EVALUASI KAPABILITAS AUDIT INTERNAL PADA PERWAKILAN BPKP PROVINSI KALIMANTAN TIMUR
Bibliographic record
Abstract
This study aims to determine (1) To know the understanding of the enhancement of APIP capability by using Internal Audit Capability Model (IA-CM) (2) To know the internal audit capability level at the BPKP Representative of East Kalimantan Province and the efforts to be taken to improve and maintain it. This research was conducted at BPKP Representative of East Kalimantan Province. Period assessed by the author's internal audit capability is the period of 2016.This research is conducted by field research and literature research by reading the literature related to the problem under study. The data used to evaluate internal audit capability at BPKP Representative of East Kalimantan Province is data of internal audit capability condition of BPKP Representative of East Kalimantan Province. The analytical tool used in this research is Head of BPKP Regulation No. 16 of 2015 on Technical Guidelines for Capacity Improvement of Government Internal Supervisory Apparatus.The result of this research is internal audit capability of BPKP Representative of East Kalimantan Province on elements of Role and Service, Professional Practice, Accountability and Performance Management, Organizational Relations and Culture, The Governance Structure is at level 3 (integrated), while the element of Human Resource Management is at level 2 (infrastructure). Based on the evaluation of the six elements, the internal audit capability of BPKP Representative of East Kalimantan Province is at level 3 (integrated) with the record.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".