Penerapan Data Analitik untuk Menentukan Pola Asosiasi Penjualan dengan Algoritma Apriori - Bong, Adryanto Wisesa; Mardiani, Mardiani (MDP Student Conference, 2025)
Company XYZ is a distributor of motorbike spare parts that faces challenges in utilizing transaction data to improve marketing strategies. This research aims to apply the Apriori algorithm in analyzing transaction data to find product purchasing patterns that often occur simultaneously. The Knowledge Discovery in Database (KDD) method is used for the analysis process, starting from understanding data, data transformation, to pattern discovery and evaluation. The interactive dashboard was designed using Python to present analysis results in an easy-to-understand visual form. The research results show that the application of the Apriori algorithm can identify significant association patterns between products, help companies improve sales strategies and optimize stock management. Thus, this research contributes to data-based decision making to support company business growth.