Analisis Ekspor Indonesia Ke Negara–Negara Di Kawasan Asia Pasifik Tahun 2010–2018
Bibliographic record
Abstract
The contribution of goods and services exports to GDP in Indonesia is still relatively low and tends to decline during the period 2010–2018. This study aims to analyze the effect of port infrastructure quality index, port container terminal area, GDP per capita, and exchange rate on exports made by Indonesia to ten countries in the Asia Pacific region, including Thailand, Singapore, the Philippines, Japan, China, Australia, New Zealand, United States, Canada and Mexico. The analysis method used is panel data regression with a fixed effect approach. The results showed that the port infrastructure quality index had no effect on exports. Meanwhile, the exchange rate and GDP per capita have a negative effect on exports. The area of the port container terminal was found to have a positive effect on exports. Exports of raw materials with low added value must be reduced and replaced by exports of finished goods or semi-finished goods with high added value so as to reduce the current account deficit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".