Penerapan Data Mining Untuk Analisis Daftar Pembelian Konsumen Dengan Menggunakan Algoritma Apriori Pada Transaksi Penjualan Toko Bangunan MDN

Naldy, Edo Tachi; Andri, Andri

doi:10.47747/jurnalnik.v2i2.525

Cited by 7 publications

(8 citation statements)

References 7 publications

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“…Using the Apriori Algorithm the association rule is applied to pattern that appears most frequently. Association rules in the form of "if … then …" or "if … and… then …" are the results of calculations or they can be called rules (Naldy & Andri, 2021). The association rules that will later be obtained after calculations with the Apriori algorithm will be the right benchmark for marketing in determining promo products according to customer purchasing patterns.…”

Section: Apriori Algorithmmentioning

confidence: 99%

Data Mining Implementation For Product Transaction Patterns Using Apriori Method

Aji

Devi

2023

SinkrOn

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In the era of information technology, entrepreneurs must have a good marketing strategy so that profits do not decrease. The decline in profits is happening at fast food restaurants for example fast food restaurants in Gresik city. This is due to the incompatibility of products sold with customers in Gresik city. Many promos given by marketing didn’t go well, resulting in sales targets not being achieved. To overcome this, good sales data analysis is needed to get products that match with type of customer. Using data mining with the Apriori algorithm is very appropriate for looking customer purchasing patterns. Association rules that are formed with support and confidence as benchmarks provide, a good reference regarding customer purchasing patterns. Research at fast food restaurant in Gresik was conducted by taking transaction data from September 2021 - September 2022 totaling 48,750 transactions with 134 transactions/day. The results of the research are customer buying patterns that are formed in 10 rules with highest percentage. The best rules that can be the best promos is: if customers buy Rice then buy Drinks with 11,19% support and 68,1% confidence. From the results of research that has been done, customer purchasing patterns have been obtained and can be used as a reference by marketing.

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Section: Apriori Algorithmmentioning

confidence: 99%

Data Mining Implementation For Product Transaction Patterns Using Apriori Method

Aji

Devi

2023

SinkrOn

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“…Banyak digunakan dalam berbagai macam program, seperti CLI, desktop, IoT, Game, program untuk hacking, dan lain-lain. Selain itu bahasa Python juga digunakan dalam pengumpulan, pengolahan dan pemakaian data dalam jumlah yang besar yang digunakan untuk menemukan suatu pola atau hubungan dalam dataset yang disebut dengan data mining [2].…”

Section: Pendahuluanunclassified

“…Item best seller dalam satu hari (1) Gambar 12. Item best seller dalam satu hari (2) Sedangkan item best seller untuk setiap harinya ditunjukkan oleh perintah Python pada gambar 13 dan gambar 14 dibawah ini. Terlihat bahwa item yang best seller pada untuk setiap harinya adalah item "( 100rb DAPAT 4 ) Chinos Pendek Pria / Katok Celana Pendek Distro".…”

Section: Tabel 1 Item Paling Tidak Populer Perbulanunclassified

Analisis Pengambilan Keputusan Untuk Korelasi Pembelian Produk Menggunakan Metode Association Rules

Khrisnawati,

Renita

2023

jitter

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Business people are required to be able to keep up with the increasingly dynamic times. Business people must have the right strategy to be able to compete with competitors so that the business they run continues to generate profits. From the existing sales transaction data, it can be used for decision making for business people in developing a good strategy in developing their business. By using data mining with the Association Rules method can be used to analyze existing sales patterns. In this test, the author uses the Apriori Algorithm to analyze the market basket analysis to find out the correlation between product purchases and products that are often purchased by consumers. From the analysis of the a priori algorithm, it produces frequent items that meet the minimum values ??of support and confidence. The result of this test is to provide product recommendations to consumers based on interrelated items and as a reference in product promotion to support decisions in developing good strategies in their business.

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“…Hasil pemrosesan data dari algoritma pincer search dan algoritma FP-Growth kemudian dianalis dan dikomparasi untuk mengetahui hasil komparasi pengaruh perbedaan parameter terhadap waktu pemrosesan data, frequent item set, rule, confidence dan lift ratio pada Toko X. Hasil pemrosesan data dari algoritma pincer search dan algoritma FP-Growth dapat memberikan ilmu pengetahuan serta informasi yang dibutuhkan oleh Toko X [20,21].…”

Section: Ilmu Pengetahuan Dan Informasiunclassified

Komparasi Algoritma Pincer Search dan Algoritma FP-Growth

Wulandari

Suarjaya

Rusjayanthi

2022

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Jumlah pembelian barang setiap harinya berbeda-beda karena itu permasalahan kekurangan stock barang dapat terjadi dan mengakibatkan ketidakpuasan pelanggan dalam berbelanja karena tidak tersedianya produk yang diinginkan. Permasalahan kekurangan stock barang dapat diminimalisir dengan melakukan penelitian mengenai data mining asosiasi menggunakan data transaksi penjualan dari Toko X berdasarkan metode algoritma pincer search dan algoritma FP-Growth. Penelitian ini bertujuan untuk mendapatkan association rule dan jumlah kemunculan frequent item set dalam data transaksi melalui minimum support yang dimanfaatkan untuk mengatasi permasalahan kekurangan stock barang di Toko X serta melakukan komparasi algoritma pincer search dan algoritma FP-Growth terhadap waktu pemrosesan data, frequent item set, rule, confidence dan lift ratio dengan bahasa pemrograman Python. Komparasi algoritma pincer search dan algoritma FP-Growth terhadap frequent item set, rule, confidence dan lift ratio dengan bahasa pemrograman Python memperoleh hasil yang sama, tetapi waktu yang dibutuhkan dalam pemprosesan data berbeda yang disebabkan oleh minimum support, jumlah transaksi dan jumlah item serta alur proses data yang berbeda dari kedua metode.

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Penerapan Data Mining Untuk Analisis Daftar Pembelian Konsumen Dengan Menggunakan Algoritma Apriori Pada Transaksi Penjualan Toko Bangunan MDN

Cited by 7 publications

References 7 publications

Data Mining Implementation For Product Transaction Patterns Using Apriori Method

Data Mining Implementation For Product Transaction Patterns Using Apriori Method

Analisis Pengambilan Keputusan Untuk Korelasi Pembelian Produk Menggunakan Metode Association Rules

Komparasi Algoritma Pincer Search dan Algoritma FP-Growth

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