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

Setyorini, Sindhy Genjang; Sari, Ega Kuslia; Elita, Lufty Rahma; Putri, Shinta Ayunda

doi:10.57152/malcom.v1i1.62

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…This method can be used in business processes, including sales. Processed sales data includes information on data relationships with customers so that it will produce customer purchasing patterns, provide recommendations, and promote product needs market basket analysis starting from the accuracy and benefits built in the form of association rules (association rule) and from data patterns linked in the database [24]. Market basket analysis helps to analyze the relationship between all the items included in the transaction to obtain information to benefit the marketing strategy so that the opportunity to increase the sale of items simultaneously can be done [25].…”

Section: Methodsmentioning

confidence: 99%

“…In Majid and Pramudyo's research (2021), it shows some recommendations based on the analysis of association rules include the removal of some parts of the product adjacent to the corresponding part and the use of rarely purchased products for price discount offers [15]. The K-Means algorithm is useful for data clusters, so the FP-Growth algorithm is useful for the association process so that it is able to provide product recommendations to customers more accurately [16]. Research conducted by Syahputra, et.al (2022), explained that clustering is a good choice that can be used to detect similarities in customer buying patterns to provide the right marketing strategy [17].…”

Section: Introductionmentioning

confidence: 99%

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Improving Marketing Strategies Using a Clustering and AR-MBA Methods at Indomaret Kaliurang

Mukarim,

Subagja,

Basuki

et al. 2024

JTI

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Marketing is the main activity carried out by entrepreneurs to maintain the viability of their business, develop the company, and get maximum profit. Companies need to know the right and appropriate marketing strategy so that the products to be sold on the market. Marketing strategy is one of the strategies applied to the retail industry in Indonesia, one of which is Indomaret. The purpose of this research is to increase market competitiveness so that it can survive and develop, and Indomaret in Kaliurang hopes to make a strategy to increase sales by conducting an analysis of consumer segments and product categories so that they can create sales strategies that can increase sales. The method used is clustering to find potential target markets that have similar characteristics and association rules &; Market basket analysis (AR-MBA) is used to find best practices for product marketing. The results of the Cluster Method with Non-Hierarchical Algorithm K-Means are 3 clusters. Based on the analysis conducted, it was found that the results of the AR-MBA method, there could be 6 rules for goods purchased simultaneously. Marketing strategies that can be applied by Indomaret Kaliurang such as promotions can be created by making products that are rarely purchased as bonuses for buying products that are often purchased. In addition, vouchers can be created as a promotional tool to encourage greater consumer purchases. Keywords: AR-MBA, clustering, sales strategy, strategy marketing

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Marketing Strategies Using a Clustering and AR-MBA Methods at Indomaret Kaliurang

Mukarim,

Subagja,

Basuki

et al. 2024

JTI

View full text Add to dashboard Cite

show abstract

“…Paper 2. Berdasarkan dari penelitian [5] (Setyorin et al, 2021) Analisis pola pembelian konsumen di PT. Citra Mustika Pandawa menggunakan algoritma K-Means clustering berhasil mengkategorikan konsumen menjadi 5 kelompok optimal.…”

Section: Hasil Literatur Reviewunclassified

Optimalisasi Stok Barang Melalui Algoritma K-Means Clustering Analisis Untuk Manajemen Persediaan Dalam Konteks Bisnis Modern

Samsudin,

Martanto,

Hayati

2024

jati

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Penelitian ini mengeksplorasi hasil data penjualan untuk di analisis dengan penerapan metode K-Means dalam mengelompokkan transaksi penjualan untuk mengoptimalkan strategi manajemen persediaan barang. Analisis data menjadi kunci utama dalam mengoptimalkan strategi persediaan barang, terutama dengan akses data yang semakin besar. Sistem manajemen persediaan konvensional memiliki kelemahan dalam akurasi dan waktu, sehingga diperlukan pendekatan modern dan efektif. Algoritma K-Means clustering memungkinkan perusahaan untuk mengkategorikan barang berdasarkan pola permintaan dan karakteristik lainnya, sehingga mempermudah penetapan tingkat persediaan ideal untuk setiap kategori barang. Penelitian ini menunjukkan bahwa analisis data dengan algoritma K-Means clustering dapat membantu mengidentifikasi pola permintaan dan karakteristik barang, sehingga membantu perusahaan dalam mengambil keputusan yang terarah dan efektif terkait strategi persediaan barang. Hal ini dapat meminimalisir ketidakpastian dan risiko, serta memastikan pengambilan keputusan persediaan barang secara personal dan efektif.

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

Cited by 2 publications

References 7 publications

Improving Marketing Strategies Using a Clustering and AR-MBA Methods at Indomaret Kaliurang

Improving Marketing Strategies Using a Clustering and AR-MBA Methods at Indomaret Kaliurang

Optimalisasi Stok Barang Melalui Algoritma K-Means Clustering Analisis Untuk Manajemen Persediaan Dalam Konteks Bisnis Modern

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