Main Content
Lembaga Kita Journal Portal
Open Access Computer & Communication Science

Penerapan Metode Market Basket Analysis (MBA) dengan Algoritma Apriori Untuk Menganalisis Pembelian Jajanan Khas Lebaran Pada Warung Sembako di Toko Win

  • Wahyu Nugraheni1*
  • Adi Nugroho2
1,2 Satya Wacana Christian University image/svg+xml
* Corresponding Author: Wahyu Nugraheni

Abstract


Market Basket Analysis is determining marketing strategies to meet products that will be purchased simultaneously by consumers who are frequently used and most useful for marketing environments that apply an "if-then" pattern. The aim is to identify which can be used as a reference in determining the layout of items with a combination of items that are frequently purchased and interconnected in order to increase sales with the right marketing strategy Research was conducted at the Win Store where so far there is a lot of data accumulate that is only used as archives or bookkeeping, so as to help increase sales by making sales transaction data as new information by processing it using the Basket Analysis Method and the Apriori Algorithm using Rapid Miner Studio.Here using 7 data atribut namely Astor, Kastangel, Spinach Chips, Seblak Chips, Intestine Chips, Monde, and Nastar, and 50 data records, with a minimum support limit = 0.4 and minimum confidence = 0.6 which produces 14 rules. And the highest item set combination pattern obtained in this study is [NASTAR, MONDE] => [KASTANGEL] yielding a confidence of 85.7%.

Keywords

Apriori Algorithm Association Rules Market Basket Analysis Rapid Miner

How to Cite

Citation Format
Nugraheni, W., & Nugroho, A. (2023). Penerapan Metode Market Basket Analysis (MBA) dengan Algoritma Apriori Untuk Menganalisis Pembelian Jajanan Khas Lebaran Pada Warung Sembako di Toko Win. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 7(4), 639-641. https://doi.org/10.35870/jtik.v7i4.1083

References

15 References
  • Gunadi, G., & Sensuse, D. I. 2012. 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.
  • Alfiyan, A. R., Kahfi, A. H., Kusumayudha, M. R., & Rezki, M. 2019. Analisis Market Basket Dengan Algoritma Apriori Pada Transaksi Penjualan Di Freshfood. IJCIT (Indonesian Journal on Computer and Information Technology), 4(1), 1–8.
  • Gemala, M., Arifin, M. and Aliffianto, A.Y., 2013. Penerapan Metode Market Basket Analysis Pada Situs Web E-Commerce (Studi Kasus: Dhian Handicraft Indonesia) (Doctoral dissertation, Universitas Dinamika).
  • Setiawan, A. and Mulyanti, R., 2020. Market Basket Analysis dengan Algoritma Apriori pada Ecommerce Toko Busana Muslim Trendy (Market Basket Analysis with Apriori Algorithms in Ecommerce Trendy Muslim Clothing Stores). JUITA: Jurnal Informatika, 8(1), pp.11-18. DOI: http://dx.doi.org/10.30595/juita.v8i1.4550.
  • Halim, S.H.A., 2021. Identifikasi Pola Penjualan Kategori Barang dalam Menjaga Stabilitas Stok Barang Menggunakan Algoritma Fp-Growth. Jurnal Informatika Ekonomi Bisnis, pp.155-160. DOI: https://doi.org/10.37034/infeb.v3i4.94
  • Umar, E., Manongga, D., & Iriani, A. 2022. Market Basket Analysis Menggunakan Association Rule dan Algoritma Apriori Pada Produk Penjualan Mitra Swalayan Salatiga. Jurnal Media Informatika Budidarma, 6(3), 1367. DOI: https://doi.org/10.30865/mib.v6i3.4217.
  • Dzulkarnaen, R., 2020. Perancangan Aplikasi Data Mining Market Basket Analysis Pada Apotek Permata dengan Metode Hybrid-Dimension Association Rules. Journal of Information Technology, 2(2), pp.67-72. DOI: https://doi.org/10.47292/joint.v2i2.35.
  • Rerung, R. R. 2018. Penerapan Data Mining dengan Memanfaatkan Metode Association Rule untuk Promosi Produk. Jurnal Teknologi Rekayasa, 3(1), 89–98. DOI: https://doi.org/10.31544/jtera.v3.i1.2018.89-98.
  • Romadhon, M. S., & Kodar, A. 2020. Implementasi Metode Market Basket Analysis (Mba) Menggunakan Algoritma Apriori Dalam Transaksi Penjualan (Studi Kasus: Kafe Ruang Temu).
  • Sharif, A. 2019. Data Mining Untuk Memprediksi Itemset Promosi Penjualan Barang Menggunakan Metode Market Basket Analysis (Mba) (Studi Kasus: Toko Sentra Ponsel). Jurnal Mantik Penusa, 3(Desember), 117–123.
  • Hendajani, F., & Anita. 2019. Perbandingan Penggunaan Aplikasi Rapid Miner Dengan Weka Untuk Penerapan Metode K-Means Clustering Pada Pengelompokan Penderita Demensia.
  • Han, J., Kamber, M., & Pei, J. 2012. Data Mining: Concepts and Techniques.
  • Masnur, A., 2015. Analisa Data Mining Menggunakan Market Basket Analysis untuk Mengetahui Pola Beli Konsumen. SATIN-Sains Dan Teknologi Informasi, 1(2), pp.32-40.
  • Rhomadhona, H., et al. 2021. Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan, 10(02), 65–73.
  • Qoni’ah, I., & Priandika, A. T. 2020. Analisis Market Basket Untuk Menentukan Asossiasi Rule Dengan Algoritma Apriori (Studi Kasus: Tb. Menara). Jurnal Teknologi dan Sistem Informasi, 1(2), 26–33. [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI.

Author Biographies

Wahyu Nugraheni, Satya Wacana Christian University

Program Studi Teknik Informatika, Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Kota Salatiga, Provinsi Jawa Tengah, Indonesia

Adi Nugroho, Satya Wacana Christian University

Program Studi Teknik Informatika, Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Kota Salatiga, Provinsi Jawa Tengah, Indonesia

License

Copyright (c) 2023 Wahyu Nugraheni, Adi Nugroho

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

This is an open-access journal distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, reproduction, and adaptation in any medium (even commercially), provided appropriate credit is given to the original author(s), a link to the license is provided, and any changes made are indicated. Authors retain copyright without restrictions and grant the journal the right of first publication as well as non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

Downloads

OJS UsageStats Plugin
Download data is not yet available.

Most read articles by the same author(s)

Contrimetric

Recommended Articles