Journal of Data Science Methods and Applications
Vol. 1 No. 1 (2025)

Klasterisasi Data Penjualan Menggunakan Algoritma K-Mean Dengan RapidMiner

Panjaitan, Tiodora Priska (Unknown)
Asmaul Dwi Akbar (Unknown)
Sabrina Nur Rahmah (Unknown)
Stefani Cinthia Ernadi (Unknown)
Mochammad Akmal Fatoni (Unknown)
Fatkhul Inayah (Unknown)
Uli Vicilia Sitorus (Unknown)

Article Info

Publish Date
26 Apr 2025

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.

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Journal Info
Journal of Data Science Methods and Applications
Website

Abbrev

JoDMApps

Publisher

Institut Informatika dan Bisnis Darmajaya

Subject

Biochemistry, Genetics & Molecular Biology Computer Science & IT Engineering Library & Information Science

Description

Theoretical Foundations: Architecture, Management and Process for Data Science Artificial Intelligence Classification and Clustering Data Pre-Processing, Sampling and Reduction Deep Learning Educational Data Mining Forecasting High Performance Computing for Data Analytics Learning Classifiers ...