventory of goods sold. The research methods used are research design methods, method research questions, data collection tools, data analysis, and data validation. The results obtained from this study are the threshold value used is support ≥ 10% and confidence ≥ 30%. The results of the analysis showed the best rule, namely: "Nuts, Honey → Prayer Rugs" with a confidence value of 59%. This means that consumers who buy Nuts and Honey have a 59% chance that they will also buy a prayer mat. This research contributes to efforts to improve the efficiency of stock management and understand consumer behavior through the analysis of purchasing patterns which is ultimately expected to increase customer satisfaction and store sales
Fabrianto, L. (2022). Shopping Behavior At Certain Times And Weeks Using Data Mining Methods Analysis Of Consumer. Mantik, 6(2), 1946.
Fabrianto, L., Faizah, N. M., Prasetyo, J. H., Prakoso, B. S., & Wiharso, G. (2021). Aturan Asosiasi Antar Item Terjual pada Data Penjualan Minimarket Milik Komunitas di Hari Besar Tertentu Menggunakan Algoritma Apriori. JURNAL AKUNTANSI, EKONOMI Dan MANAJEMEN BISNIS, 9(2), 208–215. https://doi.org/10.30871/JAEMB.V9I2.3621
Fadhli, M., Ketua Dewan Editor Zulfan, Mk., Editor Pelaksana Munawir, M., Baihaqi, M., Sekretaris Yeni Yanti, M., Mitra Bestari Ir Yuwaldi Away, M., Gani, T. A., & Melinda, Me. (2018). Data Mining Penjualan Produk Dengan Metode Apriori Pada Indomaret Galang Kota. Jurnal Nasional Komputasi Dan Teknologi Informasi (JNKTI), 1(2). https://doi.org/10.32672/JNKTI.V1I2.771
Giannakoulopoulos, A., Pergantis, M., Limniati, L., & Kouretsis, A. (2022). Investigating the Country of Origin and the Role of the .eu TLD in External Trade of European Union Member States. Future Internet 2022, Vol. 14, Page 174, 14(6), 174. https://doi.org/10.3390/FI14060174
Kaur, M., & Kang, S. (2016). Market Basket Analysis: Identify the Changing Trends of Market Data Using Association Rule Mining. Procedia Computer Science, 85, 78–85. https://doi.org/10.1016/J.PROCS.2016.05.180
Kurniawan, F., Umayah, B., Hammad, J., Nugroho, S. M. S., & Hariadi, M. (2017). Market Basket Analysis to Identify Customer Behaviours by Way of Transaction Data. Knowledge Engineering and Data Science, 1(1), 20. https://doi.org/10.17977/UM018V1I12018P20-25
Mantik, J., Fabrianto, L., Prasetyo, J. H., Faizah, N. M., & Solichatun, S. (2023). Inventory management for essential oil UMKM: enhancing business performance with data mining. Jurnal Mantik, 7(2), 702–711. https://doi.org/10.35335/MANTIK.V7I2.3909
Nasution, M. R. A., & Hayaty, M. (2019). Perbandingan Akurasi dan Waktu Proses Algoritma K-NN dan SVM dalam Analisis Sentimen Twitter. Jurnal Informatika, 6(2), 226–235. https://doi.org/10.31311/ji.v6i2.5129
Nosiel, N., Sriyanto, S., & Maylani, F. (2021). Perbandingan Teknik Data Mining Untuk Prediksi Penjualan Pada UMKM Gerabah. Prosiding Seminar Nasional Darmajaya, 1, 72–86.
Nurhidayanti, D., Kurniawati, I., & Artikel, S. (2022). Implementasi Algoritma Apriori Dalam Menemukan Association Rules Pada Persediaan Sparepart Motor. Innovation in Research of Informatics (INNOVATICS), 4(2), 62–67.
Pambudi, G. S., Sriyanto, S., & Arvianto, A. (2017). RANCANG BANGUN SISTEM INFORMASI MANAJEMEN ASET BERBASIS WEB UNTUK OPTIMALISASI PENELUSURAN ASET DI TEKNIK INDUSTRI UNDIP. J@ti Undip: Jurnal Teknik Industri, 11(3), 187–196. https://doi.org/10.14710/JATI.11.3.187-196
Profitabilitas Pada Perusahaan Perbankan Yang Terdaftar Di Bursa Efek Indonesia Bayu Wulandari, T., Veronica, V., & Prima Indonesia, U. (2022). Pengaruh Dana Pihak Ketiga, Risiko Kredit, Loan to Deposit Ratio Dan Struktur Modal Terhadap Profitabilitas Pada Perusahaan Perbankan Yang Terdaftar Di Bursa Efek Indonesia. Management Studies and Entrepreneurship Journal (MSEJ), 3(2), 325–335. https://doi.org/10.37385/MSEJ.V3I2.414
Saputra, R., & Sibarani, A. J. P. (2020). Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat. JATISI (Jurnal Teknik Informatika Dan Sistem Informasi), 7(2), 262–276. https://doi.org/10.35957/JATISI.V7I2.195
Shelke HVPM COET, R. R., V Dharaskar Former Director, A. R., & Thakare, V. M. (n.d.). Data Mining For Supermarket Sale Analysis Using Association Rule. International Journal of Trend in Scientific Research and Development, 1(4), 2456–6470.
Sudrajat, A. W., & Ermatita. (2021). Penerapan Metode Association Rule Mining Dalam Pengembangan Umkm Dengan Algoritma FP-Growth. Prosiding Seminar Nasional Aplikasi Sains & Teknologi (SNAST), 1(1), 147–155.
Surohman, S., Fabrianto, L., Riza, F., & Faizah, N. M. (2021). Korelasi Antara Profil dan Nilai Akademis Siswa dengan Menggunakan Algoritma K-Means. Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(4), 845. https://doi.org/10.25126/jtiik.2021843034
Wahyudi, E. N., Utomo, A. P., & Mariana, N. (2019). Pengelompokan Jenis Usaha Umkm Kota Semarang Dalam Rangka Proses Pembinaan Dan Pendampingan Untuk Pengembangan Usaha Dengan Teknik Data Mining. Dinamik, 24(1), 13–20. https://doi.org/10.35315/dinamik.v24i1.7840