Clustering analysis is a crucial technique in data processing and pattern understanding. In this study, we compare the clustering results using the k-Means algorithm with two different approaches to centroid initialization: random centroids and manual centroids. The dataset consists of three observed variables. The analysis results indicate significant differences in centroid placement and cluster formation between the two approaches. The random centroid approach yields three clusters with centroids located at dif…