HUBUNGAN TINGKAT PENGETAHUAN DAN POLA KONSUMSI NATRIUM DENGAN TEKANAN DARAH PADA PENDERITA HIPERTENSI DI WILAYAH KERJA PUSKESMAS CEMPAKA
Bibliographic record
Abstract
Pendahuluan: Pola konsumsi natrium dan tingkat pengetahuan adalah salah satu faktor yang mempengaruhi tejadinya peningkatan tekanan darah. Di Puskesmas Cempaka hipertensi menduduki peringkat pertama penyakit terbanyak. Tujuan: Penelitian ini bertujuan untuk mengetahui hubungan tingkat pengetahuan dan pola konsumsi natrium dengan tekanan darah pada penderita hipertensidi wilayah kerja Puskesmas Cempaka tahun 2021. Penelitian ini menggunakan Metode: analitik korelasional dengan pendekatan cross sectional, Jumlah populasi 764 orang dan sampel 88 orang. Teknik pengambilan purposive sampling. Variabel bebas (tingkat pengetahuan dan pola konsumsi natrium) dan variabel terikat (tekanan darah pada penderita hipertensi). Instrumen berupa angket. Uji yang digunakan Rank Spearman. Hasil: Mayoritas tekanan darah menunjukkan hipertensi stage 2 (TD 160-180 mmHg) sebanyak 65,9%, berpengetahuan kurang sebanyak 54,5% dan pola konsumsi natrium kurang baik sebanyak 67,0%. Kesimpulan: ada hubungan yang bermakna antara pengetahuan dan pola konsumsi natrium dengan tekanan darah pada penderita hipertensi. Saran: Direkomendasikan kepada tenaga kesehatan dan puskesmas dapat memberikan informasi sebagai pengetahuan bagi penderita hipertensi tentang hipertensi dan pola konsumsi natrium guna meminimalisir dan menghindari terjadinya komplikasi.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".