Advances in information technology are currently the most effective media for finding and disseminating the information needed in today's life. High information is sometimes not matched by the presentation of adequate information, often this information still needs to be extracted or reprocessed. As an intuition engaged in the field of communication and informatics, the Bogor Regency Communication and Informatics Service provides internet services for its employees. Therefore, the quality of the internet network at Diskominfo must always be in prime condition to support the process of its activities. For intuition, knowing and understanding the behavior of internet service users can be a reference for optimizing in the future. Access patterns are a part of user behavior when accessing internet services. Due to the large amount of data that must be processed, a method is needed to process such large data. In this thesis the author uses the K-Means Clustering method to process data. The results of this study indicate that the K-Means clustering algorithm is able to group types of network user services effectively based on the pattern of computer network usage in the Bogor District Communication and Informatics Office
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