Model Data Mining untuk Penetapan Plafon Kredit dengan Algoritma C4.5 - Frans Mikael Sinaga; Jefri Junifer Pangaribuan; Aulia Rizky Muhammad Hendrik Noor Asegaff; Wenripin Chandra; Riche Riche (Yayasan Literasi Sains Indonesia, 2025)
Manual credit limit determination in distributor companies is often subjective and inconsistent, increasing the risk of bad debts. This research aims to design an objective data mining model to support customer credit limit decisions at CV. XYZ. The method used is the Decision Tree with the C4.5 algorithm, applied to 66 historical records of customer payment data. Data analysis was performed by calculating Entropy and Information Gain values to build the decision tree, which was then validated using RapidMiner Studio software. The research successfully built a valid and consistent classification model. The