Studi Deskriptif Penggunaan Alokasi Dana Desa dalam Program Pemberdayaan Masyarakat di Desa Penfui Timur Kecamatan Kupang Tengah Kabupaten Kupang
Bibliographic record
Abstract
This thesis examines the use of Village Fund Allocation (VFA) in community empowerment programs in Penfui Timur Village, Central Kupang District, Kupang Regency. This study aims to identify and analyze how the Village Fund Allocation (VFA) is utilized to support community empowerment initiatives in the area. The theoretical framework employed to address the research problems encompasses village fund allocation and community empowerment concepts. This study adopts a qualitative research method. Primary data were obtained from key informants, while secondary data were drawn from documents related to the research variables. Data were collected through interviews, observation, and documentation. The data analysis process consisted of data reduction, data presentation, and conclusion drawing, followed by descriptive qualitative analysis. The findings indicate that the Village Fund Allocation in Penfui Timur Village has been directed toward various community empowerment programs, including skills training, strengthening of community institutions, and support for productive economic activities. However, several challenges were identified in its implementation, namely ix Page | ix limited human resources, low levels of community participation among certain groups, and suboptimal program monitoring and evaluation. Therefore, it is recommended that village administrative capacity be enhanced, fund management transparency be improved, and active community participation be encouraged, so that the use of the Village Fund Allocation can be more effective and well-targeted in improving the welfare of the village community. Based on the findings above, the author concludes that the use of the Village Fund Allocation in community empowerment programs in Penfui Timur Village, Central Kupang District, Kupang Regency has been running well, as measured through two aspects, namely the utilization of village funds and the transparency of village fund management.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".