EVALUASI PELAKSANAAN PROGRAM PEMBERANTASAN DBD (Studi Di Wilayah Puskesmas Putat Jaya Kecamatan Sawahan Kota Surabaya Tahun 2016)
Bibliographic record
Abstract
ABSTRACTDengue Haemarogic Fever (DHF) is most popular disease in this society, this disease may attack all peopleand result in death in relatively short time. In 2015, number of cases in Putat Jaya local government clinic districtSawahan Surabaya City in January-September are 42. Dengue Haemorogic fever control program should be doneby all people, not only Public Health Office, clinic but also all people, because Dengue Fever can be reduced byDengue Fever eradication. Aim of this research is evaluating the implementation of dengue haemorhagic fevercontrol program in local government clinic Putat Jaya District Sawahan in 2016.This is descriptive research, data was collected by interview and document tracking. Sample is from healthworkers and the people which was taken randomly as many as 30 people and analyzed descriptively.Based on research result, eradication activities, larvicides routine inspection, periodic inspection of larva.Aedes aegypti mosquito control have been done although it has not been thoroughly, while fogging activities infocus area has already been implemented. Number of mosquito-free for the last 3 years ≤ 95%, and not inaccordance with the requirements.Suggestions for sanitarian Putat Jaya to provide, watch, supervise and nurture a cadre of locals to carry outtheir duties and responsibilities, and to society more active in conducting control of dengue haemorogic fever,because to get the expected results, activities to eradicate dengue haemorigic fever must be donesimultaneously and continously.Keywords : Evaluation Control Program and Dengue Haemorigic Fever
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".