FAKTOR YANG MEMPENGARUHI KEBERHASILAN IMPLEMENTASI SIAPADA PNPN UPK MANDIRI
Bibliographic record
Abstract
This research is motivated by the importance of accounting information system in micro-finance institutions which UPK PNPM Mandiri which has an important role as a catalyst for poverty alleviation. Various data and field observations indicate that the accounting information system of various UPK PNPM Mandiri has not shown reliable system performance and relevant quality, even accounting standards have not been fully implemented. This research adapt DeLone and McLean model that has been modified McGill et al (2003) to map and design a critical component of the successful implementation of accounting information systems for individual users as well as analyzing a variety of system variables on user satisfaction, and the impact on individual performance. The hypothesis was analyzed using Structural Equation Model (SEM) with the help of software SmartPLS 2.0M3. Results of this research is the quality system affect the perceived quality of the system. The perception of the quality system has no effect on end-user satisfaction. The quality of information influence on end-user satisfaction. End-user satisfaction effect on system usage. The quality of the information does not affect the use of the system. The perception of the quality system does not affect the use of the system. Keywords : QIS, AIS, DeLone and McLeon.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".