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Record W4313909649 · doi:10.37306/kkb.v7i2.104

DETERMINAN PARTISIPASI PROGRAM KAMPUNG KB PADA WANITA USIA SUBUR DI KABUPATEN BANYUMAS

2022· article· id· W4313909649 on OpenAlexaff
Colti Sistiarani, Bambang Hariyadi, Eri Wahyuningsih

Bibliographic record

VenueJurnal Keluarga Berencana · 2022
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicFood Security and Socioeconomic Dynamics
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePsychologyArt

Abstract

fetched live from OpenAlex

Program kampung Keluarga Berkualitas (KB) merupakan program pemerintah yang dilaksanakan dalam upaya pencapaian Program Kependudukan, Keluarga Berencana, dan Pembangunan Keluarga. Pelaksanaan kampung KB di Kabupaten Banyumas telah diinisiasi di wilayah Desa Sumbang dan Kelurahan Karangpucung. Kegiatan kampung KB salah satunya adalah pelibatan khalayak sasaran yaitu Wanita Usia Subur (WUS). Tujuan penelitian ini yaitu mengidentifikasi faktor yang berpengaruh terhadap partisipasi program kampung KB. Populasi dalam penelitian ini yaitu Wanita Usia Subur di Kabupaten Banyumas. Sampel yang diambil dalam penelitian ini sebanyak 71 orang. Pengumpulan data dilakukan melalui wawancara dengan menggunakan kuesioner. Analisis data dalam penelitian ini menggunakan uji regresi logistik. Hasil penelitian dapat dijelaskan bahwa ada pengaruh antara sikap pelaksanaan kampung KB, dukungan suami dan akses kegiatan kampung KB terhadap partisipasi program kampung KB, serta tidak ada pengaruh antara pengetahuan tentang kampung KB. Simpulan dalam penelitian ini yaitu faktor yang paling berpengaruh dalam penelitian ini yaitu sikap pelaksanaan kampung KB. Rekomendasi penelitian ini yaitu pentingnya pendekatan program dalam faktor terkait dalam upaya peningkatan partisipasi program kampung KB.

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)0.002
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 score0.023
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.005

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 head0.022
GPT teacher head0.239
Teacher spread0.217 · 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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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