LATIHAN KOORDINASI LARI DENGAN BILAH TERHADAP PENINGKATAN TEKNIK LARI PADA SISWA KELAS V SD N EGERI 2 KENDAGA KECAMATAN BANJARMANGU KABUPATEN BANJARNEGARA
Bibliographic record
Abstract
Tujuan penelitian ini adalah untuk mengetahui latihan koordinasi lari \ndengan bilah terhadap kemampuan teknik lari pada siswa kelas V SD Negeri 2 \nKendaga Kecamatan Banjarmangu Kabupaten Banjarnegara. \nPenelitian ini menggunakan eksperimen semu, dengan \none group pretest \nposttest design . Subjek penelitian berjumlah 11 siswa kelas V SD Negeri 2 \nKendaga Kecamatan Banjarmangu Kabupaten Banjarnegara. Instrumen d alam \npenelitian ini adalah tes kemampuan teknik lari. Teknik analisis data \nmenggunakan uji hipotesis dengan anlisis uji t ( paired sample t test ), yaitu dengan \nmembandingkan nilai pretest dan posttest dengan sampel yang sama. \nHasil \npenelitian menunjukan b ahwa tes kemampuan teknik lari memiliki \nvaliditas sebesar r = 0.402 dan memiliki realibilitas sebesar = 0.912. Hasil uji t \ndiperoleh selisih peningkatan antara 4.907 sampai 3.457 pada taraf siginifikasi \n0,05%. Hasil peningkatan presentase sebesar 16.72%. Dengan demikian dapat \ndisimpulkan bahwa ada pengaruh yang signifikan latihan koordinasi lari dengan \nbilah terhadap kemampuan teknik lari siswa kelas V SD Negeri 2 Kendaga \nKecamatan Banjarmangu Kabupaten Banjarnegara.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.007 |
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".