DOI: https://doi.org/10.21456/vol5iss2pp79-83

Pendekatan Clustering untuk Ekstraksi Pengetahuan pada Pembangunan Sistem Manajemen Pengetahuan

*Dwinta Rahmallah Pulukadang  -  Magister Sistem Informasi Universitas Diponegoro, Indonesia
Mustafid Mustafid  -  Jurusan Statistik, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Farikhin Farikhin  -  Jurusan Matematika, Fakultas Sains dan Matematika Universitas Diponegoro, Indonesia

Citation Format:
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 %.

 

 

Fulltext View|Download
Keywords: Knowledge Management System; Extraction; K-means; Clustering

Article Metrics:

Article Info
Section: Research Articles
Language : EN
Recent articles
Pendekatan Clustering untuk Ekstraksi Pengetahuan pada Pembangunan Sistem Manajemen Pengetahuan Sistem Informasi Untuk Supply Chain Berkelanjutan Berbasis Pengetahuan Sistem Gesture Accelerometer dengan Metode Fast Dynamic Time Warping (FastDTW) Front Matter JSINBIS Volume 5 Nomor 2 Tahun 2015 Back Matter JSINBIS Volume 5 Nomor 2 Tahun 2015 More recent articles
Most cited articles
Studi Pengamanan Login Pada Sistem Informasi Akademik Menggunakan Otentifikasi One Time Password Berbasisis SMS dengan Hash MD5 Penerapan Model Promosi Berbasis Web Captive Portal Hotspot dengan Manajemen Terpusat Sistem Informasi Geografis Berbasis Web untuk Pemetaan Sebaran Alumni Menggunakan Metode K-Means Sistem Informasi Pengukuran Kinerja Pada Perkebunan Kelapa Sawit Dengan Menggunakan Metode Balanced Scorecard Kombinasi Balanced Scorecard dan Objective Matrix Untuk Penilaian Kinerja Perguruan Tinggi More cited articles
  1. Babu, K.V.S.N.J., Harshavardhan, T. and Kumar, A.J.S., 2012. The Role of information retrieval in knowledge management. International Journal of Social Science & Interdisciplinary Research 1(10), 212-226
  2. Baets, W., 2005. Knowledge Management and Management Learning. Springer, USA
  3. Boahene, M., Ditsa, G., 2003. Conceptual Confusions in Knowledge Management and Knowledge Management Systems: Clarifications for Better KMS Development. IRM PRESS, Australia
  4. Butler, T., Feller, J., Pope, A., Emerson B., Murphy C., 2008. Designing a core IT artefact for knowledge management systems using participatory action research in a government and a non-government organisation, Journal of Strategic Information Systems 17 (4), 249 – 267
  5. Can, F., E. A., 1990. Concepts and effectiveness of the cover-coefficient-based clustering methodology for text databases. ACM Transactions on Database Systems 15 (4), 483 - 517
  6. Darawaty, I.S., Syarah, S., Nugroho, A.H., Ayuningtyas, F., Istianto, Y., Prasetyo, B., Uliniansyah, M., Gunawan, M., Ani, D., Jarin, A., Handoko, D., 2010. Intelligent Searching Using Association Analysis for law Documents of Indonesian Government. Second International Conference on Advances in Computing, Control, and Telecommunication Technologies, Jakarta, December 2-3, 122-124
  7. Kumar, V., Steinbach, M., Tan, P., 2004. Introduction to Data Mining. Addison-Wesley
  8. Kurniawan, C., 2012.Perancangan Knowledge Management System PT. XYZ. Master Thesis, Graduate Program-Binus University, Jakarta
  9. Larose, D.T., 2005. Discovering Knowledge in Data : An Introduction to Data Mining. Wiley-Interscience, Canada
  10. Maier, R., 2007. Knowledge Management Systems - Information and Communication Technologies for Knowledge Management : Third edition.Springer, New York
  11. Manning, C.D., Raghavan P, dan Schütze H., 2009. Introduction to Information Retrieval. Cambridge University Press
  12. Mardia. K., Kent., Bibby., 1979. Multivariate Analysis, Academic Press
  13. Srividhya, R., Anitha, R., 2010. Evaluating preprocessing techniques in text categorization. international Journal of Computer Science and Application Issue, 49 -51
  14. Wibisono, Y., 2011. Perbandingan Partition Around Medoids (PAM) dan K-means Clustering untuk Tweets, Prosiding Konferensi Nasional Sistem Informasi. Medan, Februari 25-26, 483 – 486
  15. Xiong, H., Wu, J., dan Chen, J., 2009. K-Means clustering versus validation measures: a data distribution perspective. IEEE Transactions on Systems, Man, and Cybernetics – Part B 39 (2), 318-331

Last update:

  1. Penerapan Clustering K-Means Untuk Mendukung Pengelolaan Koleksi Pada Perpustakaan Fakultas Teknik Universitas Negeri Gorontalo

    Indhitya Padiku, Agus Lahinta. Jurnal Teknik, 20 (1), 2022. doi: 10.37031/jt.v20i1.206

  2. Penerapan Clustering K-Means Untuk Mendukung Pengelolaan Koleksi Pada Perpustakaan Fakultas Teknik Universitas Negeri Gorontalo

    Indhitya Padiku, Agus Lahinta. Jurnal Teknik, 20 (1), 2022. doi: 10.37031/jt.v20i1.206

  3. Sistem Pendukung Keputusan Berbasis K-Means untuk Evaluasi Keberhasilan Bisnis dan Nilai Perusahaan

    Sarmini Sarmini, Windiya Ma'arifah, Imam Tahyudin. Jurnal Sistem Informasi Bisnis, 14 (4), 2024. doi: 10.21456/vol14iss4pp363-374

Last update: 2025-05-19 14:34:31

No citation recorded.