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Record W4379659654 · doi:10.33480/techno.v20i1.3541

AUDIT OF THE REGIONAL DEVELOPMENT PLANNING INFORMATION SYSTEM (SIPD) USING COBIT 5.0 FRAMEWORK

2023· article· en· W4379659654 on OpenAlexaff
Marliana Rahmawati Nurhanifah, Ganda Wijaya, Jajang Jaya Purnama

Bibliographic record

VenueJurnal Techno Nusa Mandiri · 2023
Typearticle
Languageen
FieldComputer Science
TopicInformation Retrieval and Data Mining
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsCOBITCorporate governanceProcess (computing)BusinessProcess managementMaturity (psychological)Information systemAuditLocal governmentScale (ratio)Engineering managementComputer scienceAccountingPublic administrationEngineeringPolitical scienceGeographyFinance

Abstract

fetched live from OpenAlex

Tasikmalaya Regional Representative Council’s is one of the legislative institutions that runs the local government. In carrying out the duties and functions of the Leadership and Members of the Regional People's Representative Council in the regional development planning sector, the Secretariat of the Regional People's Representative Council of Tasikmalaya City has implemented information technology in the regional development planning process, namely the Regional Development Information System. This information system is inseparable from problems that can hinder the regional planning process. This study aims to find out how effective and efficient the use of this information system is based on the maturity level of COBIT 5. This research only focuses on the domains EDM05, APO03, APO07, BAI09, DSS01, and MEA03. Data collection techniques are carried out through observation, interviews, and the dissemination of questionnaires. Tasikmalaya Regional Representative Council’s has implemented IT governance at level 3, namely the Established Process. The results of the questionnaire processing obtained an average value of 3. 04 from a value scale of 0 to 5. The results showed weaknesses in the governance of the regional development planning information system found in the APO07 sub-domain which has the lowest maturity level value from other sub-domains, namely 1. 86.

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)0.031
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.014
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.041
GPT teacher head0.265
Teacher spread0.225 · 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 designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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