Analisis Data Mahasiswa dengan Metode Hierarchical K-Means untuk Mendukung Strategi Promosi Universitas Muhammadiyah Malang (Study Kasus Fakultas Teknik UMM)
| Main Author: | Marshelly, Nella Septi |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/50782/109/PENDAHULUAN.pdf http://eprints.umm.ac.id/50782/74/BAB%20I.pdf http://eprints.umm.ac.id/50782/75/BAB%20II.pdf http://eprints.umm.ac.id/50782/76/BAB%20III.pdf http://eprints.umm.ac.id/50782/77/BAB%20IV.pdf http://eprints.umm.ac.id/50782/78/BAB%20V.pdf http://eprints.umm.ac.id/50782/8/Lampiran.pdf http://eprints.umm.ac.id/50782/12/POSTER.pdf http://eprints.umm.ac.id/50782/ |
Daftar Isi:
- Lots of data produced by sophisticated information technology, starting from the fields of industry, economics, science and technology and various other fields of life. The application of information technology in the world of education can produce abundant data about students and the learning process produced. The concept of data mining has been known as a tool that can overcome difficulties in data processing. In data mining, the clustering technique is the process of grouping a number of data or objects with the same criteria into groups so that each cluster has data as similar as possible. Known for the two methods included in the clustering, namely partition and hierarchical, this method has advantages and disadvantages of each. In this case the hierarchical single linkage clustering and k-means clustering methods are applied to get better results both methods are combined.