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Record W3080201016 · doi:10.33059/jseb.v11i2.1919

Analisis Faktor-Faktor yang Mempengaruhi Nilai Tukar Rupiah Periode 1999Q1-2019Q2

2020· article· en· W3080201016 on OpenAlexaboutno aff
Erric Wijaya

Bibliographic record

VenueJurnal Samudra Ekonomi dan Bisnis · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsExchange rateEconomicsInflation (cosmology)Quarter (Canadian coin)Monetary economicsLiberian dollarInterest rateValue (mathematics)Inflation rateInternational economicsGeographyMathematicsFinance

Abstract

fetched live from OpenAlex

The exchange rate plays an important role in influencing the level of Indonesia's international trade towards trading partner countries. This study discusses the factors that influence the exchange rate of the rupiah against dollar both in the short and long term. The variables that are suspected to influence changes in exchange rates are the inflation rate, the interest rate (SBI), world oil prices, the value of exports, and the value of imports. This research was conducted during 1999 quarter 1 to 2019 quarter 2. The results showed that there was a long-term and short-term relationship between inflation rates, interest rates, world oil prices, exports and imports to the exchange rate. In the short term, the interest rate and world oil prices have a significant effect on the exchange rate. In the long run, the inflation rate, world oil prices and imports have a significant effect on the exchange rate.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.047
GPT teacher head0.207
Teacher spread0.161 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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