PEMBERDAYAAN MASYARAKAT, KARANG TARUNA DAN DARMA WANITA DALAM MENGENTASKAN MASALAH SAMPAH DAN LIMBAH DI DESA PARUNG
Bibliographic record
Abstract
KKN Tematik Terintegrasi bagi masyarakat yakni untuk meningkatkan kesadaran masyarakat dengan berperan aktif dalam mengembangkan produktifitas sumber daya pembangunan sesuai dengan fasilitas yang dimiliki. Kegiatan KKN Tematik Terintegrasi UIKA Bogor Tahun 2017 merupakan salah satu kegiatan dengan pendekatan community development, dimana pada pelaksanaan kegiatan ini melakukan proses perencanaan sekaligus aksi program Pendampingan masyarakat baik pada aspek sosial, ekonomi, kesehatan, pendidikan, hukum, dan agama maupun teknologi tepat guna secara terpadu. KKN yang diselenggarakan tahun kelompok 15 Terpofokus di desa Parung, adalah sebuah desa yang sedang mengarah ke desa perkotaan dengan luas wilayah ± 168,259 Hektar, terletak di kecamatan Parung, Kabupaten Bogor yang berbatasan langsung dengan Kota Depok. rendahnya tingkat pendidikan, sebagian besar warga Desa Parung bekerja sebagai pedagang di pasar. Kurangnya kepedulian warga RW 04 terhadap kebersihan lingkungannya, hampir seluruh warga RW 04 selalu membuang sampah ke jalanan, kebun, bantaran sungai, sehingga banyak sekali sampah-sampah organik maupun anorganik di sekitar lingkungan. Metode yang digunakan dalam pengabdian ini Pendekatan, Partisipasi Masyarakat dan Langkah Evaluasi.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.047 | 0.011 |
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".