Analysis of The Jakarta Public Satisfaction Index (IKM) During The Covid-19 Pandemic, Quarter IV of 2021 on Public Services In The Investment Management Unit and One-Door Integrated Services (Dpmptsp) at The Urban Village Level, Jakarta Province
Bibliographic record
Abstract
This study aims to analyze the level of satisfaction of the people of DKI Jakarta with the implementation of public services during the Covid 19 pandemic in 2021, especially services at the Urban Village level. The level of community satisfaction was analyzed through a survey conducted on 3,510 respondents from all areas in Jakarta. This research uses a quantitative method, while the community satisfaction survey uses an interview method using a computer via the jakevo.jakarta.go.id website or commonly known as Computer Assisted Web interviewing, for 107 permits and non-permits surveyed. In this way, the characteristics of each service level will be known, making it easier for service managers to know the strengths and weaknesses of the services provided to the public. The results of the study indicate that there is a need for efforts to maintain the quality of existing services, by making efforts to consistently improve service quality. Services that need to be maintained are not charged outside the provisions and what needs to be improved is that Jakevo information is clear and easy to understand.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".