MARKET BASKET ANALYSIS USING THE FP-GROWTH ALGORITHM TO DETERMINE CROSS-SELLING
Abstract
KAOCHEM Sinergi Mandiri Cooperative is a cooperative that provides various kinds of basic needs such as basic foodstuffs that can meet the needs of its members. The cooperative transaction data is only stored as a report. Association rules are a method in data mining that functions to identify items that have a value that is likely to appear simultaneously with other items. One implementation of the association method is Market Basket Analysis. The data used are transaction data for November 2019. Data mining is one of the processes or stages of the KDD method. The data mining process is carried out using the FP-Growth algorithm, which is one of the algorithms for calculating the sets that often appear from data. Researchers analyzed transaction data using the Rapid Miner Studio tools. In the data mining process using FP-Growth the researcher determines a minimum support value of 3% and a minimum confidence of 50%. The association process using these values produces 3 strong rules, namely if ades 350 ml, then fried / lontong with a support value of 0.030 and confidence 0.556 and if fried st, then fried / lontong with a support value of 0.048 and confidence 0.639, and if nasi uduk / bacang , then fried / rice cake with a support value of 0.031 and confidence 0.824. The results of the association rules can be applied using one of the marketing techniques, namely cross-selling to increase the sales of the cooperative.
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References
Astrina, I., Arifin, M.Z., & Pujianto, U. (2019, Maret). Penerapan Algoritma FP-Growth Dalam Penentuan Pola Pembelian Konsumen Pada Kain Tenun Medali Mas. Jurnal Matrix, Vol. 9.
Dan, T. T., Sihwi, S. W., & Anggrainingsih, R. (2015, Desember). Implementasi Iterative Dichotomiser 3 Pada Data Kelulusan Mahasiswa S1 Di Universitas Sebelas Maret. JURNAL ITSMART, Vol. 4, 2.
Eska, J. (2016, Maret). Penerapan Data Mining Untuk Prediksi Penjualan Wallpaper Menggunakan Algoritma C4.5. Jurnal Teknologi dan Sistem Informasi, Vol. 2, 9-13.
Ikhwan, A., Nofriansyah, D., & Sriani. (2015, September). Penerapan Data Mining dengan Algoritma FP-Growth untuk Mendukung Strategi Promosi Pendidikan ( Studi Kasus Kampus STMIK Triguna Dharma ). Jurnal Ilmiah SAINTIKOM, Vol. 14.
Kurniawan, S., Gata, W., & Wiyana, H. (2018, Maret). Analisis Algoritma FP-Growth Untuk Rekomendasi Produk Pada Data Retail Penjualan Produk Kosmetik (Studi Kasus : MT Shop Kelapa Gading). SENTIKA, 23-24.
Lestari, Y. D. (2015). Penerapan Data Mining Menggunakan Algoritma FP-Tree Dan FP-Growth Pada Data Transaksi Penjualan Obat. SNASTIKOM.
Melati, D., & Wahyuni, T. S. (2019, Desember). Association Rule Dalam Menentukan Cross-Selling Produk Menggunakan Algoritma FP-Growth. Jurnal Vokasional Teknik Elektro dan Informatika, Vol. 7.
Muzakir, A. (2016, November). Market Basket Analysis (MBA) Pada Situs Web E-Commerce Zakiyah Collection. Jurnal SIMETRIS, Vol. 7(2).
Rerung, R. R. (2018, Juni). Penerapan Data Mining dengan Memanfaatkan Metode Association Rule untuk Promosi Produk. Jurnal Teknologi Rekayasa, Vol. 3(1).
Salam, A., Zeniarja, J., Wicaksono, W., & Kharisma, L. (2018, Juli). Pencarian Pola Asosiasi Untuk Penataan Barang Dengan Menggunakan Perbandingan Algoritma Apriori dan FP-Growth (Study Kasus Distro Epo Store Pemalang). Jurnal Dinamik, Vol. 23.
Saputra, N. E., Tania, K. D., & Heroza, R. I. (2016, Oktober). Penerapan Knowledge Management System (KMS) Menggunakan Teknik Knowledge Data Discovery (KDD) Pada PT PLN (Persero) WS2JB Bayon Kayu Agung. Jurnal Sistem Informasi, Vol. 8(2).
Suntoro, J. (2019). Data Mining Algoritma dan Implementasi dengan Pemograman PHP.
Yulianti, Utami, D. Y., & Hikmah, N. (2019, Maret). Implementasi Data Mining Menentukan Game Android Paling Diminati Dengan Algoritma Apriori. Jurnal Komputer dan Informatika Universitas Bina Sarana Informatika, XXI.
Elvitaria, L., & Havenda, M. (2017, Juli). Memprediksi Tingkat Peminat Ekstrakulikuler Pada Siswa SMK Analisis Kesehatan Abdurrab Menggunakan Algoritma C4.5 (Studi Kasus: SMK Analis Kesehatan Abdurrab). Jurnal Teknologi dan Sistem Informasi Univrab, Vol. 2.
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