ANALISIS DATA PENJUALAN DEALER MOTOR BENELLI BRANCH PEKALONGAN MENGGUNAKAN METODE DECISION TREE - Ferryan Nur Setyawan; Magdalena Ariance Ineke Pakereng (Politeknik Bisnis Indonesia, 2024)
This research aims to enhance motorcycle sales strategies at PT. Benelli Anugerah Motor Pusaka Branch Pekalongan by utilizing data mining techniques, specifically the ID3 decision tree algorithm, to analyze and classify sales data. Given the increasing prevalence of motorcycles in Indonesia, this study focuses on identifying key factors that influence motorcycle purchases to optimize inventory and boost sales. Data from December 2022 to January 2024, encompassing 82 sales records, were processed using RapidMiner. The ID3 algorithm calculated entropy and information gain to classify motorcycles based on type, color, price, and transaction method (cash or credit). The results indicate that motorcycle type is the most significant factor, followed by color, price, and payment method. The model achieved an accuracy of 76.47%, with a precision of 87.50% and recall of 70.00%. This classification provides valuable insights for the dealer to manage inventory efficiently and anticipate customer preferences, thereby enhancing sales performance. The findings demonstrate the practical application of decision tree algorithms in transforming extensive data into actionable business intelligence.