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Record W7118179603 · doi:10.55927/fjmr.v4i11.609

Evaluating the Implementation of Presidential Instruction No. 1/2025 on Budget Efficiency at the Directorate General of Taxes: Evidence from the First Quarter of Fiscal Year 2025

2025· article· W7118179603 on OpenAlexaboutno aff
Abdul Khaliq Brutu, Dwirini Dwirini, Wisnu Firdiansah Haris

Bibliographic record

VenueFormosa Journal of Multidisciplinary Research · 2025
Typearticle
Language
FieldSocial Sciences
TopicLocal Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsTreasuryAccountabilityQuarter (Canadian coin)Presidential systemFiscal yearOperating budgetPerformance indicatorCapital expenditureDescriptive statistics

Abstract

fetched live from OpenAlex

This study aims to evaluate the implementation of Presidential Instruction Number 1 of 2025 concerning Budget Efficiency at the Directorate General of Taxes (DGT), focusing on the Budget Execution Performance Indicators (IKPA) in the first quarter of the 2025 fiscal year. The research method uses a descriptive qualitative approach through a case study, with data collection from the analysis of budget documents, performance reports, interviews, and reviews of relevant regulations and circulars. The results show that DGT has implemented budget efficiency in accordance with the Presidential Instruction through concrete steps such as reducing official travel, optimizing online activities, cutting ceremonial expenses, and postponing capital expenditures (except for those already under contract). However, the budget blocking mechanism, which only entails flagging, means that the funds subject to efficiency measures remain included in performance calculations. As a result, three out of eight IKPA indicators Deviation of DIPA Page III, Budget Absorption Target, and Output Achievement were not optimally met. In response, the Directorate General of Treasury applied the principle of fairness treatment by giving a score of 100 to all IKPA indicators during the first quarter of 2025. This study recommends strengthening monitoring, transparency, and information technology optimization so that budget efficiency does not hinder organizational goals and continues to ensure the accountability of state financial governance.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.467
Teacher spread0.372 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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