REVITALISASI BORNEO HOURSE STABLE PENGEMBANGAN FASILITAS, PROGRAM EDUKASI, DAN OPTIMALISASI AKSES INFORMASI MELALUI PEMASANGAN PENUNJUK ARAH
Bibliographic record
Abstract
Borneo Horse Stable, yang terletak di Balikpapan Utara, memiliki potensi besar sebagai kawasan wisata edukatif dan rekreatif, namun menghadapi berbagai permasalahan seperti kerusakan akses akibat longsor, minimnya fasilitas penunjuk arah, rendahnya pengetahuan masyarakat tentang berkuda, serta kurangnya variasi pemasukan dari aktivitas peternakan. Permasalahan tersebut menjadi alasan utama dipilihnya lokasi ini untuk Program Mahasiswa Mengabdi Desa (PMMD). Metode penyelesaian dilakukan melalui tiga pendekatan utama: pemasangan papan penunjuk arah di titik strategis untuk memudahkan navigasi pengunjung, pelaksanaan program edukasi berkuda untuk anak-anak guna meningkatkan pengetahuan dan minat terhadap perawatan kuda, dan pembuatan merchandise seperti topi dan aksesoris sebagai upaya meningkatkan pendapatan dan daya tarik wisata. Hasil dari program ini menunjukkan peningkatan kenyamanan pengunjung dalam menjelajahi kawasan, bertambahnya pengetahuan anak-anak terkait berkuda, serta meningkatnya antusiasme terhadap produk wisata yang ditawarkan. Kesimpulannya, pendekatan yang diterapkan tidak hanya menyelesaikan permasalahan utama, tetapi juga mampu mendukung pengembangan wisata Borneo Stable Horse secara berkelanjutan dan berkontribusi terhadap peningkatan ekonomi masyarakat sekitar.
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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 | 0.002 | 0.003 |
| 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 | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.009 |
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".