SciRepID - Analisis Pola Transaksi Belanja Online Menggunakan Algoritma Apriori


Analisis Pola Transaksi Belanja Online Menggunakan Algoritma Apriori

Saturnus: Jurnal Teknologi dan Sistem Informasi
Asosiasi Riset Teknik Elektro dan Informatika Indonesia (ARTEII)

📄 Abstract

This study aims to analyze purchasing patterns in online transactions using the Apriori algorithm to support sales strategy optimization. The research was conducted on transactional data from an online store selling household and daily-use products. The Apriori method was applied to identify associations between items based on minimum support and confidence thresholds. Four experimental scenarios were tested to compare the reliability of generated rules and determine the strongest item relationships. Data preprocessing included item grouping, transaction coding, and elimination of non-frequent items. The results show several strong association rules with lift ratio values above 1, indicating meaningful item relationships. The strongest rule identified was the association between forks and spoons, forming a highly relevant combination for product bundling strategies. The findings demonstrate that the Apriori algorithm can assist online stores in planning stock, designing product bundling, and improving marketing effectiveness. The research contributes practical insights for business decision-making and highlights the significance of data mining in e-commerce environments.

🔖 Keywords

#Apriori Algorithm; Association Rule Mining; Data Mining; Market Basket; Online Transaction Analysis

ℹ️ Informasi Publikasi

Tanggal Publikasi
30 April 2024
Volume / Nomor / Tahun
Volume 2, Nomor 2, Tahun 2024

📝 HOW TO CITE

Dwi Utami; Rosmala Dwi; Nurhidayah Nurhidayah, "Analisis Pola Transaksi Belanja Online Menggunakan Algoritma Apriori," Saturnus: Jurnal Teknologi dan Sistem Informasi, vol. 2, no. 2, Apr. 2024.

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