Analisis Pengaruh Dinamisme Lingkungan dan Faktor Manajerial Terhadap Perencanaan Strategis dalam Upaya Meningkatkan Kinerja Organisasi Non-Profit dengan Pendekatan Balanced Scorecard
Bibliographic record
Abstract
External environment changes and managerial factors are important to be considered in the preparation of strategic planning. Strategic planning is very important for the organization, not only for profit organizations but also for nonprofit organizations because a formal strategic planning can guide them to assess how far their goals have been achieved and how to achieve them. This study discusses how the dynamism of the external environment and managerial factors influence strategic planning and its implications for WWF Indonesia's performance using the Balanced Scorecard approach. The research method used is to use a survey of employees at WWF Indonesia and processed with SmartPLS 3.0. The results show that external business environment dynamism and managerial factors can influence strategic planning which ultimately affects the improvement of WWF Indonesia's performance.
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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 | 0.008 |
| 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) | 0.009 | 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".