ANALISIS FAKTOR-FAKTOR YANGMEMPENGARUHI KETERLIBATANDEPARTEMEN AKUNTANSI DANKECANGGIHAN SISTEM AKUNTANSIDALAM PENGAMBILAN KEPUTUSANOUTSOURCING(Studi Empiris pada PT PLN APJ Tegal)
Bibliographic record
Abstract
This study aims to examine the degree of accounting department involvement in outsourcing decisions-making and the sophistication of accounting system in outsourcing decision-making units of the branch office and identify factors affecting accounting department involvement in outsourcing decisionmaking and sophistication of accounting system in outsourcing decision-making units of the branch office. Based on the Management Accounting researched by Dawne Lamminmaki (2008), with two dependent variables and three independent variables. Using survey questionnaire from managers and three supervisor from each branch office units in PT PLN (Persero) APJ Tegal and regression-path analysis in SPSS 16. The Accounting Management dimensions (number of customers, number of customers claim, degree of respondent education) are collectively analyzed in relation to the accounting department involvement in outsourcing decision-making and the sophistication of accounting system in outsourcing decision-making. The number of customers was a positive and significant factor affecting the accounting department involvement in outsourcing decision-making and the sophistication of accounting system in outsourcing decision-making. The number of customers claim was a negative and significant factor affecting the accounting department involvement in outsourcing decision-making and the sophistication of accounting system in outsourcing decision making. The degree of respondent education was a positive and insignificant factor affecting the accounting department involvement in outsourcing decision-making and the sophistication of accounting system in outsourcing decision-making.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".