Benediction Contribution towards Job Performance through Quality Work Employees at the University of Batam, Indonesia
Bibliographic record
Abstract
This study aims to identify and examine whether prayer intentions to contribute to the quality of work: Is ritual process contributes to the quality of work? Is a prayer accompanies efforts to contribute to the quality of work? Is prayer intentions to contribute to job performance? Whether the process rituals contribute to job performance, Do businesses contribute to job performance?The research was conducted on the University’s staff Batam totaling 193 people. University Batam pick the 16 courses 8 accredited B and 8 C. accredited university Batam has the facilities and the physical facilities are very adequate and equipped with two reliable Mosque and pray every Zohar and Asr prayer and diligent employees after prayers, whether her payer give contribution to job performance, work quality? Positive phenomenon is interesting to study the variable Benediction, Job Performance, quality Work. Data analysis was performed using the method Structural Equation Model (SEM).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".