Perkiraan Waktu Dalam Penyelesaian Proyek Kolam Retensi Sirnaraga Menggunakan Penerapan EVA (Earned Value Analysis)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 it