Market Basket Analysis To Identify Stock Handling Patterns & Item Arrangement Patterns Using Apriori Algorithms

Tresna Yudha Prawira(1*), Sunardi Sunardi(2), Abdul Fadlil(3),

(1) Magister Teknologi Informatika Universitas Ahmad Dahlan
(2) Magister Teknologi Informatika Universitas Ahmad Dahlan
(3) Magister Teknologi Informatika Universitas Ahmad Dahlan
(*) Corresponding Author
DOI: https://doi.org/10.23917/khif.v6i1.8628

Abstract

The process of managing the pattern of handling stock of goods and the pattern of arranging goods on store shelves requires an identification process by utilizing data from sales transaction results. Market basket analysis of sales transaction data using Apriori Algorithm stages produces an information in the form of association rules with a minimum support value of 50% and a minimum confidence of 60%. It can be a reference in the arrangement of items on store shelves by referring to a combination of items that are often bought by consumers simultaneously. In addition, the stock inventory pattern can take advantage of the results of determining the high frequency value in the combination pattern 1 - itemset C1 with a minimum support value of 50% which is compared with the initial inventory.

Keywords

apriori algorithm; arrangement of goods; stock

Full Text:

PDF

References

A. Junaidi, "Implementasi Algoritma Apriori dan FP-Growth untuk Menentukan Persediaan Barang," vol. 8, no. 1, pp. 61-67, Maret 2019.X[2] H. Jiawei dan K. Micheline, Data Mining : Concept and Techniques Second Edition, Morgan Kaufman Publishers, 2006.

D. T. Larose, Discovering knowledge in data : an introduction data mining, Jhon Wiley & Sons Inc, 2005.

Suprayogi, dan A. Karima, "Implemetasi Algoritma Apriori dengan Market Basket Analysis untuk Pengaturan Tata Letak Produk," vol. 9, no. 2, pp. 169-179, Juli 2019.

Maharani, N. A. Hasibuan, dan N. Silalahi, "Implementasi Data Mining untuk Pengaturan Layout Minimarket dengan Menerapkan Association Rule," vol. 4, no. 4, pp. 6-11, Agustus 2017.

A. K. Prasidya, dan C. Fibriani "Analisis Kaidah Asosiasi Antar Item Dalam Transaksi Pembelian Menggunakan Data Mining Dengan Algoritma Apriori (Studi Kasus Gun Bandungan Jawa Tengah," vol. 14, no. 2, pp. 173-184, Juli 2017.

M. Sholik, dan A. Salam, "Implementasi Algoritma Apriori untuk Mencari Asosiasi BArang yang Dijual di E-commerce OrderMAs," vol. 17, no. 2, pp. 158-170, Mei 2018.

G. Abdurrahman, "Analisis Aturan Asosiasi Data Transaksi Supermarket Menggunakan Algoritma Apriori," vol. 2, no.2, pp. 100-111, Agustus 2017.

R. Yanto, dan R. Khorirah, "Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat," vol. 2, no. 2, pp. 102-113, April 2015.

S. Wahyuni, Suherman, dan L. P. Harahap, "Implementasi Data Mining dalam Memprediksi Stok Barang Menggunakan Algoritma Apriori," vol. 5, no.2, pp. 67-71, Juli 2018.

E. D. Sikumbang, "Penerapan Data Mining Penjualan Sepatu Menggunakan Metode Algoritma Apriori," vol. 4, no. 1, pp. 156-161, Februari 2018.

Y. Suardi, B. F. Ahmad, M. Ita, dan W. Bambang, "Penerapan Data Mining Pengaturan Pola Tata Letak Barang pada Berkah Swalayan untuk Strategi Penjualan Menggunakan Algoritma Apriori," vol. 2, no. 1, pp. 69-75, Januari 2019.

A. Cep, H. Nila, dan W. Wiwiek, "Implementasi Data Mining Penjualan Kosmetik Pada Toko Zahrani Menggunakan Algoritma Apriori," vol. 11, no. 2, pp. 1-7, Mei 2019.

B. A. Pilipus, R. J. Ekik, dan L. Yonata, "Prediksi Pola Pembelian Customer dengan Market Basket Analysis pada PT. Capella Medan," vol. 2, no. 2, pp. 59-66, Maret 2019.

Y. S. Haysrif, Rismayani, dan L. S Novita, "Data Mining Menggunakan Algoritma Apriori untuk Analisis Penjualan," vol. 6, no. 1, pp. 217-226, Agustus 2019.

Article Metrics

Abstract view(s): 1171 time(s)
PDF: 1209 time(s)

Refbacks

  • There are currently no refbacks.