Hubungan Kebugaran Fisik dengan Fungsi Kognitif pada Mahasiswi Penghafal Al-Qur'an di Kota Malang
Bibliographic record
Abstract
Pendahuluan: Mahasiswi memerlukan kebugaran fisik yang cukup untuk dapat berpikir dan menggunakan kemampuan kognitifnya secara maksimal agar tidak cepat lelah setelah melakukan aktivitas padat seperti kuliah dan menghafal Al-Qur’an. Kegiatan ini juga memerlukan keterampilan berpikir yang berkaitan dengan fungsi kognitif. Kebugaran fisik yang baik akan peningkatan kadar protein Brain-Derived Neutrophic Factor (BDNF) yang berfungsi untuk menstimulasi sel-sel saraf otak guna meningkatkan kemampuan kognitif. Penelitian berkeinginan untuk memahami hubungan tingkat kebugaran fisik dengan fungsi kognitif terhadap mahasiswi di Pondok Pesantren Nurul Furqon Kota Malang sebagai penghafal Alqur’an. Metode: Dalam penilitian akan menggunakan pendekatan analitik observasional dengan cross-sectional study sebanyak 30 responden diperoleh dengan teknik purposive sampling. Data diambil menggunakan YMCA Step Test dan MoCA-Ina (Montreal Cognitive Assessment). Selanjutnya pengolahan data menggunakan metode uji Fisher’s Exact Test. Hasil: Perolehan dari uji statistic menghasilkan p value sebesar 0,029 < 0,05. Kesimpulan: Terdapat hubungan antara tingkat kebugaran fisik dengan fungsi kognitif pada Mahasiswi Penghafal Al-Qur’an di Kota Malang.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".