Peningkatan Kualitas Remaja dan Pencegahan Stunting melalui Program Remaja Sadar dan Kreatif Anti Pernikahan Dini di SMK Puspita Medika, Kelurahan Cilangkap, Kota Depok, Jawa Barat
Bibliographic record
Abstract
Permasalahan stunting masih menjadi perhatian dan salah satu penyebabnya adalah ketidaksiapan pasangan akibat menikah dini. Menurut data United Nations Children’s Fund (UNICEF) tahun 2023, Indonesia berada di posisi keempat dengan jumlah kasus pernikahan anak terbanyak di dunia yaitu sebanyak 25,53 juta kasus. Sementara itu, Indonesia membutuhkan remaja-remaja berkualitas dalam mewujudkan Indonesia Emas pada tahun 2045 mendatang. Tujuan dari program ini adalah untuk meningkatkan pengetahuan dan kesadaran diri remaja terhadap pentingnya pencegahan pernikahan dini melalui edukasi tahap perkembangan psikososial remaja dan pendewasaan usia perkawinan. Program ini melibatkan 37 remaja kelas XI dan XII di SMK Puspita Medika Kota Depok. Pelaksanaan program terdiri dari dua sesi. Sesi pertama yaitu edukasi mengenai tahap perkembangan psikososial remaja dan ancaman pergaulan bebas remaja, sementara sesi kedua membahas mengenai pendewasaan usia perkawinan dan perencanaan hidup remaja. Pengukuran keberhasilan dilakukan dengan pretest, post-test, dan Challenge terkait materi program. Hasil dari ketiga tes tersebut menunjukkan adanya peningkatan pengetahuan dan keterampilan remaja mengenai tahap perkembangan psikosial remaja dan pendewasaan usia perkawinan.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.063 | 0.009 |
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".