PERENCANAAN PELAKSANAAN PROYEK KONSTRUKSI KANTOR KPU KABUPATEN BADUNG
Bibliographic record
Abstract
Perencanaan pelaksanaan proyek konstruksi merupakan tahapan penting yang bertujuan untuk mengoptimalkan waktu, biaya, dan mutu pekerjaan. Dalam proyek pembangunan Gedung Kantor KPU Kabupaten Badung, perencanaan pelaksanaan menjadi sangat krusial mengingat lokasi proyek yang berada di kawasan padat permukiman, sehingga diperlukan metode pelaksanaan yang tepat dan efisien. Permasalahan yang dihadapi adalah bagaimana menyusun jadwal pelaksanaan, menghitung kebutuhan sumber daya, serta merencanakan biaya secara sistematis agar proyek dapat berjalan sesuai rencana. Penelitian ini menggunakan metode Precedence Diagram Method (PDM) untuk menyusun penjadwalan proyek dan Microsoft Project sebagai alat bantu visualisasi. Selain itu, dilakukan analisis kebutuhan sumber daya manusia, bahan, dan alat serta penyusunan Rencana Biaya Pelaksanaan (RBP) dan Rencana Anggaran Biaya (RAB). Hasil penelitian menunjukkan bahwa perencanaan pelaksanaan dengan metode PDM menghasilkan jadwal proyek yang terstruktur dan efisien. Total biaya yang diperoleh dari hasil analisis RBP adalah sebesar Rp 4,159,270,327.34, sedangkan RAB mencapai Rp 4,623,397,141.26, dengan selisih biaya sebesar Rp 464,126,813.93. Penelitian ini diharapkan menjadi acuan perencanaan pelaksanaan proyek konstruksi bangunan serupa, khususnya dalam konteks penggunaan metode PDM.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".