IMPLEMENTASI METODE SUPPORT VECTOR MECHINE DAN K-MEANS CLUSTERING DENGAN SUPPORT VECTOR MECHINE TEMA KARYA ILMIAH PADA STMIK WIDYA CIPTA DHARMA

Andi Yusika Rangan, M Irwan Ukkas, Siti Qomariah

Abstract


Trends in research topics are useful for building an institutional research roadmap. The classification of themes of scientific works is very much needed to evaluate the vulnerability of research topics of an institution. The implementation of the text mining classification for the theme of scientific works uses the Vector Mechine supprort method and K-means Clustering with Support Vector Mechine (SVM) support. The results of this study are to measure the accuracy of each method used. Support Vector Mechine method at the level of accuracy is 93.33% while the K-means Clustering method with Support Vector Mechine (SVM) accuracy is 99.33%.


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References


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