Perumusan Strategi Bumdes Tarumajaya Kawasan Hulu Sungai Citarum Kabupaten Bandung
Bibliographic record
Abstract
Pengabdian ini dimaksudkan agar BUMDES Tarumajaya menjadi outlet bagi produk yang dihasilkan penduduk setempat dan memiliki kinerja yang baik, sehingga dapat berkontribusi pada peningkatan kesejahteraan penduduk. Program normalisasi dan rehabilitasi kawasan hulu sungai Citarum menuntut peran masyarakat agar memberi kontribusi pada normalisasi dan rehabilitasinya. Metode yang dilakukan dengan survey, wawancara, serta pelatihan mengenai manajemen bisnis yaitu memanfaatkan peluang dengan memanfaatkan potensi yang dimiliki. Hasil identifikasi menunjukkan peluang dan kekuatan lebih banyak daripada ancaman dan kelemahannya. Matrik eksternal menunjukkan total skor 2,36 dan matriks internal 2,31. Berdasarkan analisis eksternal internal, menunjukkan BUMDES Tarumajaya berada pada kuadran V, yaitu ditahan dan dijaga, serta strategi yang tepat adalah penetrasi pasar dan pengembangan produk. Program yang dapat dilakukan, antara lain melakukan aktivitas pemasaran dengan memanfaatkan perkembangan teknologi informasi termasuk di dalamnya penelusuran alternatif pengembangan produk baru, sehingga dapat meningkatkan keragaman dan kualitas produk yang dijual serta memahami perkembangan selera konsumen dan pesaing.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".