Pemanfaatan dan Pendampingan Media Sosial Sebagai Sarana Promosi
Bibliographic record
Abstract
Bantul merupakan salah satu Kabupaten di Daerah Istimewa Yogyakarta yang mempunyai banyak obyek wisata salah satunya adalah Desa Wisata Kaki Langit yang terletak di Pedukuhan Mangunan Desa Mangunan, Kecamatan Dlingo, Kabupaten Bantul dan secara geografis terletak di Perbukitan sebelah barat Kecamatan Dlingo yang berbatasan dengan Desa Muntuk, Dlingo, Bantul. Jarak Desa Wisata Kaki Langit Mangunan dari Ibukota Kecamatan 4 Km, 12 Km dari Ibu kota Kabupaten dan 22 Km dari Ibu Kota Daerah Istimewa Yogyakarta. Desa wisata Kaki Langit menjadi salah satu kandidat Kampung Adat Terpopuler dalam Penghargaan Anugerah Pesona Indonesia 2017 dan menjadi finalis Lomba Desa Wisata Tingkat Nasional 2017 yang diselenggarakan oleh Kementerian Pariwisata. Permasalahan yang dihadapi mitra salah satunya adalah pemasaran produk sumber daya alam yaitu empon-empon yang sudah diolah menjadi minuman instan, diolah dalam bentuk kapsul dan jamu celup. Metode yang digunakan model Edukatif yaitu pendekatan sosialisasi, pelatihan dan pendampingan sebagai sarana transfer ilmu pengetahuan dan pendidikan untuk pemberdayaan masyarakat, dan program pengabdian menghasilkan peningkatan kemampuan pemasaran secara online.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".