Studi Perencanaan Bangunan Perkuatan Tebing Sebagai Upaya Pengendalian Longsor Sungai Kusan Kabupaten Tanah Bumbu Kalimantan Selatan
Bibliographic record
Abstract
Sungai Kusan pada wilayah DAS Kusan banyak mengalami longsor pada tebing sungai akibat banjir pada bulan Januari-April 2021. Untuk itu perlu dilakukan perencanaan perkuatan tebing sungai agar dapat mencegah kerugian yang lebih besar. Pada studi ini, dilakukan analisis dengan beberapa metode untuk mengetahui perencanaan bangunan perkuatan tebing yang ideal berdasarkan kondisi profil aliran sungai dan kestabilan tebing eksisting. Dari hasil analisis, didapatkan penyebab longsor akibat gerusan sungai dan beberapa kondisi eksisting tebing tidak stabil. Berdasarkan kondisi tersebut, dilakukan pengendalian longsor dengan dinding penahan kantilever berdimensi 7x7 m. Pada pondasi kantilever di desain mini pile sepanjang 12 m, berjumlah 7 buah untuk meneruskan beban ke dalam lapisan tanah keras. Selain itu, ditambahkan desain blok beton dengan dimensi 0,7x0,7x0,7 m yang dilengkapi geotextile untuk mencegah gerusan pada tebing sungai dan pondasi kantilever. Berdasarkan kombinasi desain tersebut, maka pengendalian longsor pada tebing Sungai Kusan dapat diterima.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".