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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
Journal of Data Science Methods and Applications Vol. 1 No. 1 (2025)
Publisher : Program Studi Sains Data - Institut Informatika dan Bisnis Darmajaya

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Abstract

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.