ANALISIS PERILAKU POLA MAKAN PENDERITA DIABETES MELLITUS TIPE II DI WILAYAH KERJA UPTD PUSKESMAS KAWALI TAHUN 2021 (Implementasi teori Health Believe Model)
Bibliographic record
Abstract
Wilayah Asia Tenggara menempati peringkat ke-3 dengan prevalensi sebesar 11,3% dengan Indonesia sendiri berada diperingkat ke-7 diantara 10 negera dengan jumlah penderita Diabetes Mellitus terbanyak, yaitu sebesar 10,7 juta. Salah satu faktor masalah pada penanggulangan DM adalah ketidaktahuan penderita Diabetes Mellitus terkait pola makan yang dapat menyebabkan peningkatan kadar gula dalam darah. Tujuan: Untuk menganalisis serta mengetahui bagaimana perilaku pola makan penderita Diabetes Mellitus tipe II di Wilayah Kerja UPTD Puskesmas Kawali. Metode: Metode yang digunakandalam penelitian ini adalah metode kualitatif deskriptif. Peneliti menggunakan 12 informan yang terdiri dari 5 orang penderita DM, 5 orang keluarga penderita DM dan 2 orang Tenaga Kesehatan UPTD Puskesmas Kawali. Teknik pengumpulan data dilakukan dengan cara wawancara mandalam. Hasil: Pola Makan penderita DM di Wilayah Kerja UPTD Puskesmas Kawali belum sepenuhnya sesuai dengan prinsip pola makan 3J. Perceived Barriers penderita DM cenderung tinggi jika melakukan pola makan sesuai dengan prinsip 3J. Cues to Action penderita DM sebagian diperoleh dari dukungan keluarga terdekat.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".