SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LAHAN PERTANIAN YANG TEPAT UNTUK MENINGKATKAN HASIL PANEN CABAI MENGGUNAKAN METODE MOORA
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
Decision support system is a system that can solve problems that occur in ranking quickly and can find out the highest to lowest value in a selection. In this paper is one of the case studies that can be solved using a decision support system, where the problem faced in the selection of agricultural land is how to choose the best chili and to make a selection must use manually and the assessment process takes a long time. to get results. Therefore created a problem how to determine an appropriate agricultural land selection problem to determine the good chili crop yield using the MOORA method and where the MOORA method is used to test in correctness that aims to determine the accuracy of the value obtained by the system, the results of the best land selection is in the city area of binjai jln sawi payaroba west binjai, plus the value of the weight of the criterion and the modification trial which aims to find out how many criteria can be added.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it