OPTIMASI PENGELOLAAN AIR BENDUNG CAWAK UNTUK DAERAH IRIGASI CAWAK DENGAN PROGRAM SOLVER (Studi kasus : Kemanteren Nglumber_Kecamatan Kepohbaru_Kabupaten Bojonegoro)
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
AbstractBendung Cawak is located in the district of Kepohbaru, Bojonegoro. Bendung Cawak is used for irrigation and water supplies of Kepohbaru, water availability is insufficient, while the amount of land and also residents who need water, so optimization Bendung Cawak is necessary for the water pitcher bendung can be optimized according to the needs.In this study, to maximize the area of land irrigated area to be optimized. In the optimization model used is the optimization of the monthly for 1 year by calculating the area of irrigated land available, land irrigation is met, the greater availability of water and irrigation needs are met. Optimization method used in this calculation is Program Solver.The results obtained by the reliable discharge available in the Cawak dam reservoir are 2.547 m3 / second. The need for irrigation water with the cropping pattern of Palawija-Padi-Padi at the beginning of planting in August I is 0.579 l / sec / ha as a planting plan with the minimum water requirements. As well as optimization, the optimum cropping pattern and initial planting are August I with the Palawija-Padi-Padi planting intensity 291% and with irrigation area MT I 675 ha, MT II 742 ha, MT III 742 ha. AbstrakBendung Cawak terletak di Kecamatan Kepohbaru, Kabupaten Bojonegoro. Layanan Bendung Cawak dipergunakan untuk keperluan irigasi di Daerah Irigasi Cawak Kecamatan Kepohbaru, ketersediaan air yang tidak mencukupi sedangkan banyaknya lahan yang membutuhkan air , sehingga Optimasi Bendung Cawak sangat diperlukan agar air tampungan Bendung dapat dioptimalkan sesuaidengan kebutuhan.Pada studi ini, untuk memaksimalkan luas lahan irigasi dilakukan optimasi luas lahan irigasi . Dalam model optimasi yang digunakan adalah optimasi satu bulanan selama 1 tahun dengan memperhitungkan luas lahan irigasi yang tersedia, luas lahan irigasi yang terpenuhi, besarnya ketersediaan debit air maksimal, dan kebutuhan air irigasi yang dipenuhi. Metode optimasi yang digunakan dalam perhitungan ini yaitu Program Solver.Hasil yang diperoleh debit andalan yang tersedia di tampungan bendung cawak adalah 2,547 m3/detik. kebutuhan air irigasi dengan pola tanam Palawija-Padi-Padi awal tanam Agustus I itu sebesar 0,579 lt/dtk/ha sebagai rencana tanam dengan kebutuhan air paling minimum.Serta optimasi didapatkan pola tanam dan awal tanam yang paling optimum adalah Agustus I dengan pola tanam Palawija-Padi-Padi intensitas tanam 291% dan dengan luas areal irigasi MT I 675 ha, MT II 742 ha, MT III 742 ha.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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