Penerapan Algoritma K-Means Berbasis RapidMiner pada Analisis Distribusi Air Bersih di Indonesia - Agustina, Melisa; Anisa, Nor (Majalah Ilmiah METHODA, 2025)
This study aims to analyze the distribution pattern of clean water, identify the largest production capacity, and examine the distribution of the highest number of customers of clean water companies in several provinces in Indonesia using the K-Means algorithm. The data used includes distribution of delivery, potential production capacity (liters per second), and the number of customers of clean water companies across various provinces in Indonesia. The K-Means method is applied to cluster provinces based on the similarity of distribution patterns, production capacity, and customer numbers. The analysis results reveal significant clustering, where certain provinces have high clean water production capacity and a large number of customers, with the volume of water distributed matching the production capacity. These findings indicate a good balance between production capacity, the number of customers, and the volume of water distribution. This study focuses on the analysis of clean water distribution, the largest production capacity, and customers of clean water companies in various provinces in Indonesia. The insights gained can assist companies in designing more efficient distribution strategies to optimally meet customers needs across different regions. This contributes to the sustainable and equitable management of clean water resources.