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Record W2592179290 · doi:10.28986/jtaken.v2i2.65

EVALUASI ATAS IMPLEMENTASI APLIKASI SISTEM AKUNTANSI INSTANSI BASIS AKRUAL (SAIBA) PADA MITRA KERJA KPPN GORONTALO DAN MARISA

2017· article· en· W2592179290 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJurnal Tata Kelola dan Akuntabilitas Keuangan Negara · 2017
Typearticle
Languageen
FieldComputer Science
TopicInformation Retrieval and Data Mining
Canadian institutionsnot available
FundersMcGill University
KeywordsBusiness administrationAccrualComputer scienceBusinessAccounting

Abstract

fetched live from OpenAlex

The purpose of this research is to evaluate the success of accrual basic application system (SAIBA) implementation based on user perception with DeLone & McLean (DM) Information System (IS) Success Model Approach. The data used are primary and secondary data. Primary data gathered through questionnaires distributed to respondents while secondary data gathered from other institutions such as the Directorate General of Budget, Directorate General of Treasury, and Treasury Office of Gorontalo and Marisa. This model uses six variables which are system quality, information quality, user satisfaction, use, individual impact, and organizational impact. This research empirically showed that the accrual basic application system (SAIBA) currently implemented not successfully running yet based on all Delone and McLean's success measurement criteria.AbstrakPenelitian ini bertujuan untuk mengevaluasi sejauh mana keberhasilan implementasi aplikasi SAIBA yang telah berjalan selama ini berdasarkan sudut pandang pengguna (user) dengan menggunakan pendekatan Delone & McLean Information System Success Model. Sumber data yang digunakan dalam penelitian ini berasal dari data primer dan data sekunder. Data primer berupa data yang diperoleh langsung dari responden melalui kuesioner yang dibagikan. Sedangkan data sekunder adalah data yang diperoleh dan disajikan oleh pihak-pihak lainnya seperti Direktorat Jenderal Anggaran Kementerian Keuangan, Direktorat Jenderal Perbendaharan Negara Kementerian Keuangan, dan Kantor Pelayanan Perbendaharaan Negara (KPPN) Gorontalo dan Marisa. Model ini menggunakan enam variabel pengukuran yaitu kualitas sistem (system quality), kualitas informasi (information quality), kepuasan pengguna (user satisfaction), penggunaan sistem (use), dampak individu (individual impact) dan dampak organisasi (organizational impact). Penelitian membuktikan secara empiris bahwa implementasi aplikasi SAIBA belum berjalan sukses berdasarkan kriteria pengukuran sesuai model kesuksesan DeLone dan McLean (1992).

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0030.009
Open science0.0060.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.292
Teacher spread0.262 · 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