Analisis Faktor Risiko Kelelahan Kerja pada Kurir PT Tiki Jalur Ekakurir (JNE) di Wilayah Kecamatan Pondok Gede Kota Bekasi tahun 2022
Bibliographic record
Abstract
Penelitian ini memiliki tujuan untuk melihat gambaran faktor risiko kelelahan yang dialami oleh kurir PT JNE di wilayah Kecamatan Pondok Gede Kota Bekasi tahun 2022. Penelitian dilakukan pada 31 orang kurir yang beroperasi di wilayah Pondok Gede dan sekitarnya pada Mei – Juni 2022. Penelitian ini menggunakan studi cross-sectional dengan metode kuantitatif. Variabel dependen penelitian ini adalah kelelahan kerja, dan variabel independen yaitu faktor risiko terkait pekerjaan (shift kerja, durasi kerja, waktu istirahat), faktor risiko non pekerjaan (masa kerja, commuting time, dan kepuasan terhadap sistem insentif dan reward), dan faktor individu (usia, status gizi, kualitas tidur, kuantitas tidur, ketakutan pada akan Covid-19, dan kebiasaan sarapan). Hasil menunjukkan bahwa 51,6% (16 orang) mengalami kelelahan sedang, 35,5% (11 orang) kelelahan ringan, dan 12,9%(4 orang) tidak kelelahan. Kelelahan sedang cenderung dialami oleh durasi kerja berlebih (39,3%), beban kerja rendah (75%), istirahat cukup (45%), shift kerja siang (41,7%), masa kerja >5 tahun (47,1%), commuting time lama (57,1%), puas dengan sistem reward (45%), puas dengan sistem insentif (47,4%), usia ≤35 tahun (37,9%), tidur kurang dari 7 jam (53,8%), status gizi berlebih (40%), dan ketakutan terhadap covid-19 yang ringan (40%).
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How this classification was reachedexpand
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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".