Hubungan Merokok dan Pendidikan terhadap Fungsi Kognitif Civitas Akademika di Lingkungan Universitas Muhammadiyah Jakarta
Bibliographic record
Abstract
Perilaku merokok masih merupakan masalah kesehatan dunia karena dapat menyebabkan berbagai penyakit dan bahkan kematian. Salah satu kandungan rokok yaitu nikotin memiliki efek terhadap otak antara lain menyebabkan ketergantungan dan toksisitas pada fungsi kognitif. Tujuan penelitian ini untuk mengetahui hubungan merokok (derajat merokok dan ketergantungan nikotin) dan pendidikan terhadap fungsi kognitif di lingkungan Universitas Muhammadiyah Jakarta. Penelitian ini merupakan penelitian dengan desain studi cross sectional yang menggunakan kuesioner baku brinkman, fagerstorm dan Montreal Cognitive Assessment versi Indonesia (MoCA-Ina). Pengambilan sampel dilakukan dengan cara consecutive sampling dimana subjek yang sesuai dengan kriteria inklusi dimasukkan sampai jumlah yang diperlukan terpenuhi, jumlah sampel pada penelitian ini berjumlah 96 responden. Kriteria inklusi dalam penelitian ini adalah orang yang berusia 18-50 tahun dan memiliki kebiasaan merokok. Berdasarkan hasil uji Chi Square diketahui terdapat hubungan yang signifikan antara derajat merokok (p=0.024), ketergantungan nikotin (p=0.021), dan pendidikan (p=0.014) terhadap fungsi kognitif. Kata kunci: merokok, pendidikan, fungsi kognitif
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
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".