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Record W7118175829 · doi:10.7454/jepi.v9i2.2224

Pengaruh Kinerja Makroekonomi Dalam dan Luar Negeri terhadap Penanaman Modal Asing di Indonesia

2009· article· W7118175829 on OpenAlexaboutno aff

Bibliographic record

VenueJurnal Ekonomi dan Pembangunan Indonesia · 2009
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsInflation (cosmology)Investment (military)Foreign direct investmentInterest rateInflation rateMoney supply

Abstract

fetched live from OpenAlex

This paper studies the effect of domestic and foreign macroeconomy performances on the foreign direct investment (PMA) in Indonesia, employing descriptive and inferencial (econometric model) analyses. The national economic grcwth and national interest rate affect significantly PMA in Indonesia. While the national inflation rate positively effected on PMA, but resuits show that hyperinflation contributes to decreasing PMA. The macroeconomic improvement in some competitor countries, especially Chinese and Thailand tends to decrease PMA in Indonesia. However, the improvement of macroeconomies in Singapore and Malaysia can increase PMA in Indonesia. Therefore, bilateral relationship with these countries must be intensified. In addition, although the economic growth of some More Developed Countries (MDCs) has positive relationship with PMA in Indonesia, but their effect were not significant statistically, except Canada. This implies that global finance crisis, especially in USA and european countries would not largely effect on PMA in Indonesia.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.019
GPT teacher head0.223
Teacher spread0.204 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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