FAKTOR YANG BERHUBUNGAN DENGAN IMUNISASI DASAR LENGKAP DI WILAYAH KERJA PUSKESMAS KOTO TINGGI KABUPATEN LIMA PULUH KOTA TAHUN 2023
Bibliographic record
Abstract
Tujuan Penelitian: Cakupan imunisasi dasar lengkap di Puskesmas Koto Tinggi Kabupaten Lima Puluh Kota belum mencapai target yaitu 18,68% dari target nasional 94%. Penelitian ini bertujuan untuk mengetahui faktor yang berhubungan dengan imunisasi dasar lengkap di wilayah kerja Puskesmas Koto Tinggi Kabupaten Lima Puluh Kota. Metode: Jenis penelitian adalah kuantitatif, pada bulan Juni-Agustus 2023, rancangan penelitian studi cross sectional, sampel 76 responden di wilayah kerja Puskesmas Koto Tinggi. Analisis data dilakukan secara univariat, hingga multivariat. Hasil: didapatkan bahwa 61,8% ibu tidak memberikan imunisasi dasar lengkap, 44,7% berpengetahuan rendah, 39,5% bersikap negatif, 31,6% berpendidikan rendah, 75% tidak bekerja, 75% sedikit anak, 57,9% kesulitan menjangkau pelayanan kesehatan, 55,3% tidak didukung keluarga, 41,8% tidak didukung tenaga kesehatan, 56,6% kurang terpapar informasi. Diperoleh p-value pengetahuan (0,000), sikap (0,001), pendidikan (0,400), status pekerjaan (0,340), jumlah anak (0,892), keterjangkauan pelayanan kesehatan (0,890), dukungan keluarga (0,000), dukungan tenaga kesehatan (0,263), dan paparan informasi (0,000). Variabel yang paling dominan berpengaruh terhadap imunisasi dasar lengkap adalah dukungan keluarga (p-value 0,000 dan POR = 20,344). Kesimpulan: Pengetahuan, sikap, dukungan keluarga, dan paparan informasi berhubungan dengan imunisasi dasar lengkap. Untuk meningkatkan cakupan imunisasi dasar lengkap, Puskesmas dapat menyediakan taman baca sebagai bahan bacaan dan media informasi akan pentingnya imunisasi dasar.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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.
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".