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Record W4385585499 · doi:10.33143/jhtm.v9i1.2977

Gambaran Pelaksanaan Surveilans HIV di Dinas Kesehatan Provinsi Jawa Timur Tahun 2017

2023· article· id· W4385585499 on OpenAlexaff
Eva Flourentina Kusumawardani, Meutia Paradhiba, Mardi Fadillah, Onetusfifsi Putra, Firman Firdauz Saputra, Perry Boy Chandra Siahaan, Rubi Rimonda, Laila Apriani Hasanah Harahap, Nasrianti Syam

Bibliographic record

VenueJOURNAL OF HEALTHCARE TECHNOLOGY AND MEDICINE · 2023
Typearticle
Languageid
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)MedicineFamily medicine

Abstract

fetched live from OpenAlex

Kasus HIV/AIDS terdapat hampir di semua negara di dunia tak terkecuali Indonesia. Penyakit ini telah menulari seluruh lapisan masyarakat termasuk bayi dan anak-anak. Perlu adanya kegiatan surveilans rutin untuk melakukan pencatatan dan pelaporan sehingga dapat memonitoring jumlah kasus pada periode waktu tertentu. Kegiatan surveilans HIV merupakan salah satu cara efektif untuk mengontrol penyebaran kasus HIV/AIDS. Tujuan penelitian: untuk memberikan gambaran evaluasi sistem surveilans HIV berdasarkan komponen sistem dan atribut surveilans di Dinas Kesehatan Provinsi Jawa Timur. Metode penelitian: jenis penelitian ini merupakan penelitian kualitatif dengan rancangan studi evaluasi. Pengumpulan data dilakukan dengan metode wawancara kepada petugas surveilans HIV di Dinas Kesehatan Provinsi Jawa Timur sejumlah 3 orang menggunakan kuesioner. Hasil penelitian: berdasarkan komponen sistem surveilans 66,7% petugas surveilans HIV memiliki tingkat Pendidikan S1 Kesehatan Masyarakat peminatan epidemiologi dan 33,3% adalah S2 Kesehatan Masyarakat. Pengumpulan, pengisian formulir hingga alur pelaporan dianggap mudah, dan tidak mengalami keterlambatan dalam proses input data ke aplikasi SIHA. Proses analisis hanya dilakukan ditingkat Dinas Kesehatan, sedangkan ditingkat Puskesmas tidak. Sistem surveilans HIV di Kabupaten/Kota di wilayah kerja Dinas Kesehatan Provinsi Jawa Timur masih memerlukan perbaikan dalam analisis, ketersediaan pedoman surveilans HIV, dan perlunya peningkatan pengetahuan petugas terkait surveilans HIV.Kata Kunci: Surveilans, HIV/AIDS, Komponen, SistemHIV/AIDS cases exist in almost every country worldwide, including Indonesia. This disease has affected all segments of society, including infants and children. Regular surveillance activities are needed to record and report cases, enabling the monitoring of the number of cases over specific periods of time. HIV surveillance is an effective method to control the spread of HIV/AIDS cases. The aim of this study was to provide an evaluation of the HIV surveillance system based on its components and surveillance attributes in the East Java Provincial Health Office. This qualitative study employed an evaluation study design. Data collection involved interviews with three HIV surveillance officers in the East Java Provincial Health Office, using a questionnaire. The results of the study revealed that 66.7% of the HIV surveillance officers possessed a bachelor's degree in Public Health with a specialization in epidemiology, while 33.3% held a master's degree in Public Health. The data collection, form completion, and reporting processes were considered easy, with no delays in inputting data into the SIHA application. The analysis process was only conducted at the Provincial Health Office level and not at the Primary Health Center level. The HIV surveillance system in the districts and cities within the jurisdiction of the East Java Provincial Health Office still requires improvement in terms of analysis, availability of HIV surveillance guidelines, and the need for increased knowledge among surveillance officers regarding HIV surveillance..Keywords: Surveillance, HIV/AIDS, Components, Systems

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 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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.060
GPT teacher head0.389
Teacher spread0.329 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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