Pengaruh Latihan Scapular Postural Correction Terhadap Penurunan Nyeri Leher Pengguna Notebook Di \nUniversitas Muhammadiyah Surakarta \n \n
Bibliographic record
Abstract
“PENGARUH LATIHAN SCAPULAR POSTURAL CORRECTION TERHADAP PENURUNAN NYERI LEHER PENGGUNA NOTEBOOK DI UNIVERSITAS MUHAMMADIYAH SURAKARTA.” \n(Dibimbing oleh : Agus Widodo, SSt,FT, M.Fis dan Totok B.S, SSt.FT, MPH) \nNyeri leher adalah rasa nyeri yang meliputi kelainan saraf, tendon, otot dan ligamen di sekitar leher. Intervensi fisioterapi yang dilakukan adalah latihan Scapular Postural Correction. Tujuan penelitian ini adalah untuk mengetahui pengaruh pemberian latihan Scapular Postural Correction terhadap penurunan nyeri leher pengguna notebook di Kama FIK UMS. Tempat penelitian dilaksanakan di Kama FIK kampus I UMS selama 2 minggu. Penelitian ini menggunakan metode quasi eksperiment dengan desain Pre and Post Test with Control Group Design. Jumlah sampel pada penelitian ini adalah 20 responden 11 orang wanita dan 9 orang pria. Dan untuk mengukur nyeri leher menggunakan Visual Analog Scale (VAS). Uji normalitas data dengan shapiro wilk test didapat nilai P 0.313 (p > 0.05), berarti data berdistribusi normal. Uji pengaruh dengan paired sample t-test diketahui p 0,001 (p < 0,05), berarti data signifikan. Kesimpulan penelitian ini adalah ada pengaruh latihan Scapular Postural Correction terhadap penurunan nyeri leher pengguna notebook di UMS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.146 | 0.019 |
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".