Analisis Kecepatan Putar Silinder Perontok Terhadap Kinerja Mini Power Thresher Hasil Rekayasa UPJA Desa Sungai Kelambu
Bibliographic record
Abstract
Various types of power threshers have been developed to suit conditions in the field. The development of the power thresher was also carried out by UPJA Sungai Kelambu Village, Sambas Regency by making a mini power thresher that was designed to suit the conditions of the land and the needs of local farmers. The purpose of this research was to obtain a relationship between threshing rotational speed and performance on the mini power thresher. The threshing cylinder rotational speed was varied at 669 and 778 rpm. The measured performance of the mini power thresher was feeding capacity, threshing capacity, cleanliness, percentage of grain not threshed, percentage of scattered grain, threshing efficiency, percentage of yield loss, fuel consumption, and increase in cracked grain. The test sample used was IR 64 rice. Based on the test results, the rotational speed of the thresher cylinder has a very significant effect on the threshing performance of the mini power thresher. Changes in threshing cylinder rotational speed from 669 rpm to 778 rpm can improve the performance of the mini-power thresher in terms of feed capacity, threshing capacity, threshing cleanliness, percentage of grain scattered, and percentage of yield loss. The decrease in performance is found in fuel consumption and the percentage of cracked grain. The variables that relatively unchanged were the percentage of grain not threshed and threshing efficiency. The operation of this mini power thresher is recommended at a thresher cylinder rotational speed of 778 rpm.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".