Analisa Penyebab Keterlambatan Proyek Pembangunan Sidoarjo Town Square Menggunakan Metode Fault Tree Analysis (FTA)
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
Setiap proyek konstruksi pada umumnya mempunyai rencana pelaksanaan dan jadwal pelaksanaan tertentu, kapan pelaksanaan proyek tersebut harus dimulai, kapan proyek tersebut harus diselesaikan, bagaimana proyek tersebut akan dikerjakan, serta bagaimana penyediaan sumber dayanya. Diharapkan dalam pelaksanaanya tidak terjadi keterlambatan karena keterlambatan yang terjadi akan mengakibatkan meningkatnya biaya proyek. Namun, dalam pelaksanaan proyek pembangunan Sidoarjo Town Square mengalami keterlambatan. Metode yang direncanakan dalam pembahasan untuk mengetahui faktor yang mempengaruhi terjadinya keterlambatan yaitu Metode Fault Tree Analysis (FTA) dan Method Obtain Cut Set (MOCUS). Didapatkan bahwa item pekerjaan yang mengalami keterlambatan yaitu: pekerjaan struktur GWT STP, pekerjaan finishing fasade dan canopy, dan pekerjaan atap. Dari hasil analisa FTA dari ketiga top event, didapatkan bahwa keterlambatan terjadi dikarenakan perubahan desain serta perijinan, dimana keduanya akibat faktor penyebab keterlambatan dari pihak owner.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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