<![CDATA[The Indonesian Architects Association (IAI) of North Sumatra is a professional association that oversees architects in the North Sumatra region. In membership management, there are many inactive members, which risks causing a decline in membership numbers. This condition also has an impact on the development of the architectural profession in North Sumatra. This research aims to build a system that is able to cluster data on members who are at risk of leaving. The method used is the k-means algorithm, which is implemented in a web-based system. With this method, members are grouped into three main clusters based on their level of involvement. The research results show that the first cluster (C1) consists of 178 active members with high seniority (loyal). The second cluster (C2) includes new members who are active but still require further involvement (need engagement), with a total of 196 people. Meanwhile, the third cluster (C3) contains passive members who are at risk of leaving (retention target), with a total of 334 people. With this system, IAI North Sumatra can more easily identify and take strategic steps in maintaining and increasing the number of membership, so that it can support the development of the architectural profession in the area. Keywords: Clustering, K-means, Membership, IAI Sumut, Laravel]]>
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