Upaya Penerapan Manajemen Pengetahuan dI Perpustakaan STIKES ALifah Padang
Bibliographic record
Abstract
AbstractIn this paper, we discuss the implementation of knowledge management in the Alifah Padang STIKes Library. The writing of this paper aims to describe: (1) the application of technology in the Alifah Padang STIKes Library; (2) cultural changes that occur in the Alifah Padang STIKes Library; (3) knowledge sharing activities in the Alifah Padang STIKes Library; (4) knowledge management socialization at Alifah Padang STIKes Library. This study uses a descriptive method with a qualitative approach, which is collecting data by observing and interviewing 5 visitors and 1 librarian at the Alifah Padang STIKes Library. Based on the analysis of the data described earlier, it can be concluded the following matters. First, the application of information technology in the Alifah STIKes Library is applied to the field of information processing activities using the SIMPUS application and information retrieval fields by utilizing online catalogs. Second, the cultural changes that occurred in the STIKes Library were seen from the changes in the organizational structure of the Alifah STIKes Library, which was based on the level of human resources and expertise in managing the library. Second, the cultural changes that occurred in the STIKes Library were seen from the changes in the organizational structure of the Alifah STIKes Library, which was based on the level of human resources and expertise in managing the library. Third, the form of knowledge sharing activities in the Alifah STIKes Library was carried out by sharing knowledge between Alifah STIKes library officers on issues in library management, establishing cooperative relations with 9 university libraries in West Sumatra in the field of complementary library materials, and participating in training activities at Bina institutions. Jakarta Library. Fourth, Knowledge management socialization in the Alifah STIKes Library in terms of the socialization of the results of the meeting which was decided by the Chairperson of Alifah STIKes based on mutual agreement of the meeting members, by delivering the results of the meetings conducted hierarchically through superiors to subordinates in an oral and written form thoroughly.Keywords: knowledge management; implementation; library
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".