Pelaksanaan Pelayanan Publik Hak Tanggungan Terintegrasi Secara Elektronik Oleh Kantor Pertanahan Kota Jambi
Bibliographic record
Abstract
The Ministry of Agrarian Affairs and Spatial Planning/National Land Agency has launched electronic land services. The electronic service in question is electronically integrated mortgage rights (HT-el). With land services through an electronic system that is easy to use, it is the aim of the Ministry of Agrarian Affairs and Spatial Planning/National Land Agency to remain competitive in the digital era and help the community. The aim of this research is to determine the implementation, obstacles faced, and efforts made by the government in implementing electronic mortgage rights. The research method used is empirical juridical, through a socio-legal-research approach. The data sources used in this research are library data from laws, books, journals and the internet; Field data comes from interviews with related parties. Land office counters are no longer needed because HT-el services are all done online. This is a significant achievement of the Ministry of ATR/BPN in its efforts to improve the efficiency and quality of land services through implementing the e-Government concept. Based on the research findings, it can be concluded that the Jambi City Land Office has followed the process contained in the ATR/BPN Ministerial Regulation Number 5 of 2020 and HT-el technical instructions Number 2 of 2020 in implementing HT-el. Even though there are several obstacles, including system problems, inappropriate application files, unverified land parcel data, and SPS payments outside working hours, implementation continues.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.018 |
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".