PREFERENSI PILIHAN JENIS HUNIAN BERDASARKAN PERILAKU BELANJA GENERASI Z
Bibliographic record
Abstract
Generasi z merupakan bagian dari generasi milenial. Meski demikian, generasi z memiliki karakteristik perilaku dan kepribadian yang berbeda dengan generasi sebelumnya. Tujuan dari penelitian ini yakni untuk mengetahui preferensi pilihan jenis hunian berdasarkan perilaku belanja generasi z. Penelitian ini merupakan penelitian kuantitatif deskriptif. Hasil penelitian menyatakan bahwa meski generasi y dan z termasuk generasi milenial, namun ada beberapa karakteristik umum yang berbeda diantara keduanya dalam memilih hunian. Hal ini dibuktikan melalui preferensi pilihan hunian generasi z yang menjadi responden dalam penelitian ini berdasarkan perilaku belanjanya, meliputi aspek cara mencari produk hunian, merek pengembang, kepemilikan hunian, jenis properti hunian, dan privasi.
 
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.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".