Pola Sebaran Perumahan Terencana di Kota Banda Aceh
Bibliographic record
Abstract
Perumahan terencana di Kota Banda Aceh tersebar di 9 kecamatan yang berjumlah 169 perumahan. Kawasan perumahan tidak lepas dari berbagai aspek pendukung, salah satunya ialah aspek transportasi. Pendekatan yang digunakan dalam penelitian ini ialah kuantitatif deskriptif, dengan menggunakan alat bantu ArcGIS 10.4. Analisis yang digunakan untuk mengidentifikasi pola sebaran perumahan terencana di Kota Banda Aceh ialah analisis tetangga terdekat/ nearest neighbor analysis. Hasil penelitian menunjukan pola sebaran perumahan terencana di Kota Banda Aceh memiliki pola mengelompok (cluster pattern) dengan nilai Z-score –9,7087601, pola mengelompok dapat memudahkan penyediaan infrastruktur dan perencanaan transportasi umum, hanya saja perumahan terencana di Kota Banda Aceh banyak yang mengelompok jauh dari jaringan jalan utama.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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".