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Record W2527925720 · doi:10.21831/medikora.v15i2.23144

PENGEMBANGAN MODEL BODY WEIGHT TRAINING UNTUK LATIHAN OTOT PERUT

2019· article· id· W2527925720 on OpenAlexaff
Bayu Aji Laksono, Widiyanto Widiyanto

Bibliographic record

VenueMEDIKORA · 2019
Typearticle
Languageid
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsPhysicsMedicineBody weightGynecologyInternal medicine

Abstract

fetched live from OpenAlex

Kurangnya pengetahuan tentang model/variasi latihan body weight menyebabkan members fitness/pelaku olahraga pada saat melakukan latihan beban terkesan monoton, kurang bervariasi dan membosankan. Tujuan penelitian ini adalah untuk mengembangkan model body weight training untuk latihan otot perut, yang nantinya dapat menjadi panduan untuk latihan otot perut dan diharapkan dapat mempercepat pembentukan otot perut menjadi sixspack. Model-model body weight training lebih menekankan pada spesifikasi bagian otot perut. Penelitian ini merupakan penelitian pengembangan model dengan langkah-langkah penelitiannya sebagai berikut: (1) mengenali potensi dan masalah, (2) pengumpulan data, (3) desain produk, (4) validasi desain, (5) revisi desain, (6) uji coba produk, (7) revisi produk, (8) uji coba pemakaian, (9) revisi produk, dan (10) produk masal. Validasi draf model latihan dilakukan oleh tiga ahli/pakar materi tentang kebugaran fisik. Sampel penelitian dalam uji coba skala kecil berjumlah 5 responden dan uji coba skala besar berjumlah 20 responden. Penelitian dilakukan di Club Arena International Hotel Pandanaran, Hotel Jambuluwuk, dan Hotel Ros In. Teknik analisis data menggunakan data kualitatif dan kuantitatif. Data kualitatif diperoleh dari: (1) hasil wawancara dengan members fitness center, (2) catatan lapangan, dan (3) data saran perbaikan draf model awal dan hasil observasi pada pelaksanaan uji coba dengan skala kecil dan besar. Data kuantitatif diperoleh dari: (1) penilaian skala nilai validasi draf model, (2) penilaian skala nilai observasi pelaksanaan model, dan (3) hasil penilaian kuesioner uji coba skala kecil dan besar dari responden. Hasil yang diperoleh dari data validasi draf model dan observasi pelaksanaan model latihan oleh ahli/pakar 100 % baik sekali. Hasil penilaian kuesioner uji coba skala kecil 80 % baik sekali dan 20 % baik, sedangkan untuk hasil kuesioner uji coba skala besar 60 % baik sekali dan 40 % baik. Berdasarkan hasil tersebut dapat diartikan bahwa model body weight training untuk latihan otot perut layak untuk digunakan.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.006

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 head0.103
GPT teacher head0.431
Teacher spread0.328 · 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 designBench or experimental
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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Citations5
Published2019
Admission routes1
Has abstractyes

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