DATA CLUSTERING MENGGUNAKAN METODOLOGI CRISP-DM UNTUK PENGENALAN POLA PROPORSI PELAKSANAAN TRIDHARMA

Irwan Budiman, M.Kom and Ir. Toni Prahasto, M.ASc, Ph.D and Yuli Christiyono, ST, MT (2012) DATA CLUSTERING MENGGUNAKAN METODOLOGI CRISP-DM UNTUK PENGENALAN POLA PROPORSI PELAKSANAAN TRIDHARMA. Masters thesis, Universitas Diponegoro.

[img]
Preview
PDF
1619Kb

Abstract

Quality of human resources faculty can be reflected from the implementation of productivity and quality Tridharma (education, research, community service and supporting field activities). Lecturer Workload and Evaluation of Higher Education Tridharma (BKD and the EPT-PT) aims to ensure the implementation of the faculty task runs according to the criteria set out in legislation. Data clustering Tridharma implementation is needed to get some knowledge of the pattern of Tridharma implementation at college. Clustering as a data mining technique should be scalable, reliable and meet an agreed standard. CRISP-DM is the standardization of data mining is used in this study. The results of data clustering found the pattern of proportion of Tridharma into 3 clusters representing patterns: professionals, managers and teachers. Keywords: Clustering, CRISP-DM, K-Means, Tridharma

Item Type:Thesis (Masters)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Postgraduate Program > Master Program in Information System
ID Code:36029
Deposited By:Mr Musa MSI
Deposited On:31 Aug 2012 14:18
Last Modified:31 Aug 2012 14:18

Repository Staff Only: item control page