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Record W3118409914 · doi:10.33088/jmk.v9i1.299

ANALISIS PENERAPAN PENGELOLAAN KEUANGAN BADAN LAYANAN UMUM(PK-BLU) POLITEKNIK KESEHATAN KEMENKES BENGKULU

2018· article· en· W3118409914 on OpenAlexaff
Agung Riyadi

Bibliographic record

VenueJURNAL MEDIA KESEHATAN · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Satisfaction
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsNonprobability samplingOfficerBusinessRevenueFinanceAccountingFinancial managementBusiness administrationPolitical sciencePopulationMedicine

Abstract

fetched live from OpenAlex

fter two years of implementing the financial management of BLU, there is still themanager of the department / study program who do not understand the flexibility of financialmanagement that offers efficiency and productivity, have not seen the role of the supervisoryboard (a god) to the financial coaching BLU. Value turnover was still below the minimumrequirement, Operational Cooperation is still very minimal, opinions BLU is still small (under15 billion) and the remuneration of the BLU can not be granted to managers and employeesBLU officials. The purpose of this study was to determine the application overview ManagedHealth Polytechnic BLU MoH Bengkulu. This research was conducted with qualitative. Theunit of analysis of research data is Poltekkes MoH Bengkulu. The subject of research is theDirector, Pudir, Kasubbag Adum, Kaur Finance, kaur and Staff Officer, Treasurer BLU,Treasurer non-tax revenues, financial reporting staff, Ka. Planning Unit, Kajur/Sekjur,department managers, lecturers and students of each department / study program. Thesampling technique purposive sampling, namely the determination of the sample based oncertain criteria and based on the consideration of researchers. The results showed that 1) Theperception of the BLU is different - different. 2) Budget planning is already using the RBA asthe budget plan. 3) Source BLU reception from the state budget in the form of pure Rupiahand non-tax revenues came from students and other funding sources. 4) Has had threeaccounts that have been approved by theMinistry of finance. 5) The financial statements BLUconsist of the balance sheet, budget realization reports, activity reports, cash flow statementand notes to the financial statements and there are no clear technical guidelines on financialreporting BLU. 6) Have been prepared BLU performance accountability report. 7) Neverbefore have a budget deficit, and is still running a budget surplus. 8) Dewas still held byofficials not yet fully substitute god that can run all functions of a god .. 9) Monitoring offinancial management BLU implemented by SPI, Itjend, and the Office of PublicAccountants. 10) The remuneration system BLU yet fully implemented, the implementationof remun still follow the pattern of the ministries / agencies.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.133
GPT teacher head0.473
Teacher spread0.340 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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