PENGARUH KEPUASAN KERJA TERHADAP KINERJA KARYAWAN MILENIAL PT SEMEN PADANG DENGAN VARIABEL DEMOGRAFIS SEBAGAI MODERATOR
Bibliographic record
Abstract
PENGARUH KEPUASAN KERJA TERHADAP KINERJA KARYAWAN MILENIAL PT SEMEN PADANG DENGAN VARIABEL DEMOGRAFIS SEBAGAI MODERATOR ABSTRAK Penelitian ini bertujuan untuk mengetahuai pengaruh kepuasan kerja terhadap kinerja karyawan milenial dengan variabel demografis sebagai moderator. Penelitian in dilaksanakan terhadap karyawan milenial PT Semen Padang dengan sampel penelitian sebanyak 211 orang. Pengolahan data penelitian dilakukan dilakukan dengan SEM-PLS. Hasil penelitian menunjukkan bahwa aspek kepuasan kerja yang berpengaruh positif dan signifikan terhadap kinerja sesuai urutan pengaruh paling besar adalah karakteristik pekerjaan, komunikasi, rekan kerja, dan penghargaan. Sementara variabel gaji, kesempatan promosi, atasan, dan tunjangan diketahui tidak berpengaruh terhadap kinerja. Sedangkan untuk variabel prosedur dan peraturan kerja ditemukan berpengaruh negatif dan signifikan. Selanjutnya untuk variabel demografis terbukti memoderasi hubungan antara kepuasan dan kinerja. Kinerja yang dipengaruhi oleh aspek kepuasan kerja berbeda untuk variabel lokasi kerja, masa kerja, dan pendidikan. Kata kunci: Kinerja; Kepuasan Kerja; Demografis; Milenial \nPENGARUH KEPUASAN KERJA TERHADAP KINERJA KARYAWAN MILENIAL PT SEMEN PADANG DENGAN VARIABEL DEMOGRAFIS SEBAGAI MODERATOR ABSTRACT The purpose of this research is to determine the effect of job satisfaction on millennial employee performance with demographic variables as moderators. This research was conducted on PT Semen Padang millennial employees with a sample of 211 people. Research data processing was carried out by SEM-PLS. The results showed that aspects of job satisfaction that had a positive and significant effect on performance in the order of the greatest influence were job characteristics, communication, coworkers, and appreciation. While variable salary, promotion opportunities, supervisors, and fringe benefits are known to have no effect on performance. As for the variable procedures and work regulations found negative and significant effect. Furthermore, demographic variables moderate the relationship between satisfaction and performance. Performance that is influenced by aspects of job satisfaction was found to be different for work location, work period, and education variables. Keywords: Performance; Job satisfaction; Demographic; Millennial
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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 | 0.004 | 0.014 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 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".