Malaysia housing price and its economic factors / Fatin Syahira Mastor
Bibliographic record
Abstract
Malaysia is one of ASEAN countries that is rapidly developing. However, housing price is a hot issue being debated in Malaysia. The main purpose of this research is to determine the economical factors which are affecting the housing price in Malaysia. Secondary data are applied to complete this research and the data are collected from World Development Indicator and National Property Information Centre (NAPIC). This research used time-series data from January 1999 to December 2018 which is 20 interval time to examine the causality. The research economic factors are Gross Domestic Product (GDP), Population (POP) and Inflation Rate (CPI). The result shows that only population has a positive relationship with the housing price index. Nevertheless, gross domestic product and inflation have negative insignificance relationships with the housing price index. These researches are significant to the researcher, developer, and government. They can take this research as their reference and take some idea to control and monitor all factors that will affect the Malaysian financial and economy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".