Optimasi WWR untuk Penghawaan dan Pengendalian Kebisingan Lingkungan dalam Hunian Tropis Lembab
Bibliographic record
Abstract
Dalam lingkungan perkotaan, penghawaan dan kebisingan merupakan faktor yang paling penting dalam mempengaruhi lingkungan dalam bangunan. Penelitian ini mengkaji WWR (Window to Wall Ratio) sebagai kompromi kebutuhan penghawaan dan pengendalian kebisingan rumah Jawa yang menjadi studi kasus dari hunian tropis lembab. Kebutuhan luas bukaan (WWR) memiliki perilaku yang kontradiktif, yaitu antara kebutuhan bukaan maksimal untuk aliran angin dan minimum untuk mengurangi kebisingan. Lokasi penelitian ini berada di dataran rendah (Surabaya, 0-50 m msl) dan di dataran tinggi (Malang, 440-667 m msl). Kedua kota besar tersebut dipilih karena memiliki kemiripan budaya dan arsitektur. Hasil penelitian ini menunjukkan bahwa rentang WWR sebagai bentuk integrasi pemenuhan kebutuhan penghawaan dan pengendalian kebisingan, yaitu dataran rendah/siang hari: 0.13-100% (standar survei), 0.13-5.24% (standar WHO); dataran rendah/malam hari: 0-100% (standar survei), 0-3.24% (standar WHO); dataran tinggi/siang hari: 0.24-100% (standar survei), 0.24-70.48% (standar WHO); dan dataran tinggi/malam hari: 0-100% (standar survei/standar WHO).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".