Analisis Aspek Keperilakuan Terhadap Penerapan Sistem Akuntansi Persediaan Pada Dinas PUPRD Provinsi Sulut
Bibliographic record
Abstract
The purpose of this research was to determine the effect of behavioral aspects of attitudes, perceptions, and emotions on the application of the inventory accounting system at the Department of Public Works and Spatial Planning of North Sulawesi Province. The method used in this research is a quantitative method with multiple linear regression approach. The population of this research is the employees of the Department of Public Works and Regional Spatial Planning of the Province of North Sulawesi. While the research sample used by the researcher was 14 respondents. The results showed that the behavioral aspect of the attitude had no effect with a value of 0.078 on the implementation of the inventory accounting system. The behavioral aspect of perception has no effect with a value of 0.555 on the application of the inventory accounting system. Aspects of emotional behavior have no effect with a value of 0.714 on the implementation of the inventory accounting system. This is because the Department of Public Works and Spatial Planning of the Province of North Sulawesi has a good culture where this culture is the basis for employees to work based on standard operating procedures that have been set so that there is no opportunity to raise debates in aspects of behavior, attitudes, perceptions and emotions. The R Square value is 0.312 or 31.2%. This figure shows that the contribution of the behavioral aspects of attitudes, perceptions and emotions to explain the variables of the application of the inventory accounting system.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".