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Record W2618098233

HUBUNGAN CORE STABILITY DAN POWER, SPEED SERTA AGILITY PADA PEMAIN BASKET USIA 15-16 TAHUN

2016· article· id· W2618098233 on OpenAlexaboutno aff
Nining Wijayanti

Bibliographic record

VenueFisioterapi : Jurnal Ilmiah Fisioterapi · 2016
Typearticle
Languageid
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsDashBasketballCore stabilityJumpStatisticsPhysical therapyMedicineComputer sciencePhysicsGeography
DOInot available

Abstract

fetched live from OpenAlex

Abstract Objective: Determine relationship of core stability and power, speed and also agility in basketball players aged 15-16 years. Methods : This study is a non-experimental research in the form of correlation studies to analyze the relationship between variables. Sample consisted of 37 basketball players aged 15-16 years in SMAN 112, SMAN 78 and Cakrawala basketball club Jakarta. Samples are given a series of tests consisting of McGill's Procedure, vertical jump test, 40 yards dash test and t-run agility test. Results: Result from McGill’s Prosedure mean±SD= 369,60±139,24, vertical jump test 50,38±8,15, 40 yards dash test 5,32±0,44 and t-run agility test 10,58±0,88. Result from Kolmogorov-Smirnov test showed that all of data are normally distributed. Result from correlation test using Pearson product moment showed that relationship between core stability-power r= 0,436, core stability-speed r= -0,341 and core stability-agility r= -0,514. Result from hypothesis test using T-test showed that core stability-power t hitung = 2,866, core stability-speed t hitung = 2,1460 dan core stability-agility t hitung = 3,544. Value of t hitung are compared to t table and showed that t hitung > t tabel (1,687), it means there is any relationship between each variable. Conclusion : There is a relationship between core stability and power, speed and also agility in 15-16 years old basketball players. Keywords : core stability, power, speed, agility, basketball player. Abstrak Tujuan: Mengetahui hubungan core stability dan power, speed serta agility pada pemain basket usia 15-16 tahun. Metode: Penelitian ini merupakan jenis penelitian non eksperimental berupa studi korelasi untuk menganalisa hubungan antar variabel. Sampel penelitian terdiri dari 37 orang pemain basketusia 15-16 tahun yang berasal dari kelompok basket SMAN 112, SMAN 78 dan klub Cakrawala Jakarta. Sampel diberikan serangkaian pengukuran berupa McGill’s procedure , vertical jump test , 40 yards dash test dan t-run agility test . Hasil: Hasil pengukuran McGill’s Procedure diperoleh data berupa mean±SD = 369,60±139,24, vertical jump test 50,38±8,15, 40 yards dash test 5,32±0,44 dan t-run agility test 10,58±0,88. Hasil uji normalitas dengan Kolmogorov-Smirnov test didapatkan seluruh data berdistribusi normal. Hasil uji korelasi dengan Pearson product moment test didapatkan hasil untuk hubungan core stability-power r= 0,436, core stability-speed r= -0,341 dan core stability-agility r= -0,514. Hasil uji hipotesis dengan uji T didapatkan hasil untuk hubungan core stability-power t hitung = 2,866, core stability- speed t hitung = 2,1460 dan core stability-agility t hitung = 3,544. Nilai t hitung dibandingkan dengan nilai t tabel, hasil perbandingan menunjukkan seluruh hasil t hitung > t tabel (1,687) yang berarti terdapat korelasi antar variabel. Kesimpulan: Terdapat hubungan antara core stability dan power, speed serta agility pada pemain basket usia 15-16 tahun. Kata Kunci : core stability, power, speed, agility, pemain basket.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.002

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.

Opus teacher head0.085
GPT teacher head0.409
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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