Analisis Reformasi Tata Kelola Administrasi Pemerintahan (Studi Kasus Provinsi Jawa Barat)
Bibliographic record
Abstract
The challenges of governance in the era of globalization are becoming increasingly complex, particularly in West Java Province, which faces public demands for efficiency, transparency, and accountability in public services. Although governance reforms have been implemented, obstacles such as complex bureaucracy, a lack of accountability, and rapid socio-economic changes continue to impact service quality. This study aims to analyze the impact of administrative governance reforms on the efficiency of public services. The main focus of this research is on the changes in transparency and public participation resulting from the implemented reforms, as well as the primary challenges faced in their implementation, including bureaucratic obstacles and technology adoption. The research employs a qualitative approach. Data were collected through 30 in-depth interviews with 10 government officials, 10 business actors, and 10 members of the general public. Additionally, focus group discussions (FGDs) were conducted involving 8-12 participants to gain deeper insights into their experiences related to governance reforms. Data analysis was performed using a thematic approach. The findings indicate that governance reforms in West Java Province have accelerated public administrative services, particularly through digitalization, which has reduced processing times for permits. However, challenges remain, such as limitations in human resources and technology, resistance to change among civil servants, and discrepancies in policy implementation across regions. Therefore, enhancing employee training and simplifying bureaucratic procedures are essential to ensure the sustainability of these reforms.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".