Pengembangan Permainan Edukasi Berbasis Kinect Bagi Penderita Asperger Syndrome Untuk Menangani Empathy Disorder
Bibliographic record
Abstract
Di Indonesia, penanganan empathy disorder pada penderita asperger syndrome masih belum disambut baik oleh para orang tua dikarenakan faktor biaya dan transportasi. Selain itu, penanganan empathy disorder pada penderita asperger syndrome diberikan perlakuan yang sama dengan klasifikasi Autism Spectrum Disorder (ASD) lainnya. Penelitian ini bertujuan untuk mengembangkan permainan edukasi berbasis Kinect yang dapat membantu seseorang dengan asperger syndrome dalam memahami perasaan orang lain, sehingga rasa empati terhadap sesama dapat tumbuh. Pada akhir tahun 2013 s.d 2014, Kinect dianggap feasible dalam menangani terapi dan rehabilitasi pada penderita penyakit syaraf dan Traumatic Brain Injury (TBI). Pada penelitian ini Kinect diterapkan ke dalam permainan edukasi yang mengandalkan pergerakan tangan kanan. Penelitian ini diujikan pada 5 penderita asperger syndrome dengan empathy disorder. Hasil dari penelitian ini tercapai setelah penderita asperger syndrome menggunakan permainan edukasi berbasis Kinect, yang menghasilkan kenaikan score pada tiap level dan emosi, serta penurunan total Toronto Empathy Questionnaire (TEQ) sebesar 12,8% dari rata-rata total TEQ sebelum penderita asperger syndrome menggunakan permainan edukasi berbasis Kinect.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".