BibTex Citation Data :
@article{JSINBIS9909, author = {Dwinta Pulukadang and Mustafid Mustafid and Farikhin Farikhin}, title = {Pendekatan Clustering untuk Ekstraksi Pengetahuan pada Pembangunan Sistem Manajemen Pengetahuan}, journal = {Jurnal Sistem Informasi Bisnis}, volume = {5}, number = {2}, year = {2015}, keywords = {Knowledge Management System; Extraction; K-means; Clustering}, abstract = { The importance of knowledge management in any organization encourages the development of a knowledge management system with features that can facilitate knowledge management processes such as storing, organizing, filtering, searching, and most important is the transfer of knowledge. The purpose of this researchis to develop a knowledge management system with a clustering approach for knowledge extraction by using a knowledge of publication writing. This study uses clustering k-means method which is used for cluster knowledge feature where at the same time can help the process of organizing, filtering, browsing and searching knowledge. The results of this research showed that the clustering k-means can be used for knowledge management system with the best value of purity = 0,8454 which is found by using k = 20. Clustering approach in the system again can help the process for knowledge searching based on knowledge cluster. This can be proved by carried out 15 times experiments which result in average level of accuracy (precision) about 89.13% and the average rate of completeness (recall)about 85.73 %. }, issn = {2502-2377}, pages = {79--83} doi = {10.21456/vol5iss2pp79-83}, url = {https://ejournal.undip.ac.id/index.php/jsinbis/article/view/9909} }
Refworks Citation Data :
The importance of knowledge management in any organization encourages the development of a knowledge management system with features that can facilitate knowledge management processes such as storing, organizing, filtering, searching, and most important is the transfer of knowledge. The purpose of this researchis to develop a knowledge management system with a clustering approach for knowledge extraction by using a knowledge of publication writing. This study uses clustering k-means method which is used for cluster knowledge feature where at the same time can help the process of organizing, filtering, browsing and searching knowledge. The results of this research showed that the clustering k-means can be used for knowledge management system with the best value of purity= 0,8454 which is found by using k = 20. Clustering approach in the system again can help the process for knowledge searching based on knowledge cluster. This can be proved by carried out 15 times experiments which result in average level of accuracy (precision) about 89.13% and the average rate of completeness (recall)about 85.73 %.
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