Perencanaan Konten Media Sosial Dalam Event Road Tour Legacy Of Java X Sidji Batik Coffee Series
Bibliographic record
Abstract
Tujuan dari penelitian ini adalah melakukan kegiatan perancangan konten media social dalam rangka mempromosikan event “Road Tour Legacy of Java Batik Sidji X Coffee Series”. Kegiatan perancangan ini dimulai dari pengumpulan data secara kualitatif untuk mengetahui perencanaan media promosi yang digunakan. Teknik Pengumpulan data dilakukan dengan melakukan wawancara dan observasi secara langsung kepada salah satu seniman yang terlibat dalam kegiatan event. Hasil penelitian menunjukan perancangan konten event dilakukan dengan Menentukan Platform, Menentukan konten, Analisis & Evaluasi SWOT (Strenghts, Weaknesess, Opportunities, dan Threats), dan Action & Communication.. Media sosial pembuatan konten yang sesuai seperti yang dibuat oleh Batik Sidji yaitu film pendek mengenai Batik pada Channel Youtube, dan informasi yang diberikan Batik Sidji melalui Instagram dapat menarik perhatian masyarakat terhadap kesenian Batik.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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; both teacher heads agree on what is shown here.
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".