Analisis Kinerja Konsultan Pengawas Dalam Pelaksanaan Proyek Konstruksi
Bibliographic record
Abstract
A civil construction project is said to be successful if it meets three parameters, namely cost, quality and time, where the project costs are in accordance with the budget, the quality of the project is achieved according to specifications or requirements and the maximum project duration is the same as the planned time. However, in its implementation, projects are often faced with certain conflicts, one of which has an impact on the completion time, so it is felt necessary to involve a supervisory consultant in it in the hope of being able to provide supervision and control over each work item's progress. In relation to roads as an example of a civil building in the form of land transportation infrastructure which includes all its parts, this is reflected in the Short Road Reconstruction Project - Tanah Garo in Muara Tabir District, Tebo Regency, Jambi Province which uses the 2022 National Economic Recovery Loan (PEN) funds amounting to Rp. . 49,638,999,000 for flexible pavement work along 13,503 m for 105 calendar days, research was carried out on several factors and variables regarding the significant role of supervisory consultants in keeping the project on track. The research method is qualitative analysis which is developmental in nature and uses the help of the Microsoft Excel 2019 application in processing data. From the results of the analysis, it was concluded that the performance of supervision and quality control of work carried out by CV. Atifa Cipta Plan as the supervisory consultant for the Short Road Reconstruction Project - Tanah Garo received the highest average score among the six other factors, namely 4.80, which means very good.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".