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Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/7436
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dc.contributor.authorPuspitasari, Novianti-
dc.contributor.authorWidians, Joan Angelina-
dc.contributor.authorPohny, Pohny-
dc.date.accessioned2021-10-20T13:56:14Z-
dc.date.available2021-10-20T13:56:14Z-
dc.date.issued2018-06-14-
dc.identifier.citationMendeleyen_US
dc.identifier.issn2541-5689-
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/7436-
dc.descriptionPeer Review: Jurnal Nasional Tidak Terakreditasi. Joan Angelina Widiansen_US
dc.description.abstractProcessing information of the most disease suffered by the people in a region, particularly to those receive Health Insurance card (Jaminan Kesehatan Daerah; JAMKESDA) was one of the government focuses. The study used Fuzzy C-Means (FCM), to process the disease data suffered by JAMKESDA users for four years in regional public hospital. The results showed that FCM method could group the disease into two forms namely generative and infectious one. Based on the cluster validity test using Partition Coefficient (PC), the partition value of fuzzy is higher by using two clusters (0.68) rather than three clusters. In conclusion, the forming model of two clusters is more optimal than that three one to process data disease of JAMKESDA usersen_US
dc.language.isoen_USen_US
dc.publisherUniversitas Sebelas Mareten_US
dc.relation.ispartofseriesVol 7. No.1;-
dc.subjectFuzzy C-Means, Penyakit, Degeneratif, Infeksi, Clustering.en_US
dc.titlePeer Review: Jurnal Nasional_Widians_A Clustering of generative and Infectious Diseases using Fuzzy C-Meansen_US
dc.typeArticleen_US
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