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Record W4287095759 · doi:10.18280/ijsse.120308

Implementation of Integrated Business Licensing Applications Online with a Risk-Based Approach (OSS-RBA) for Legal Assurance of Business Affairs in Langkat District

2022· article· en· W4287095759 on OpenAlexvenueno aff
Mukidi, Marzuki Marzuki, Nelvitia Purba, Murad Daeng Patiorang, Rudy Pramono, Juliana Juliana

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Analysis in Indonesia
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)BusinessInvestment (military)Agency (philosophy)Legal certaintyBusiness caseService (business)FinancePublic relationsMarketingProcess managementLawPolitical science

Abstract

fetched live from OpenAlex

Implementing Business licensing services for district and city governments has used the OSS application system so far. Still, the reality shows that the results have not demonstrated optimal results both in quality and quantity. However, in line with technological developments that cannot be denied, like it or not, the business community must be able to try to follow the Government's thinking to be effective and efficient in implementing services and Business licensing needs to the community by implementing an Online Application with a risk-based approach (OSS-RBA). As a refinement of legal considerations to face risks in the community business. In this case, the Langkat Regency government's Responsibility is the one-stop investment application and licensing service for the Langkat Regency, North Sumatra, based on government policies through the Ministry of Investment or the agency in charge of investment, applies licensing applications with a risk-based approach (OSS-RBA). It is hoped that the efforts made by the Langkat Regency government with an integrated one-door system, the Application of this Application can help the community, especially in the Langkat Regency area, to be effective and efficient in obtaining business permits to improve people's welfare and obtain legal certainty in running their Business. Supervision is carried out periodically and incidentally to provide business assessments and assurance to micro, small and medium-sized business actors and investment from the Langkat district government. This research is normative legal research, by conducting library research oriented toward applicable laws and regulations using a qualitative approach. The theory used in this paper is the theory of the welfare state based on the spirit and awareness to build a prosperous social justice country by obtaining legal certainty. The results of the study found that the Responsibility of the Langkat Regency government in implementing business licensing applications through online applications with a risk-based approach (OSS-RBA) to realize the economic welfare of the community effectively, easily and cheaply and quickly by empowering all potential resources to fulfil the best service to the business community.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.008
GPT teacher head0.276
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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