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Suhada Suhada, A M H Pardede


Data processing documents also become an important issue at this time. Along with the increasing amount of data collected and stored in a database increases drastically. This data can come from a variety of sources such as financial applications, Enterprise Resource Management (ERM), Customer Relationship Management (CRM), and others. These data if can be used to support the decision-making process. This paper shows the result of clustering data derived from students' final assignment AMIK Tunas Bangsa Pematangsiantar using Support Vector Clustering method but it also displayed the data using the software RapidMiner clustering results with pengklasteringan time for 11:21 minutes with a gain that took the title in 1708 and classified database 311 who took the title of the classified web programming.

Keywords: Clustering Algorithm, Support Vector Clustering, RapidMiner

Keywords: Clustering Algorithm, Support Vector Clustering, RapidMiner

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