<![CDATA[Abstract. This study aims to analyze consumer purchasing patterns during the month of Ramadan at PT. Purnama Mandiri, a wholesale retail store, by applying the Equivalence Class Transformation (ECLAT) algorithm. The Ramadan period is marked by a significant increase in consumer demand, particularly for staple goods, resulting in a substantial growth in the volume and complexity of transaction data. Despite this, such data has not been optimally utilized by the company for strategic decision-making. To address this gap, a Market Basket Analysis (MBA) was conducted using 271,296 sales transaction records collected during Ramadan from 2021 to 2024. The ECLAT algorithm was selected due to its computational efficiency in identifying frequent itemsets within large-scale datasets. By setting a minimum support threshold of 20 transactions (0.000755), frequent itemsets ranging from lengths of 2 to 8 were identified, with the majority concentrated in lengths 2 to 5. From these results, a total of 3,377 association rules were derived, all of which met the criteria for strong rules (confidence ≥ 0.6 and support ≥ 0.000755). One of the strongest rules indicated that purchases of DRIGEN KOSONG are consistently associated with MINYAK SAYUR CURAH, exhibiting a confidence level of 100% and a lift of 10.17. These insights offer valuable implications for business strategies, including product placement, bundling promotions, and inventory management during Ramadan. Abstrak. Penelitian ini bertujuan menganalisis pola pembelian konsumen selama bulan Ramadhan di Toko Grosir PT. Purnama Mandiri menggunakan algoritma Equivalence Class Transformation (ECLAT). Bulan Ramadhan mengalami lonjakan konsumsi yang signifikan, terutama bahan pokok, yang menyebabkan meningkatnya jumlah dan kompleksitas data transaksi. Namun, data tersebut belum dimanfaatkan secara optimal oleh PT. Purnama Mandiri sebagai dasar pengambilan keputusan strategis. Oleh karena itu, dilakukan Market Basket Analysis (MBA) terhadap 271.296 data transaksi penjualan selama bulan Ramadhan tahun 2021-2024. Algoritma ECLAT dipilih karena efisien dalam menemukan frequent itemsets pada dataset besar. Dengan minimum support 20 transaksi (0,000755), ditemukan kombinasi itemset dengan panjang 2 hingga 8, terbanyak pada panjang 2–5. Dari hasil tersebut terbentuk 3.377 aturan asosiasi yang seluruhnya memenuhi kriteria strong rule (confidence ≥ 0,6 dan support ≥ 0,000755). Salah satu aturan terkuat menunjukkan bahwa pembelian DRIGEN KOSONG berasosiasi kuat dengan pembelian MINYAK SAYUR CURAH, dengan confidence 100% dan lift 10,17. Temuan ini dapat dimanfaatkan untuk strategi bisnis seperti penataan produk, promosi bundling, dan pengelolaan stok yang lebih efektif selama bulan Ramadhan.]]>
