Arahan Peningkatan Kenyaman Taman Venus Sebagai Ruang Terbuka Hijau Publik Kota Sangatta
Bibliographic record
Abstract
Taman yang nyaman dapat terwujud dengan memperhatikan aspek sirkulasi, aroma, bentuk, keamanan, kebersihan dan keindahan. Tujuan yang ingin dicapai dalam penelitian ini adalah memberikan arahan peningkatan kenyamanan Taman Venus. Analisis deskriptif komparatif merupakan metode yang digunakan dalam merumuskan arahan peningkatan kenyamanan taman dengan cara membandingkan hasil analisis dengan studi literatur dan kebijakan yang ada. Output yang didapatkan ialah peningkatan kenyamanan pada sirkulasi dengan pelebaran area pejalan kaki dan penataan area parkir kendaraan, variabel aroma dengan penanaman perdu pada area sekitar pembuangan sampah, variabel bentuk dengan kursi dari bahan anti korosi serta penambahan mushola, variabel keamanan dengan penambahan CCTV dan lampu pedestrian, variabel kebersihan dengan pengelolaan pembuangan sampah, variabel keindahan dengan meredesain lampu dan kursi taman dengan ukiran batik serta penanaman perdu pada area yang mengalami kekeringan, pengelolaan kebersihan kolam ikan dan air mancur.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.008 |
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".