Comparison Of Market Basket Analysis To Determine Consumer Purchasing Patterns Using Fp-Growth And Apriori Algorithm

Aldino, Ahmad Ari; Pratiwi, Evi Dwi; Setiawansyah,; Sintaro, Sanriomi; Putra, Ade Dwi

doi:10.1109/icomitee53461.2021.9650317

Cited by 34 publications

(16 citation statements)

References 13 publications

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“…Association Rules are a very helpful tool in the business world as they can be used to determine which goods and services are most likely to be purchased in conjunction with each other. To perform an association rule search, it is necessary to have a variable measure of confidence, which the user is tasked with defining such measures are the support and confidence values [17]- [22].…”

Section: Association Rulementioning

confidence: 99%

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

Rahayu

2023

J. Appl. Data Sci.

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The development and competition that exists in the business world today leads every manager or company to be more dexterous in making marketing strategies to increase sales. Various things are done to keep up with existing market competition, such as analyzing customer purchase transaction data to serve as a policy determination and decision-making system in making marketing strategies. In determining marketing strategies, it can be done by taking transaction data to see existing purchase or transaction patterns. Market Basket Analysis is part of a data mining method that uses the FP-Growth algorithm technique to find out associated products. This research uses data taken from sales transaction data archives as much as 150 sales transaction data and 26 product data. In this study, it is determined that the minimum support value is 50% and the minimum confidence is ≥ 0.75 From the test results, 9 products have superior support values and meet the minimum value. From the test results, a rule with a confidence value of 0.870 was obtained: D → W (if consumers buy Wardah Lightening Gentle Wash, then buy Azarine Sunscreen SPF50), and 0.808: A → E → O (if consumers buy Emina Face Wash, then buy Azarine Night Moisturizer and Himalaya Neem Mask).

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Section: Association Rulementioning

confidence: 99%

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

Rahayu

2023

J. Appl. Data Sci.

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“…First, we criticize this study for not using the FP-Growth algorithm during the learning phase. This is because most studies prove its effectiveness compared to previous algorithms [14] [15]. Second, the study used a small fraction of the dataset of the seventh participant, which negatively impacted the value of the published results.…”

Section: Related Workmentioning

confidence: 99%

A Context-Aware Personalized Recommendation System for Smart Home Automation based on Unsupervised and Supervised Learning Algorithms

Dilekh

Benharzallah

Mokeddem

et al. 2023

Preprint

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Current home automation systems allow remote monitoring and control of smart home devices. However, the problem caused by autonomous or self-controlled home automation is that predicting inhabitant behaviour and desires in every situation with 100% accuracy is unrealistic, at least for now. Therefore, the actual implementation of autonomous home automation may prove daunting and rigid for some users. Additionally, inhabitants want to be in control and want control over when and how things are done, this is due to their anxiety about losing control in favor of autonomous home automation. A personalized recommendation system for smart home residents with a certain degree of confidence is therefore ideal. This paper proposes a methodology to build a context-aware personalised recommender system for smart home automation. We suggest a predictive model for useful automation services of relevant smart home devices that smart home residents’ may wish to perform, by capturing the user’s current state and contextual preferences at that time. This is done by applying, in the first stage, an unsupervised algorithm to extract rules of behavior based on the resident’s previous interactions and passively captured in their daily lives by IoT-enabled sensors, and then, in the second stage, applying a supervised algorithm to recommend automation services in future instances when the actual behaviour of the user and context matches the established rules. Evaluations of smart home datasets show that the system produces correct recommendations with an average accuracy of 86.99%, a recall of 76.06%, and a precision of 82.67%.

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“…Hal ini dapat di lihat dengan banyaknya pertumbuhan industri besar maupun industri kecil [3]. karena hal tersebut peranan dari media publikasi seperti halnya website sangat di butuhkan dalam rangka mempromosikan produk atau barang, terlebih untuk industri kecil yang berpotensi untuk bersaing dengan industri lainnya [4]. Selain di gunakan untuk media promosi internet juga di gunakan sebagai proses pembelian dan penjualan produk, jasa dan informasi yang dapat di publikasikan secara on-line dengan menggunakan website [5], dengan menggunakan peranan dari web produk, jasa dan informasi yang kita punya dapat di lihat oleh semua kalangan dari belahan dunia yang berbeda [6].…”

Section: Pendahuluanunclassified

Aplikasi Penjualan Baju Berbasis Web (E-Commerce) dengan Formulasi Penyusunan Kode

et al. 2022

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Perdagangan elektronik atau lebih di kenal sebagai E-commerce adalah konsep yang dapat di gambarkan untuk menggambarkan proses penjualan dan pembelian jasa melalui internet dan dapat menggunakan media website. Sistem informasi penyebaran produk dan jasa dapat di publikasikan dengan luas tanpa perlu mengeluarkan biaya yang sangat besar, hal tersebut sangatlah berbanding terbalik pada usaha penjualan baju yang ada pada Cluthar Project. Pada Cluthar Project dimana sistem penjualan di lakukan apabila ada pembeli datang ke toko dan sistem penyampaian informasi produk yang di sediakan masih dalam cakupan yang kecil dimana penyebaran informasi masih menggunakan pamplet hal tersebut sangatlah tidak efisien dan hal tersebut mempengaruhi penjualan pada Cluthar Project. Oleh karena itu penulis melakukan penelitian secara langsung pada Cluthar Project, dengan metode OOP dan perancangan menggunakan UML untuk meneliti permasalahan pada Cluthar Project. Dalam permasalahan yang ada di Cluthar Project dimana penjualan dan pemasaran barang di lakukan masih tidak efisien, oleh karena itu penulis melakukan perancangan aplikasi penjualan berbasis web (e-commerce) pada Cluthar Project menggunakan aplikasi berbasis web dengan bahasa pemograman PHP dan basis data MySQL dimana aplikasi tersebut dapat di gunakan untuk mempermudah penjualan, pembelian dan penyebaran informasi-informasi produk terbaru karena menggunakan formulasi penyusunan kode barang, hal tersebut dilakukan agar Pembeli melakukan transaksi pembelian tanpa harus datang ke toko, dapat melihat produk terbaru Cluthar Project dan Aplikasi tesebut dapat meningkatkan penjualan pada Cluthar Project

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Comparison Of Market Basket Analysis To Determine Consumer Purchasing Patterns Using Fp-Growth And Apriori Algorithm

Cited by 34 publications

References 13 publications

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

A Context-Aware Personalized Recommendation System for Smart Home Automation based on Unsupervised and Supervised Learning Algorithms

Aplikasi Penjualan Baju Berbasis Web (E-Commerce) dengan Formulasi Penyusunan Kode

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