ADOPSI DAN PEMANFAATAN TIK BAGI PENGRAJIN KERAMIK DAN GERABAHDIKASONGAN
Bibliographic record
Abstract
This study aimed to determine the process of adoption and use of ICTs by the ceramics craftsmen and businessmen and also pottery at the Pottery Center in Kasongan, Bantu/, Yogyakarta. This research use Qualitative approach with a constructivist paradigm. Research methodology is case study, with the assumption of JCT as a new media especially the Internet in the process of adoption of innovation it takes time to be utilized properly and effectively. Stages of adoption process started from the knowledge acquired informally on the internet, from face to face communication with people who understand the Internet, to the decision to use it was fully decided by the artisans themselves. The study s findings, such as, the use of JCT to access the Internet by the craftsmen is still very limited. The use of internet is usually for e-mail, browsing to find the design of ceramic art in a globalized world, as well as for promotion of ceramic art products. Kasongan ceramic products are mainly for export markets (US., Europe, Korea, Canada, Malaysia) and less for the domestic market (Jakarta, Denpasar, Malang). Routinely, Dinasperindagkop Kab. Bantu/ implement training programs in production engineering and design for the craftsmen to improve the quality of the ceramic products. Kasongan ceramics center area is growing through the concept of Ge/em Kaji, which consists of 3 supporters in the surrounding area (center accessories, leather, pottery and stone sculpture) they all come together as a region center for a more comprehensive Kasongan ceramic products.
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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 | 0.002 | 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".