Pelatihan Pengelolaan Website, Media Sosial, dan Google my Business di Kintamani Edelweiss Park
Bibliographic record
Abstract
Kintamani Edelweiss Park merupakan salah satu Kelompok Sadar Wisata (Pokdarwis) di Lingkungan Caldera Batur tepatnya di Kaki Gunung Batur Kecamatan Kintamani, Kabupaten Bangli Provinsi Bali. Kintamani Edelweiss Park beranggotakan masyarakat lokal yang sebagian besar merupakan pelaku wisata. Tempat ini dibentuk sebagai alternatif bagi wisatawan selain menikmati Mount Batur and Lake View, Mount Batur Trekking, dan Natural Hot Spring, wisatawan juga bisa menikmati Edelweiss Park yang berlatar belakang Gunung dan Danau Batur. Mitra ini dipilih sejalan dengan Visi dan Misi STMIK STIKOM Indonesia yaitu mendukung perkembangan industri pariwisata melalui pemanfaatan teknologi informasi. PKM ini bertujuan membantu meningkatkan kunjungan wisata ke Bali, meningkatkan perekonomian masyarakat dari sektor pariwisata khususnya Bali Timur untuk pemerataan pembangunan seluruh kabupaten kota di Bali. Pada PKM ini telah diberikan sebuah website domain dan hosting selama satu tahun. Selain memberikan website, juga dilakukan program pelatihan pengelolaan website menggunakan Wordpress, pelatihan manajemen sosial media menggunakan Canva, serta pelatihan membuat listing bisnis di google menggunakan Google my business. Dengan adanya kegiatan PKM, saat ini mitra sudah memiliki website yang bisa diakses di www.kintamaniedelweisspark.com, akun Facebook dan Instagram. Selain itu mitra juga memiliki pengetahuan tentang manajemen website menggunakan wordpress, manajemen sosial media dengan canva serta listing bisnis di Google.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.170 | 0.069 |
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".