This is a preprint journal club review of K-Means Method for Clustering Water Quality Status on The Rivers of Banjarmasin by Tien Zubaidah and Nieke Karnaningroem. The preprint was originally posted on INArxiv on December 21, 2017 (link: https://osf.io/g6wkp/). The article is now in review in the ARPN Journal of Engineering and Applied Sciences (submitted December 20, 2017). Original abstract: The surface river water quality in Banjarmasin city tends to decline constantly as the result of direct and indirect waste disposal from various human activities along the river body. This study aimed to determine the vulnerability points against pollution in the rivers of Banjarmasin using clustering techniques with K-means algorithm. The parameters observed include Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspend Solid (TSS) and Dissolved Oxygen (DO). The data were collected at eight water monitoring stations on various rivers in Banjarmasin city. With the K-means method, four water quality status were clustered. The result showed that 6 stations observed during the period April to October 2016 were categorized into the heavy polluted cluster with major pollution point of sources came from the domestic and industrial activities.