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Record W2620838701

PERANCANGAN MEDIA PROMKES IBU HAMIL BERBASIS INTERNET OF THINGS MENGGUNAKAN SERVER RASPBERRY PI 3 PADA DINAS KESEHATAN KOTA PALU

2017· article· id· W2620838701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSEMNASTEKNOMEDIA ONLINE · 2017
Typearticle
Languageid
FieldComputer Science
TopicInformation Retrieval and Data Mining
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.006
Open science0.0050.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.262
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it