PERENCANAAN STRATEGIS TEKNOLOGI INFORMASI: Studi Kasus Pada Perguruan Tinggi Lepisi Tangerang
Bibliographic record
Abstract
Strategic plan IS/IT is an identification process portofolio application IS bases on computer that will support organization in execution of business plan and implement its business target. Strategy Planning IS/IT studies influence IS/IT to business performance and contribution for organization in selecting strategic steps. In other hand strategic plan IS/IT also explains various of toolses, technique and framework for manjemen to harmonize strategy IS/IT with business strategy, even prowl just pass by innovative technology implementation. In course of strategic plan IS/IT with object of LEPISI College research this, writer uses framework according to Jhon Ward and Peppard. Concept of idea from strategic plan IS/IT from Jhon Ward left from existence of invesment condition IS and TI in the past that less can give benefit for target of organization business, catch business opportunity, and existence of phenomenon growing of competitive excellence organization because can exploit potency IS and IT. Situation is referred can happen because strategic plan IS and TI that out of focus at business, conducted by part that less understand business opportunity, and make only strategy because technology need. The result of research this is the have the shape of proposal of strategy planning framework Information system that can be used at college LEPISI. Keyword: Information system Strategic plan/Information Technology, Methodologies IS/IT
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".