Kajian Kinerja Pelaksanaan Pengurusan Persetujuan Bangunan Gedung (PBG) pada Dinas PUPR Kabupaten Padang Pariaman
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 2022, the implementation of PBG processing which has been carried out by the Padang Pariaman DPUPR in the field of Human Settlement does not comply with the time period based on the established regulations. In this regard, the author conducted research on the factors that influence its implementation, the obstacles faced, as well as potential improvements or recommendations to increase the efficiency and effectiveness of the process. The research method used is a qualitative method by distributing questionnaires and interviews with informants. The dominant factor is timeliness in implementing PBG arrangements; facilities and infrastructure; HR; and initiative. In the Likert Scale assessment, the highest result was obtained in the Disagree assessment, namely 5.57%. The results of the identification of indicators and evaluation results have been validated with experts so that the author provides recommendations to the field of creative work of the Padang Pariaman Regency DPUPR to increase the number of human resources capable of carrying out PBG implementation in accordance with applicable regulations. The Padang Pariaman Regency DPUPR Job Creation Sector must have the facilities and infrastructure to carry out the duties of implementing PBG in serving the community. And the Cipta Karya sector must have the initiative to provide information to the public about PBG and provide licensed experts to help the community complete the PBG requirements.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it