The determinant of housing price in Malaysia / Fatin Nur Syamimi Mohd Herman
Bibliographic record
Abstract
Housing price fluctuate has given many concern to most households and developers. Thus, objective of this study is to investigate the factors that influence housing price in Malaysia for the period of quarter one 2006 to quarter four 2017. The independent variables used include population, household income, base lending rate and construction cost. Ordinary Least Squares (OLS) method was used to analyse the data collected from World Bank, Bank Negara Malaysia (BNM) and Department of Statistic Malaysia in order to examine the determinants of housing price in Malaysia. The results revealed that household income has positive and significant influence the housing price in Malaysia. The negative and significant relationship between base lending rate and housing price in Malaysia also been obtained from findings. However, population has negative and insignificant impact to housing price in Malaysia while construction cost has positive but insignificant impact the housing price. The finding of this paper will assist future researcher to obtain a better results by using other variables apart from been used in this study. The future researcher also can wide the range of scope and using other method to analyse the data.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".