Analisis Pola Pembelian Pada Platform E-Commerce Menggunakan Algoritma Apriori Untuk Mengidentifikasi Tren Produk 2025 - Margan Rizkiano Ritonga; Maysya Faiftin Siringoringo; Sardo Pardingotan Sipayung (GLOBAL SCIENTS PUBLISHER, 2026)
The growth of E-commerce platforms had generated large volumes of transaction data that could be used to analyze consumer behavior and product trends. This study aimed to analyze purchasing patterns using the Apriori algorithm to identify product trends for 2025. The method involved data collection, data cleaning, transformation into itemsets, and extraction of association rules based on support, confidence, and lift values. The results indicated that several product combinations were frequently purchased together and showed strong relationships, reflecting consumer preferences. Products in the electronics, fashion, and household categories demonstrated increasing demand and were likely to become trends in 2025. These findings could support e-commerce managers in developing effective marketing strategies, optimizing inventory management, and improving data-driven product recommendation systems to enhance competitiveness and customer satisfaction.