PERANCANGAN MEDIA PROMKES IBU HAMIL BERBASIS INTERNET OF THINGS MENGGUNAKAN SERVER RASPBERRY PI 3 PADA DINAS KESEHATAN KOTA PALU
Bibliographic record
Abstract
WHO (World Health Organization) sebagai badan kesehatan dunia telah memperkirakan angka kematian ibu (maternal mortality rate) berkisar 300.000 orang. Sementara itu di Indonesia sendiri angka kematian ibu / AKI masih berada pada kisaran 305 kematian dari 100.000 kelahiran hidup. AKI di Kota Palu Provinsi Sulawesi Tengah sendiri terbilang sangat tinggi dan bisa dikatakan salah satu yang tertinggi di Indonesia, berdasarkan data profil kesehatan, AKI di Kota Palu berada pada angka 111 kematian dari 100.000 kelahiran hidup. Oleh karena itu dibutuhkan sebuah perancangan media komunikasi promosi kesehatan yang dapat membantu menurunkan AKI di Kota Palu, berbasis Internet of Things dengan menggunakan Rasppberry PI 3 sebagai server aplikasi sms reminder. Pengujian perancangan dilakukan terhadap 10 responden bagian promkes Dinas Kesehatan Kota Palu. Hasil pengujian menyatakan perancangan sudah sesuai dengan kebutuhan pengguna saat ini.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.109 | 0.046 |
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".