The Evaluation of Fiscal Decentralization in Indonesia Based on the Degree of Regional Autonomy
Bibliographic record
Abstract
This study was to determine the improvement of students' cognitive aspects with the Kibar method of BTHQ learning at SD Muhammadiyah Karangkajen. The design of this research is qualitative, with a qualitative descriptive approach. The subjects of this study were grade 1 students of SD Muhammadiyah Karangkajen. The results showed that BTHQ activities: 1) provide knowledge, 2) understanding and good reading methods using makharijul letters, 3) providing advice or motivation so that children take BTHQ on time, 4) providing educational punishments for students, 5) conduct an evaluation after the BTHQ activity. This case study focuses on the BTHQ learning curriculum carried out by tutors/teachers through the kibar method for students at SD Muhamadiyah Karangkajen. This case study shows that, with the BTHQ learning curriculum by competent tutors/teachers, it can improve the cognitive aspects of children/students, as a basis for understanding PAI family learning. This study contributes to the ease of learning with the children's BTHQ curriculum through the waving method. In addition, this study recommends that teachers apply this method to improve the cognitive aspects of BTHQ through supportive learning innovations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".