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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY MDP Student Conference
Nevile, Steven
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering

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Journal : MDP Student Conference

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Penerapan Data Mining Untuk Rekomendasi Paket Produk Menggunakan Algoritma Apriori dan Algoritma FP-Growth Nevile, Steven; Yulistia, Yulistia
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.10933

Abstract

This research utilizes data mining with the Apriori and FP-Growth algorithms to generate product package recommendations for Planty Burger based on sales transaction data. Through data mining-based analysis, Planty Burger can identify consumer preference patterns and provide more relevant recommendations. The research methodology includes Data Collection, Data Preprocessing, Algorithm Implementation, Analysis and Result Evaluation, and Software Development. The use of both algorithms allows for a comparison of results to ensure the validity of the identified patterns. Based on the analysis, it can be concluded that if a customer purchases Matcha Greentea, there is a high probability (75% confidence) that they will also purchase a BBQ Steak Burger. The analysis results are expected to enhance customer satisfaction and sales by providing appropriate product package recommendations.
Co-Authors Andika, Irfan Farisi, Ahmad Satya, Richard Steven Lim, Steven Yulistia, Yulistia