Optimasi Produktivitas Alat Berat dengan Metode Simpleks LINGO (Heavy-Duty Productivity Optimization Using LINGO Simplex Method)
Bibliographic record
Abstract
One of the areas that are now the location for clearing residential land is in Karang Widoro Village, which is now a plantation and fruit farm and has been purchased by the developer Podo Joyo Masyhur (PJM) Group who then runs the project "The OZ Tidar Housing, Malang" where the land being worked on has a total area of 47,000 m2. Construction work involving digging, hauling, and leveling equipment requires consideration so that the work can be carried out following the target volume of work and the specified time allocation. So it is necessary to carry out project control by considering aspects that affect excavation and backfill work by heavy equipment in the field. Several choices of methods in optimizing calculations and selecting tools to increase work productivity of heavy equipment are the Linear Simplex Method Program. Then combined with the use of currently widely developed software, this method is more effective in finding the best solution for a function with several variables from existing problems. LINGO can be a solution for optimizing work execution so that work targets can be completed on time with minimum operational costs and minimizing the number of units obtained. The results of the analysis of several factors that influence productivity are calculated using a linear program to achieve an optimum choice. The Simplex Method Lienar Program Optimization Model is: Minimization Z = 1836000 x1 + 483000 x2 + 712200 x3 (in IDR/day).ABSTRAKSalah satu area yang sekarang menjadi lokasi pembukaan lahan perumahan adalah di Desa Karang Widoro yang sekarang menjadi perkebunan dan pertanian buah serta telah dibeli oleh pengembang Podo Joyo Masyhur (PJM) Group yang kemudian menjalankan proyek “Perumahan The OZ Tidar, Malang” dimana lahan yang dikerjakan memiliki luas total 47.000 m2. Pada pekerjaan konstruksi yang mengikutsertakan alat gali-muat, angkut, dan perata tanah memerlukan pertimbangan agar pekerjaan dapat dilaksanakan sesuai dengan target volume pekerjaan dan alokasi waktu yang ditetapkan. Maka perlu dilakukan pengendalian proyek dengan mempertimbangkan aspek-aspek yang berpengaruh terhadap jalannya pekerjaan galian dan urukan oleh alat berat di lapangan. Beberapa pilihan metode dalam perhitungan optimasi dan pemilihan alat untuk peningkatan produktivitas kerja alat berat adalah Program Linear Metode Simpleks. Lalu digabungkan dengan penggunaan perangkat lunak yang saat ini banyak berkembang, metode ini lebih efektif dalam pencarian solusi terbaik suatu fungsi dengan beberapa variabel dari permasalahan yang ada. LINGO dapat menjadi solusi dalam optimasi pelaksanaan pekerjaan sehingga target pekerjaan dapat selesai tepat waktu dengan biaya operasional yang minimum serta meminimalkan jumlah unit yang didapatkan. Hasil analisis terhadap beberapa faktor yang berpengaruh pada produktivitas dan dihitung menggunakan program linear sehingga mampu dicapai pilihan yang optimum. Model Optimasi Program Lienar Metode Simpleks yang ditetapkan adalah : Minimasi Z =1836000 x1 + 483000 x2 + 712200 x3 (dalam Rp/hari)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".