PENGARUH SISTEM REMUNERASI DAN LINGKUNGAN KERJA TERHADAP KEPUASAN KARYAWAN BPJS KETENAGAKERJAAN WILAYAH 3T DENGAN BEBAN KERJA SEBAGAI VARIABEL MODERASI
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menganalisis pengaruh sistem remunerasi dan lingkungan kerja terhadap kepuasan karyawan di BPJS Ketenagakerjaan Wilayah 3T. Selain itu, penelitian ini juga mengeksplorasi peran beban kerja sebagai variabel moderasi dalam hubungan tersebut. Metode yang digunakan adalah survei dengan kuesioner, dan analisis data dilakukan melalui analisis regresi moderasi. Hasil penelitian menunjukkan bahwa sistem remunerasi dan lingkungan kerja memiliki pengaruh positif dan signifikan terhadap kepuasan karyawan. Namun, beban kerja terbukti melemahkan pengaruh positif dari sistem remunerasi dan lingkungan kerja terhadap kepuasan karyawan. Temuan ini memberikan wawasan tentang pentingnya pengelolaan beban kerja dalam upaya meningkatkan kepuasan kerja karyawan di lingkungan kerja yang menantang. This study aims to analyze the influence of the remuneration system and work environment on employee satisfaction at BPJS Ketenagakerjaan Region 3T. Additionally, it explores the role of workload as a moderating variable in this relationship. The research employs a survey methodology using a questionnaire, with data analyzed through moderated regression analysis. The results indicated that both the remuneration system and work environment positively and significantly affect employee satisfaction. However, workload has been found to weaken the remuneration system and the positive influence of the work environment on employee satisfaction. These findings provide insights into the importance of managing workload to enhance employee satisfaction in challenging work environments.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".