Implementasi Metode Improved K-Means untuk Mengelompokkan Dokumen Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer - Muhammad Abdurasyid; Indriati Indriati; Rizal Setya Perdana (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Journal of Information Technology and Computer Science Development (J-PTIIK) is a scientific journal in the field of computer that contains scientific writings of research results FILKOM Brawijaya University students that published periodically. J-PTIIK is a journal document that has journal topics that are in the field of information technology and computer science. At this time J-PTIIK is clustered by volume archive and published journal number. To facilitate the identification of journal topics contained in J-PTIIK, J-PTIIK documents can be clustered based on similarity of topics contained in J-PTIIK. J-PTIIK documents clustering is made using improved k-means method. The improved k-means method is the unsupervised clustering techniques with the initial centroid determination obtained by combining the optimization method of distance and density. Document pre-processing and formation of vector space model to perform term weighting is done first before clustering the J-PTIIK documents. Based on the evaluation results, J-PTIIK documents clustering obtained an optimal silhouette coefficient by 0.026574 at k = 19 and Î± = 0.50. Optimal purity test results obtained by 0.738197 at k = 23 and Î± = 0.50. The research result shows that the use of improved k-means method has better silhouette coefficient than k-means method, with average value of silhouette coefficient at improved k-means method by 0.016457654 and k-means method by 0.011820563.