NURROCHMAN, MA’RUF (2024) CLASSTERIZATION OF STUDY GROUPS USING THE K-MEDOIDS METHOD. Tugas Akhir thesis, Informatics.
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Abstract
ABSTRACT Study groups are formed to improve the academic abilities of each student. The current formation of study groups generally still uses the principle of similarity at a glance. This means that every student who is part of a study group does have the same interests or knowledge orientation, but not specifically. In this case, researchers see that clustering techniques can be used to group study groups based on research titles. The K-Medoids method is applied to a web-based clustering system. This system allows users to customize the clustering model and the various data that will be processed. Training was carried out on 577 data into 8 clusters. Each cluster has its own characteristics which can be seen from the existing terms. Testing the clustering model uses 10 real data. The test obtained the results of the researcher's analysis as a system tester, namely that there was a number of data that had cluster discrepancies. Another test with dominant title data with 10 foreign words resulted in the conclusion that much of the data was predicted to lead to a particular cluster. Thus, it can be concluded that this web-based clustering system still requires improvement to increase the accuracy of grouping results.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 21 May 2024 06:25 |
| Last Modified: | 21 May 2024 06:25 |
| URI: | http://eprints.uty.ac.id/id/eprint/15577 |
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