MODEL PERENCANAAN STRATEGIS SISTEM INFORMASI (STUDI KASUS PADA PEMERINAH DAERAH KEPULAUAN ANAMBAS)
Bibliographic record
Abstract
The use of IT / SI is an organization's needs in running its business and services. IT / SI is mostly done by the Government in carrying out its activities and services taken from others efficiently, effectively, and approved to support good and clean governance. KPPKB (Office of Empowerment of Women and Family Planning in Anambas Islands Regency) has also used IT / SI in carrying out its duties and services. The use of IT / SI in the Anambas Islands Regency KPPKB Office has not been carried out completely and many conventional activities have not been able to support optimal achievement of targets and performance. To obtain organizational goals, IT / SI strategies are needed in common with business strategies. This article discuss the steps in the analysis of information systems strategic planning at the Office of the KPPKB (Empowering Women and Family Planning) in the Anambas Islands Regency using the work of Ward and Peppard. The analysis tools used are PEST, CSF, SWOT, Value Chain and McFarlan Strategic Grid. The final results are expected to help the Anambas Islands District Women's Empowerment and Family Planning Office to be better in the system planning.
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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 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".