PELAYANAN PUBLIK KANTOR KELURAHAN KADIPIRO KECAMATAN BANJARSARI KOTA SURAKARTA
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
Tujuan penelitian untuk mendeskripsikan dan menganalisis pelayanan publik Kantor Kelurahan Kadipiro. Metode penelitian menggunakan deskriptif kualitatif. Teknik pengumpulan data menggunakan wawancara, observasi, dan dokumentasi. Teknik analisis data menggunakan model analisis interaktif. Hasil penelitian menunjukkan bahwa: Pelayanan Publik berkaitan dengan Reliability (kehandalan) sudah dilaksanakan cukup baik. Pelayanan publik berkaitan dengan Tangibles (bukti langsung), dasarnya sudah dilaksanakan dengan baik. Pelayanan publik berkaitan dengan Responsiveness (daya tanggap), ditunjukkan kemampuan para staf dalam memberikan pelayanan sudah dilaksanakan dengan baik. Pelayanan publik berkaitan dengan Assurance (jaminan), pegawai memberikan pelayanan yang baik kepada masyarakat serta sopan dan santun. Pelayanan publik berkaitan dengan Emphaty (empati), ditunjukkan keseriusan dan ketulusan pegawai dalam melayani masyarakat, sikap tegas tapi penuh perhatian terhadap masyarakat. Kendala-kendala yang mempengaruhi pelayanan publik, antara lain: keterbatasan sumber daya manusia yaitu kurangnya jumlah pegawai, sarana dan prasarana yang masih kurang, komputer yang sering trobel dan lambat. Mengatasi kendala tersebut pihak Kelurahan Kadipiro memaksimalkan jam kerja, dan memanfaatkan anggota Linmas, menyarankan masyarakat untuk mencari informasi melalui media online, menyediakan computer cadangan. Kata kunci: reliability, tangible, responsiveness, Assurance, dan Emphaty
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.010 |
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