Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

Mustakim, Mustakim; Herianda, Della Maulina; Ilham, Ahmad; Gs, Achmad Daengs; Laumal, Folkes E.; Kurniasih, Nuning; Iskandar, Akbar; Manulangga, Gloria Christiana; Iswara, Ida Bagus Ary Indra; Rahim, Robbi

doi:10.1088/1742-6596/1114/1/012131

Cited by 32 publications

(12 citation statements)

References 1 publication

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“…Support merupakan ukuran seberapa dominan suatu barang dari keseluruhan transaksi, sedangkan Confidence merupakan hubungan antar dua item berdasarkan suatu kondisi tertentu. Untuk mendapatkan nilai Support, nilai Confidence dan nilai Lift Ratio dapat digunakan Persamaan 1, Persamaan 2, dan Persamaan 3 [15]. (3)…”

Section: Fp-growthunclassified

Analisis Keranjang Pasar Menggunakan Algoritma K-Means dan FP-Growth pada PT. Citra Mustika Pandawa

Setyorini

Sari

Elita

et al. 2021

MALCOM

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PT. Citra Mustika Pandawa adalah perusahaan yang bergerak dibidang furniture, menjual berbagai perabotan dalam rumah tangga seperti, sofa, televisi, rak piring, lemari dan sebagainya. Pengamatan terhadap transaksi data penjualan PT.Citra Mustika Pandawa memberikan pengetahuan dan informasi baru tentang keadaan pasar serta keminatan pelanggan terhadap suatu produk. Metode yang terkenal dibidang bisnis retail adalah Association Rule atau sering dikenal dengan istilah analisa keranjang belanja (market basket analysis). Pendekatan untuk menganalisa keranjang pasar dengan menggunakan aturan asosiasi. penelitian menggunakan metode asosiasi untuk melihat ketertarikan antara barang yang satu dengan yang lainnya dalam data transaksi. Dalam mengolah data transaksi digunakan algoritma FP-Growth dan K-Means. Algoritma K-Means berguna untuk cluster data, sehingga algoritma FP-Growth berguna untuk proses asosiasi.Berdasarkan Association Rule yang telah terbentuk pada tiap cluster diketahui bahwa terdapat 8 items/produk yang sering dibeli oleh pelanggan pada PT. Citra Mustika Pandawa yaitu produk Meja Makan Elite, Rak Piring Asia Jaya, Tv Led 32", Lemari Es 1p, Kitchen Set, Mesin Cuci 2t, dan Lemari Pakaian 1p.

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Section: Fp-growthunclassified

Analisis Keranjang Pasar Menggunakan Algoritma K-Means dan FP-Growth pada PT. Citra Mustika Pandawa

Setyorini

Sari

Elita

et al. 2021

MALCOM

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“…For example in a minimarket, management needs to know the menu most sought after by consumers that can later be used by management to produce information in the form of sales predictions [7]. The management also needs to use appropriate methods to analyze consumer spending patterns in the minimarket so it can increase overall revenue or profit [8].…”

Section: International Journal Information System and Computer Scienc...mentioning

confidence: 99%

The Application of Product Marketing Strategy Using an Association Rule Mining Apriori Method

Ananda

Salamah

2020

IJISCS

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In competition in the business world, it is necessary to find the right strategy that can be used in sales optimization. One strategy used in optimization is to determine the layout of the goods and keep the stock of goods available. Factors that influence the needs of market analysis is the level of frequency of consumers in buying an item. The number of transactions and data recording activities that still use the manual system, increasingly piling up only into expenditure and income records without any further processing. The method used in this analysis is the Apriori Algorithm which is commonly used in transaction data or commonly called Market Basket Analysis. Apriori algorithm is a type of association rule that can find a combination of items using two benchmarks, namely support and confidence. The concept of this association rule is to collect sales transaction data which will then be carried out by the mining process by determining the value of support and the value of trust. The results of this study can facilitate companies to increase sales turnover which refers to the results of processing sales transaction data using the Apriori Algorithm.

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“…Dari kedua algoritma tersebut, terdapat dua hal yang ingin diketahui dari analisis dataset penjualan pada Berkah Mart, yaitu proses rule yang akan dihasilkan dari masing-masing algoritma dan waktu yang dicapai masing-masing algoritma dalam membentuk rule. Hasil yang didapatkan adalah FP-Growth lebih efektif dalam menemukan frequent itemset dan menemukan pola pembelian pelanggan dibanding dengan Apriori [15].…”

Section: Pendahuluanunclassified

Implementation of K-Medoids and FP-Growth Algorithms for Grouping and Product Offering Recommendations

Syukra¹,

Hidayat²,

Fauzi³

2019

IJAIDM

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212 Mart Rambutan Street on Pekanbaru City is a company engaged in retail. Meeting the needs of consumers and making the right decision in determining the sales strategy is a must. One way to find out market conditions is to observe sales transaction data using data mining. The data mining method commonly used to analyze market basket (Market Basket Analysis) is the Association Rule. The Association Rule can provide product recommendations and promotions, so that the marketing strategy is more targeted and the items promoted are the customer's needs. At 212 Mart, the determination of product promotion is obtained from the analysis of sales transaction data reports, which are based on the most sold products and the expiration date. Often the product being promoted does not fit the customer's needs. The purpose of this study is to apply the K-Medoids algorithm for clustering on FP-Growth in producing product recommendation rules on a large number of datasets so that they can provide technical recommendations / new ways to the 212 Mart in determining product promotions. The results obtained are from the experiments the number of clusters 3 to 9 obtained optimal clusters of 3 clusters based on the validity test of the Davies Bouldin Index with a value of 0.678. With a minimum support value of 5% - 9% and a minimum value of 50% confidence, the result is that the Association Rule is found only in cluster 3 with 5 rules.

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Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

Cited by 32 publications

References 1 publication

Analisis Keranjang Pasar Menggunakan Algoritma K-Means dan FP-Growth pada PT. Citra Mustika Pandawa

Analisis Keranjang Pasar Menggunakan Algoritma K-Means dan FP-Growth pada PT. Citra Mustika Pandawa

The Application of Product Marketing Strategy Using an Association Rule Mining Apriori Method

Implementation of K-Medoids and FP-Growth Algorithms for Grouping and Product Offering Recommendations

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