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Recently, the world is experiencing generating the huge amount of data in different domains. Data mining and Data analytics and are the practices used for analyzing data and extracting hidden knowledge. One of the major data mining methods which is used to analysis of data is data clustering. Data clustering ease the extract information from each cluster separately. There are many algorithms used to perform the clustering. One of the most famous algorithms which is used for clustering for more than half a century is k-means. By many optimization and enhancement, K-means still considers as the most popular clustering algorithm which is still being used in various domains. This research attempts to conduct a Systematic literature Review (SLR) to collect, classify, and analyze the primary studies about the different version of k-means clustering algorithm. This SLR gives a means of finding, appraising, and interpreting existing researches pertinent to the topic. By narrowing down the crucial sections of debate, we are hoping to establish a foundation for upcoming researches.