Pengelompokan Pembiayaan Nasabah Klaim Asuransi Pengguna Kendaraan Bermotor dengan Metode K-Medoids
| Main Authors: | Aulanda, Lulu, Windarto, Agus Perdana, Okprana, Harly |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Forum Kerjasama Pendidikan Tinggi (FKPT)
, 2021
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| Online Access: |
https://ejurnal.seminar-id.com/index.php/tin/article/view/902 https://ejurnal.seminar-id.com/index.php/tin/article/view/902/610 |
Daftar Isi:
- In general, insurance is providing risk coverage to the insurer, namely the insurance company for a predetermined period and agreements. Insurance or coverage is an agreement between two or more parties, in which the insurer binds himself to the insured, by receiving an insurance premium, to provide compensation to the insured due to loss, damage or loss. The k-medoids method is one of several clustering methods in data mining which is part of partitional clustering. This method uses objects in a collection of objects to represent a cluster. The k-medoids clustering method can be applied to customer financing data for insurance claims on motor vehicle users, so that the financing grouping can be seen based on these data. From the grouping data, the characteristics can be seen so that it is known that the cluster is low, cluster is medium and cluster is high