Hubungan Karakteristik Asal Sekolah Dengan Prestasi Belajar Mahasiswa/I Semester I Di Prodi Ilmu Keperawatan Dan Ners Fakultas Ilmu Kesehatan Universitas Katolik Musi Charitas Palembang
Bibliographic record
Abstract
Background: Education is a planned effort to realize a learning process that is useful for the development of his potential to have personality, self-control, intelligence, and skills. Education consists of the status of private and public schools that have the same rights and obligations, the same study time and have the same disciplinary knowledge, put together into one particular subject such as Natural Sciences, Social Sciences, Languages, Mathematics. The quality of an education can also affect student learning achievement where learning achievement is the result of a learning gained by someone from an assessment and evaluation. \nObjective: This study aims to determine the relationship between the characteristics of the school's origin and the semester 1 student achievement at the Nursing Science Study Program and Nurses at the Catholic University of Musi Charitas Palembang. \nMethod: This research method uses analytical survey with a retrospective approach using 2 types of Chi Square and Kendall Tau tests with significance limits of α <0.05, questionnaires used and samples in this study Level I and Level II students of FIKes Nursing Science Study Program Palembang UKMC totaling 99 people. The sampling technique uses total sampling \nResults: Based on the Chi Square test analysis there was no relationship between the origin of the school and the learning achievement p value 0.187 there was no relationship between the majors and the learning achievement p value 0.190. Based on the analysis of the Kendall Tau test there was no relationship between accreditation and learning achievement p value 0.374. \nSuggestion: Diharapkan bagi mahasiswa agar lebih giat meningkatkan semangat belajar yang lebih tinggi agar mendapatkan prestasi yang lebih baik lagi, meskipun berasal dari asal sekolah yang berbeda.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".