KETERCUKUPAN AIR TEMPORAL SEBAGAI INDIKATOR KETERSEDIAAN AIR KAWASAN (STUDI KASUS DAS CILIWUNG HULU)
Bibliographic record
Abstract
DAS Ciliwung Hulu wilayahnya meliputi kawasan wisata puncak, menpunyai curah hujan rata-rata tahunan lebih besar dari 3.000 mm, namun beberapa kawasan mengalami kekurangan air baku diwaktu musim kemarau. Kondisi tersebut akibat pembangunan lahan untuk pariwisata atau pemukiman dengan laju 12.34% per tahun, sehingga air hujan yang masuk ke dalam tanah (infiltrasi) hanya 20%. Tujuan dari penelitian ini adalah untuk mengetahui ketersediaan air sepanjang tahun dari masing-masing sub DAS di DAS Ciliwung Hulu dengan indikator ketercukupan air temporal. Metode yang digunakan adalah: F.J. Mock untuk analisis debit andalan, Indeks Pollutan untuk analisis kualitas air, neraca air untuk surplus dan defisit air, dan indeks ketercukupan air temporal (IKaT). Hasil analisis menunjukkan: Sub DAS Ciseuseupan untuk katagori ketersediaan air termasuk ke dalam katagori tidak cukup, sedangkan dalam katagori ketercukupan air temporal masuk kurang cukup; Sub DAS Cibogo dalam katagori ketersediaan air masuk dalam status kurang cukup, namun dalam katagori ketercukupan air temporal termasuk ke dalam status sedang: sub DAS Cisarua baik untuk katagori ketersediaan maupun ketercukupan air temporal masuk dalam status sedang; dan sub DAS Ciesek, Ciliwung Hulu, dan Cisakabirus mempunyai skor 1 baik untuk ketercukupan air temporal maupun keterseiaan air.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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 teacher head, 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".