Exploring ethnomathematics in Malay architecture and traditional hall in Penyengat Island and connecting it to geometry in elementary schools
Bibliographic record
Abstract
Malay ethnomathematics is culture-based learning that is very important in 21st-century life. The progress of globalization has led to many technological advances, which have resulted in many cultures being abandoned or even extinct. Ethnomathematics research can be a solution for preserving culture, because it integrates culture and learning materials in schools. This study aims to explore Malay ethnomathematics in the architecture of the Indra Perkasa Traditional Hall on Penyengat Island as a resource for teaching mathematics on geometry and measurement in elementary schools. The method used was an ethnographic study, which is part of a qualitative research method. Data collection techniques included observation, interviews, documentation, and other sources, such as books and journals. This study shows some aspects of Malay ethnomathematics related to geometry and measurement materials in elementary schools, including flat shapes, spatial shapes, and length measurements. This study indicates the potential for the integration of Malay ethnomathematics into the architecture of the Indra Perkasa Traditional Hall on Penyengat Island as a mathematics learning resource for geometry and measurement in elementary schools in Indonesia.
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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 | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".