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PERSEPSI SISWA TERHADAP PEMBELAJARAN REMEDIAL PADA MATA PELAJARAN EKONOMI DI SMA NEGERI 1 TANAH PUTIH

2021· article· id· W4323647147 on OpenAlexaff
Nureni Ramadiana, Nurhuda

Bibliographic record

VenuePEKA · 2021
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Penelitian ini dilakukan dengan tujuan untuk mengetahui persepsi siswa terhadap pembelajaran remedial pada mata pelajaran ekonomi kelas X di SMA Negeri 1 Tanah Putih tahun ajaran 2018/2019. Penelitian ini dilaksanakan di SMA Negeri 1 Tanah putih pada bulan Maret 2019, subjek penelitian ini adalah guru ekonomi dan siswa kelas X jurusan MIPA di SMA Negeri 1 Tanah Putih sebanyak 42 orang. Pengumpulan data dalam penelitian ini menggunakan angket dan wawancara. Angket terdiri dari 36 pernyataan dan siswa menjawab bentuk tes ulang yang terdiri dari 7 butir pertanyaan. Berdasarkan analisis deskriptif tes ulang mengenai persepsi siswa terhadap pembelajaran remedial pada mata pelajaran ekonomi yang menjawab sangat setuju 138 responden, setuju 84 responden, kurang setuju 37 responden, tidak setuju 34 responden. Berdasarkan analisis data, maka disimpulkan bahwa skor rata-rata tentang tes ulang yaitu 1,37 dengan kategori sangat rendah.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.006

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 head0.045
GPT teacher head0.304
Teacher spread0.259 · 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
Published2021
Admission routes1
Has abstractyes

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