the k-means clustering is a unsupervised learning algorithm which is used to perform cluster analysis or grouping of the data. that is also known as categorization algorithm. the clustering algorithms directly employed over data. the algorithm results the k clusters according to application needs. in this work the k-means clustering algorithm is implemented using WEKA jar. the performance of the algorithm is also measured in terms of accuracy, error rate and time consumption. we can use data set in CSV format and we obtain some of the training data samples form UCI repository.