Klasterisasi Data Penjualan Menggunakan Algoritma K-Mean Dengan RapidMiner - Panjaitan, Tiodora Priska; Asmaul Dwi Akbar; Sabrina Nur Rahmah; Stefani Cinthia Ernadi; Mochammad Akmal Fatoni; Fatkhul Inayah; Uli Vicilia Sitorus (Program Studi Sains Data - Institut Informatika dan Bisnis Darmajaya, 2025)
ABSTRACTThis research aims to identify the optimal number of clusters in the dataset using the K-Means algorithm and the Elbow method in Rapidminer software. The method used is K-Means to cluster data and the Elbow method to determine the optimal number of clusters. The results of research using the K-Means algorithm have obtained the optimal number of clusters. From the results of processing test data with the number of clusters (k= 2 – 5), it was found that cluster 2 had the highest number of domestic chicken egg sales compared to cluster 1, namely 41 purchases.