Perkiraan Waktu Dalam Penyelesaian Proyek Kolam Retensi Sirnaraga Menggunakan Penerapan EVA (Earned Value Analysis)
Bibliographic record
Abstract
Kolam Retensi adalah suatu kolam yang dapat menampung atau meresap air sementara yang terdapat didalamnya, tentunya dalam pelaksanaan kontruksinya harus direncanakan penjadwalan yang matang. Metode “Nilai Hasil” (Earned Value) merupakan suatu metode pengendalian yang digunakan untuk mengendalikan biaya dan jadwal proyek secara terpadu. Metode ini dapat memberikan informasi dalam status kinerja proyek pada suatu periode pelaporan dan memberikan informasi prediksi biaya yang dibutuhkan serta waktu untuk menyelesaikan seluruh pekerjaan berdasarkan indikator kinerja saat pelaporan. Dalam penelitian ini dicoba menhitung perkiraan waktu dalam penyelesaian proyek dengan menggunakan metode tersebut agar diharapkan mendapatkan penjadwalan konstruksi yang efisien.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".