Analisis pengaruh Dana Desa, Alokasi Dana Desa dan Bantuan Keuangan Khusus Keistimewaan Kalurahan terhadap indeks Desa Membangun di Kabupaten Gunungkidul
Bibliographic record
Abstract
Purpose – This study aims to analyze the influence of Village Funds (Dana Desa), Village Fund Allocation (Alokasi Dana Desa), and the Special Financial Assistance for Privilege Funds (Bantuan Keuangan Khusus Dana Keistimewaan) on the Village Development Index (Indeks Desa Membangun, IDM) in Gunungkidul Regency.Methods – The study employs panel data analysis on 114 villages in Gunungkidul Regency over the 2019–2023 period.Findings – The results indicate that Village Funds, Village Fund Allocation, and Special Financial Assistance for Privilege Funds significantly affect the Village Development Index. Village Fund Allocation has a greater effect on IDM improvement than Village Funds and Special Financial Assistance. Additionally, Special Financial Assistance for Privilege Funds has a more pronounced impact on IDM enhancement for villages categorized as developing and advanced.Implication – The findings imply that the management of Village Funds, Village Fund Allocation, and Special Financial Assistance should be data-driven, transparent, and accountable, with active community involvement and rigorous oversight. Collaboration between the government and stakeholders is essential to ensure effective utilization and maximize the benefits for local communities.Originality – This study contributes to the literature by analyzing fiscal policies related to Village Funds, Village Fund Allocation, and Special Financial Assistance for Privilege Funds in Gunungkidul Regency using panel data.Originality – This research analyzes the influence of DD, ADD, and especially BKK DAIS Kalurahan budget policies in Gunungkidul Regency to be relevant and important to be carried out in an effort to increase IDM. AbstrakTujuan – Penelitian ini bertujuan untuk menganalisis pengaruh Dana Desa, Alokasi Dana Desa dan Kebijakan Bantuan Keuangan Khusus Dana Keistimewaan terhadap Indeks Desa Membangun di Kabupaten Gunungkidul.Metode – Penelitian ini menggunakan analisis data panel pada 114 desa di Kabupaten Gunung Kidul pada periode tahun 2019-2023. Temuan – Hasil penelitian ini menunjukkan bahwa Dana Desa, Alokasi Dana Desa dan BKK Dana Keistimewaan memiliki pengaruh terhadap Indeks Desa Membangun. Alokasi Dana Desa lebih berpengaruh terhadap peningkatan IDM dibandingkan Dana Desa dan BKK Dana Keistimewaan. BKK Dana Keistimewaan lebih berpengaruh terhadap peningkatan IDM pada desa yang berstatus berkembang dan maju.Implikasi – Penelitian ini berimplikasi pada bahwa Pengelolaan Dana Desa, Alokasi Dana Desa, dan Bantuan Keuangan Khusus Dana Keistimewaan Kalurahan harus berbasis data, transparan, dan akuntabel dengan melibatkan masyarakat serta pengawasan ketat. Kolaborasi antara pemerintah dan pemangku kepentingan menjadi kunci efektivitas dan optimalisasi manfaat bagi masyarakat.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".