Klasifikasi Persediaan Obat Menggunakan Algoritma Deci-sion Tree di Puskesmas Brebes - Ermawati, Erli; Bambang Irawan; Nur Ariesanto Ramdhan (Lembaga Pengembangan Kinerja Dosen, 2025)
This study aims to classify drug inventory at Puskesmas Brebes to address issues of overstock and stockout, which impact healthcare services. The C4.5 Decision Tree algorithm was used with three classification categories: High, Medium, and Low. The dataset contains 1,586 records with attributes such as drug name, unit, quantity, disease type, and inventory class. The model was trained using RapidMiner with 70% training data and 30% testing data, achieving 100% accuracy. It was implemented in a web-based application that automatically classifies data and visualizes results through charts. The findings demonstrate that the C4.5 algorithm is effective in supporting drug inventory management.