PARTISIPASI PASANGAN USIA SUBUR DALAM PELAKSANAAN PROGRAM KAMPUNG KELUARGA BERENCANA DI DESA PULAU KERASIAN KABUPATEN KOTABARU
Bibliographic record
Abstract
Tujuan penelitian ini adalah untuk mengetahui penyebab rendahnya partisipasi partisipasi pasangan usia subur dalam pelaksanaan program KB Kampung di Desa Pulau Kokasian Kecamatan Laut Kepulauan Kabupaten Kotabaru. Kemudian diuraikan dan dianalisis dari determinan keberhasilan implementasi implementasi kebijakan publik menurut Edward III yaitu komunikasi, sumber daya, disposisi, struktur birokrasi untuk mencapai tujuan penelitian peneliti menggunakan metode kuantitatif, dengan analisis deskriptif. Variabel yang digunakan adalah komunikasi, sumber daya, disposisi, dan struktur birokrasi. Hasil penelitian dari 37 pertanyaan dianalisis menggunakan analisis parsial yang ditabulasi dan frekuensi menghasilkan analisis pengaruh komunikasi sebesar 33%, sumber daya sebesar 47%, disposisi sebesar 36%, struktur birokrasi sebesar 32%. Kesimpulannya, penyebab paling dominan rendahnya partisipasi pasangan usia subur dalam pelaksanaan program Desa Keluarga Berencana adalah Sumberdaya karena memiliki pengaruh sebesar 47% terhadap rendahnya partisipasi pasangan usia subur dalam pelaksanaan KB Desa. Program di Desa Pulau Kerasian, Kecamatan Pulau Laut Kepulauan, Kabupaten Kotabaru.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.004 |
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".