PENGEMBANGAN INFRASTRUKTUR BERBASIS RESILIENT CITY DI KOTA KENDARI SULAWESI TENGGARA
Bibliographic record
Abstract
Resilient city memiliki beberapa prinsip di antaranya prinsip ketahanan bencana, ketahanan pangan, ketahanan infrastruktur, ketahanan sosial, ketahanan sumber daya, serta integrasi alam. Melihat masalah yang ada di Kota Kendari, salah satu konsep yang paling efektif untuk diterapkan adalah konsep ketahanan infrastruktur. Sebagai mesin pertumbuhan, infrastruktur kota mempunyai risiko untuk terkena dampak bencana. Penelitian ini bertujuan untuk mengetahui kondisi eksisting infrastruktur yang ada di Kota Kendari serta bagaimana menerapkan prinsip-prinsip ketahanan kota (Resilient City) pada Infrastruktur di Kota Kendari khususnya di kawasan BWK V sebagai lokasi yang cukup rawan bencana banjir. Penelitian ini menggunakan metode deskriptif kualitatif dimana Cognitive Mapping digunakan sebagai teknik analisisnya. Hasil penelitian menunjukan bahwa kondisi infrastruktur di lokasi penelitian dari segi fisik belum memadai. Ketahanan infrastruktur yang berbasis pada resilient city dapat diterapkan mulai dari tahap perencanaan sampai pemeliharaan. Penelitian ini diharapkan dapat digunakan oleh pemerintah sebagai acuan dalam mengembangkan kota berketahanan terhadap bencana.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".