HUBUNGAN TIPE KEPRIBADIAN DENGAN KEJADIAN \nGANGGUAN JIWA PADA KELUARGA DI DESA \nBANARAN GALUR KULON PROGO \nYOGYAKARTA
Bibliographic record
Abstract
Latar belakang : Faktor tipe kepribadian merupakan salah satu faktor yang \nberkontribusi terjadinya gangguan jiwa. Kegagalan seorang indvidu dalam \nmelakukan penyesuaian dengan persoalan yang dihadapinya dalam jangka panjang \nakan mengakibatkan terjadinya gangguan jiwa pada individu tersebut. \nTujuan : Untuk mengetahui hubungan tipe kepribadian dengan kejadian gangguan \njiwa pada keluarga di Desa Banaran Galur Kulon Progo Yogyakarta. \nMetode penelitian : Penelitian ini merupakan penelitian case control atau kasus \nkontrol dengan menggunakan pendekatan waktu retsospektif. Cara pengambilan \nsample dengan cara consecutive sampling yaitu 86 responden dengan rincian subyek \npada kelompok gangguan jiwa yaitu 28 orang dan subyek pada kelompok tidak \ngangguan jiwa sebanyak 58 orang. Analisis data menggunakan uji Chi-Square. \nHasil : Ada hubungan signifikan antara faktor tipe kepribadian dengan kejadian \nganguan jiwa di Desa Banaran Galur Kulon Progo Yogyakarta. Dengan taraf \nsignifikan P = 0,000 (p < 0,05). Tipe kepribadian introvert memiliki 6 kali lebih \nbesar untuk mengalami gangguan jiwa (OR = 6.667). \nSaran : Bagi Penanggung Jawab Program Kesehatan Jiwa Puskesmas Galur II perlu \nuntuk mengadakan kegiatan sosialisasi atau penyuluhan terkait tipe kepribadian dan \ngangguan jiwa. \nKata kunci : Tipe kepribadian, kejadian, gangguan jiwa. \nReferensi : 20 buku (2001-2012), 3 skripsi, 2 jurnal, 3 web \nHalaman : xiii, 49 halaman, 6 tabel, 3 gambar, 13 lampiran
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".