PENGARUH PRODUK DOMESTIK BRUTO DAN SUKU BUNGA TABUNGAN RUPIAH TERHADAP JUMLAH TABUNGAN RUPIAH PADA BANK-BANK UMUM DI INDONESIA TAHUN 2004-2011
Bibliographic record
Abstract
This study aims to determine the effect of: gross domestic product (X 1 ) to the number of rupiah savings and the effect of interest rate of rupiah savings (X 2 ) to the number of rupiah savings. This study uses secondary data obtained from Bank Indonesia and the Central Bureau of Statistics and other sources that support this research. The data is in the form of time series (data prepared based of time series) from 1st quarter of 2004 up to 4th quarter of 2011 , which was analyzed by quantitative descriptive analysis method. The results showed that, GDP has a positive and significant effect on the number of rupiah savings. This is consistent with the research hypothesis and the theory of Keynes who said that the spending of savings depends on income level. While the interest rate of rupiah savings has a negative and significant effect on the number of rupiah savings. This is not consistent with the research hypothesis and Classical theory say that saving is a function of the interest rate, because of the amount of savings increased despite low interest rates. This situation can occur due to: 1). per capita income growing community, 2). People are not too concerned factor in this low interest rate, Keynes said Society believes in a normal interest rate, 3). increasing public confidence in the Bank's products and services offered by commercial banks. Keywords: Gross Domestic Product, Interest Rate, Savings
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
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 source (direct Gemma or distilled Codex), 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".