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Record W2888106088 · doi:10.34310/sjkb.v5i1.152

ANALISA DETERMINAN PEMILIHAN ALAT KONTRASEPSI INTRA UTERI DEVICE (IUD)

2018· article· id· W2888106088 on OpenAlexaff
Murti Wuryani, Dewi Ratna

Bibliographic record

VenueJurnal SMART Kebidanan · 2018
Typearticle
Languageid
FieldHealth Professions
TopicHealthcare Quality and Satisfaction
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsGynecologyMedicine

Abstract

fetched live from OpenAlex

Salah satu strategi dari pelaksanaan program KB sendiri seperti tercantum dalam rencana pembangunan jangka menengah (RPJM) tahun 2004-2009 adalah meningkatnya penggunaan metode kontrasepsi jangka panjang (MKJP) seperti IUD (Intra Uterine Device), implan susuk dan sterilisasi. Di Indonesia pada tahun 2016 kontrasepsi yang paling tinggi digunakan adalah suntik sebanyak 53,9%, dan IUD kontrasepsi terendah sebanyak 6,6% (BKKBN, 2016). Tujuan penelitian adalah untuk mengetahui faktor yang berhubungan dengan pemilihan alat kontrasepsi IUD di Wilayah Kerja Puskesmas Uepai Kabupaten Konawe. Metode penelitian dengan pendekatan kuantitatif menggunakan rancangan cross sectional. Sampel dalam penelitian ini adalah sebagian dari Pasangan Usia Subur (PUS), yang sudah menikah dan masih aktif menjadi Akseptor KB (IUD dan Non IUD) yang tinggal di Wilayah Kerja UPTD Puskesmas Uepai Kabupaten Konawe tahun 2018 berjumlah 94 sampel, instrument yang digunakan adalah kuesioner, hasil penelitian di analisa menggunakan chi-square. Hasil penelitian menunjukkan ada hubungan pengetahuan, pendidikan, sarana dan prasarana, sumber informasi, dukungan keluarga dan dukungan tenaga kesehatan dengan pemilihan alat kontrasepsi IUD dengan nilai p value masing-masing variabel < 0.05. Kesimpulan dalam penelitian faktor yang berhubungan dengan pemilihan alkon IUD adalah pengetahuan, pendidikan, sarana dan prasarana, sumber informasi, dukungan keluarga dan dukungan tenaga kesehatan. Kata Kunci : Alat kontrasepsi; IUD

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.006

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 head0.099
GPT teacher head0.433
Teacher spread0.334 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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