| dc.contributor.author | Puspitasari, Novianti | |
| dc.contributor.author | Widians, Joan Angelina | |
| dc.contributor.author | Pohny | |
| dc.date.accessioned | 2020-11-23T09:57:57Z | |
| dc.date.available | 2020-11-23T09:57:57Z | |
| dc.date.issued | 2018-06-01 | |
| dc.identifier.citation | 1 | en_US |
| dc.identifier.issn | 2301-7201 | |
| dc.identifier.uri | http://repository.unmul.ac.id/handle/123456789/5399 | |
| dc.description | Turnit in paper | en_US |
| dc.description.abstract | Processing 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 result 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 cluster (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 users. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IT SMART : Jurnal Ilmiah Teknologi dan Informasi, Universitas Sebelas Maret | en_US |
| dc.subject | Fuzzy C-Means, Diseases, Degenerative, Infection, Clustering | en_US |
| dc.title | Turnit in : A Clustering Of Generative And Infectious Diseases Using Fuzzy C-Means | en_US |
| dc.type | Other | en_US |
