ALGORITMA CLUSTERING K-MEDOIDS PADA E-GOVERNMENT BIDANG INFORMATION AND COMMUNICATION TECHNOLOGY DALAM PENENTUAN STATUS EDGI - Iman Saufik Suasana; Zaenal Mustofa (UNIVERSITAS STEKOM, 2020)
Abstract E-Government is a tool to improve relations with the community, now the development of E-Government in various world governments are monitored directly by the UN through the United Nations E-Government Survey. This monitoring uses the framework where in this EGDI there are 3 factors considered: Online Service Index, Telecommunication Infrastructure Index and Human Capital Index. But the determination of EDGI status is less accurate because it must be based on knowledge and processing of the number of existing data so that required a calculation that applies clustering method with data mining techniques. Kmedoids using clustering techniques, capable of producing optimal Bouldin Index values and this study also determines the medoid distance calculation to obtain optimal algorithm, the value obtained from Bouldin Index on the Chebyshev K-medoids method 0.593. Thus, the optimal clustering scheme with distance ratio is the minimum index value of K-medoids Chebyshev.