PENGARUH PEMBERIAN AIR REBUSAN DAUN SAMBUNG NYAWA TERHADAP PENURUNAN TEKANAN DARAH PADA PENDERITA HIPERTENSI DI WILAYAH KERJA PUSKESMAS BINANGA KECAMATAN BARUMUN TENGAH
Bibliographic record
Abstract
Hypertension cannot be cured but can be controlled so that it does not appear for a long time (years to decades) but still be watched out for. One of the medicinal plants that can be used as a herbal medicine for hypertension is the life-saving plant. The aim of this research is to determine the effect of giving boiled water from Sambung Nyawa leaves on reducing blood pressure in hypertension sufferers in the working area of the Binanga Community Health Center, Barumun Tengah District. This research design uses a quasi-experimental method. The population in this study were residents suffering from hypertension in the Binanga Community Health Center working area from January-December 2021, namely 198 people. The sampling technique in this research was a purposive sampling technique with a sample size of 22 people. The results of the research using the Wilcoxon statistical test showed that there was a significant influence between the effect of giving boiled water from splicing life leaves on reducing blood pressure in hypertension sufferers in the working area of the Binanga Community Health Center, Barumun Tengah District with a p-value = 0.000 (<0.05). The results of this study recommend that hypertension sufferers and their families are able to understand and comprehend the use of non-pharmacological therapy, namely boiled life-giving leaves as an alternative treatment for lowering blood pressure in hypertension sufferers. Keywords: life-giving leaves, blood pressure, hypertension
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".