Analisis Difusi Inovasi pada Inovasi Produk Batik di Kelurahan Jenggot Dalam Mendukung Upaya Pengembangan Ekonomi Lokal Kota Pekalongan
Bibliographic record
Abstract
The development of innovation in a particular area cannot be separated from the diffusion of innovation. This diffusion of innovation occurs because of the process of social interaction by related actors in the region. This is explained by Rogers (2003), that the diffusion of innovation is a process when innovation is communicated or mentioned through certain channels for a certain period of time to members of a social system, which then becomes part of the social system. With the diffusion of innovation, an area will experience changes in certain conditions due to the impact of emerging innovations, which will play a role in developing the character of the region. As happened in Jenggot village, the emergence or entry of new patterns influenced changes in the market in terms and the direction of development of the existing batik patterns in the village. Batik patterns that were originally patterned and impressed monotonously with plant and animal-based patterns are becoming more contemporary and fashionable. The diffusion of innovation helps business owners either directly or indirectly in promoting their batik products. Thus increasing the value of the batik product itself.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".