Vol.9, No.4, November 2020.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Unsupervised Data Mining with K-Medoids Method in Mapping Areas of Student and Teacher Ratio in Indonesia


Adya Hermawati, Sri Jumini, Mardiah Astuti, Fajri Ismail, Robbi Rahim


© 2020 Robbi Rahim, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 4, Pages 1614-1618, ISSN 2217-8309, DOI: 10.18421/TEM94-37, November 2020.


Received: 20 August 2020.

Revised:   09 October 2020.
Accepted:  15 October 2020.
Published: 27 November 2020.




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 obtained. This shows that the results of the cluster formed are optimal (the smaller the better). The test results with the parameter Performance (Classification) show the results of classification error = 2.50%. The results of the research can be used as information to determine the ratio of students and teachers because the higher the value of this ratio means that the level of teacher supervision and attention to students is reduced so that the quality of teaching tends to be lower.


Keywords –Data Mining, k-medoids method, Davies Bouldin Index, student and teacher, ratio.



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