Mewujudkan Pelayanan Publik dalam Sistem Pemerintahan Berbasis Elektronik: Peran Diskominfo Provinsi Jawa Tengah Pada 2018-2023
Bibliographic record
Abstract
Dampak kemajuan teknologi digital membuat Pemerintah harus bertransformasi dari yang bersifat Government Centric menjadi Society Centric. Layanan publik harus jadi cepat, tepat, mudah dan murah. Pemerintah Provinsi Jawa Tengah melalui Diskominfo sepanjang 2018-2023 giat meningkatkan pelayanan publik melalui Sistem Pemerintahan Berbasis Elektronik (SPBE). Hasilnya, capaian Indeks SPBE telah melampaui target akhir RPJMD, dari 2018 sebesar 3,24 menjadi 3,68 pada 2023. Capaian Indeks SPBE yang telah melampaui target pembangunan akan berpengaruh positif pada peningkatan pelayanan publik Diskominfo. Tingkat kematangan pelayanan publik Diskominfo menunjukkan kenaikan level dari rentang 3-4 menjadi 3-5. Meskipun demikian, masih ditemukan kekurangan terkait implementasi pelayanan publiknya. Untuk mendalami permasalahan tersebut dilakukan penelitian dengan mempelajari laporan-laporan dan survei dengan metode wawancara terbuka. Hasil penelitian menunjukkan permasalahan tersebut adalah optimalisasi, kemanfaatan dan kesesuaian kebutuhan pelayanan.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.090 | 0.019 |
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".