HUBUNGAN KUALITAS PERTEMANAN DAN KONTROLDIRI DENGAN KECANDUAN SMARTPHONE PADA REMAJA
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menguji tiga hipotesis: (1) Terdapat hubungan negatif antara kualitas pertemanan dan kontrol diri dengan kecanduan smartphone (Smartphone addiction), (2) Terdapat hubungan negatif antara kualitas pertemanan dan kecanduan smartphone (Smartphone addiction), dan (3) Terdapat hubungan negatif antara kontrol diri dan kecanduan smartphone (Smartphone addiction). Subjek penelitian ini adalah 225 remaja (N=225). Data dianalisis menggunakan metode kuantitatif dengan uji korelasi non-parametrik Spearman’s rho, karena asumsi normalitas tidak terpenuhi.. Instrumen yang digunakan adalah Smartphone Addiction Scale-Short Version (SAS-SV), McGill Friendship Questionnaire–Friendship Function (MFQ-FF), dan Brief Self-Control Scale (BSCS). Hasil analisis menunjukkan bahwa Hipotesis 3 diterima; ditemukan adanya hubungan negatif yang signifikan antara Kontrol Diri dengan Kecanduan Smartphone (ρ=−0.428,p=0.000). Sebaliknya, Hipotesis 2 ditolak karena Kualitas Pertemanan tidak memiliki hubungan yang signifikan dengan Kecanduan Smartphone (ρ=0.009,p=0.449). Secara simultan, Hipotesis 1 diterima secara parsial karena hanya Kontrol Diri yang signifikan, dengan kontribusi variabel dominan dalam menjelaskan variasi Kecanduan Smartphone sebesar 23.3%. Temuan ini menunjukkan bahwa kontrol diri merupakan faktor penting dalam mencegah kecanduan smartphone pada remaja. Penelitian ini memberikan implikasi pada pentingnya pelatihan regulasi diri dalam upaya pencegahan kecanduan teknologi. Kata kunci: kecanduan smartphone, kontrol diri, kualitas pertemanan, remaja
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".