ANALISIS CLUSTER NON-HIRARKI DENGAN METODE K-MODES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Analisis cluster merupakan suatu analisis multivariat yang digunakan untuk mengelompokkan objek-objek berdasarkan kemiripan karakteristik yang dimiliki. Salah satu teknik dari analisis cluster adalah metode K-Modes. Tujuan dari penelitian ini adalah untuk mengetahui jumlah cluster terbaik yang digunakan dalam pemilihan kegiatan ekstrakurikuler menari. Perbandingan hasil validitas cluster dilakukan berdasarkan nilai Davies-Bouldin Index (DBI) terkecil yang dihasilkan pada masing-masing cluster yaitu 2 cluster dan 3 cluster. Berdasarkan hasil analisis yang telah dilakukan pada perbandingan nilai DBI, diperoleh nilai terkecil sebesar 0,52 pada 2 cluster. Hasil penelitian menunjukkan bahwa cluster terbaik yang dihasilkan pada pemilihan kegiatan ekstrakurikuler menari adalah dengan menggunakan 2 cluster dimana anggota cluster 1 terdiri dari 56 siswi dan anggota cluster 2 terdiri dari 36 siswi.Kata Kunci: analisis multivariat, k-modes, davies-bouldin index
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it