📅 14 July 2023
DOI: 10.51903/elkom.v16i1.999
INDONESIA Pola Asosiasi Untuk Rekomendasi Penataan Display Barang Menggunakan Algoritma Apriori dan FP-Growth (Study Kasus Gamefantasia Ada Swalayan Pati)
Jurnal Elektronika dan Komputer
Universitas Sains dan Teknologi Komputer
📄 Abstract
This data mining association processes 1224 Gamefantasia ticket redemption transaction data. The goal is to find a pattern of association between goods as a recommendation for structuring the display of goods at the cashier counter and increasing ticket exchange transactions. Modeling uses a comparison of two algorithms, namely the Apriori algorithm and FP-Growth. The data analysis method with the CRISMP-DM method is then processed by RStudio software. The results of the study with the same parameters support 0.02 and confidence 0.1 FP-Growth algorithm formed 53 rules, the strength of the association rule 6.2%, the accuracy was1245%. Whereas the Apriori algorithm forms only 12 rules, the strength of the association rules is 2.1% and the accuracy is 7.8%. Thus, it can be concluded that the use of the FP-Growth algorithm has better results than the Apriori algorithm because it has the highest accuracy in finding transaction patterns.
🔖 Keywords
#Apriori Algorithm
#FP-Growth Algoritm
#CRISP-DM Method
ℹ️ Informasi Publikasi
Tanggal Publikasi
14 July 2023
Volume / Nomor / Tahun
Volume 16, Nomor 1, Tahun 2023
📝 HOW TO CITE
MURDIANTO, BEKRI; MURDIANTO, BEKRI; Arief Jananto, "INDONESIA Pola Asosiasi Untuk Rekomendasi Penataan Display Barang Menggunakan Algoritma Apriori dan FP-Growth (Study Kasus Gamefantasia Ada Swalayan Pati)," Jurnal Elektronika dan Komputer, vol. 16, no. 1, Jul. 2023.
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