PENERAPAN ORANGE DATA MINING UNTUK PEMBELAJARAN SISTEM MANUFAKTUR DISKRIT PADA KASUS KLASIFIKASI DAN KLASTERISASI GAMBAR HEWAN BERBASIS MACHINE LEARNING - Sukriyah Buwarda; Mutmainnah; Lutfi (Fakultas Teknologi Lingkungan dan Mineral - Universitas Teknologi Sumbawa, 2025)
Politeknik ATI Makassar has introduced technologies such as Artificial Intelligence, Internet of Things, and Big Data Analytics in the Discrete Manufacturing Systems course. This research focuses on the application of Data Science using the Orange Data Mining application for the classification and clustering of animals. The adopted experimental method involves controlling variables by following the CRISP-DM methodology. Evaluation results indicate that the logistic regression model is the best, with an AUC accuracy of 1 and a precision of 0.962. Clustering resulted in two clusters: C1 for cats and C2 for cows, with a silhouette score of 0.145. This research demonstrates the effectiveness of the Orange Data Mining application in teaching discrete manufacturing systems based on machine learning.