Adya, Hermawati and Sri, Jumini and Mardiah, Astuti and Fajri, Ismail and Robbi, Rahim (2020) Unsupervised Data Mining with K-Medoids Method in Mapping Areas of Student and Teacher Ratio in Indonesia. TEM Jurnal, 9 (4). pp. 1614-1618. ISSN 2217-83
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Abstract
The purpose of this study was to analyze the k-medoids method in conducting cluster mapping in the ratio of the number of students and teachers in Indonesia by region, especially at the elementary school level. The data source is secondary obtained from the Ministry of Education and Culture which is processed by the Central Statistics Agency (abbreviated as BPS) in the BPS Catalog: 4301008 concerning the Portrait of Indonesian Education. The analysis process uses the help of Rapid Miner software by using parameters of the Davies Bouldin Index (DBI) and Performance (Classification). By using three cluster labels, namely the high cluster (K1), normal cluster (K2) and poor cluster (K3), it was found that 3 provinces were in the high cluster, 9 provinces were in the normal cluster and 22 provinces were in the fewer clusters. By testing the cluster results (k = 3) through the DBI parameter the value = 0.587 was
| Item Type: | Article |
|---|---|
| Subjects: | 300 Ilmu sosial, Sosiologi dan Antropologi > 370 Pendidikan > Aspek sosial dari pendidikan |
| Depositing User: | Fajri Ismail - |
| Date Deposited: | 07 Jun 2023 02:22 |
| Last Modified: | 07 Jun 2023 02:22 |
| URI: | http://repository.radenfatah.ac.id/id/eprint/28088 |
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