Efek Perlakuan Panas Terhadap Perubahan Warna Bambu Sembilang (Dendrocalamus giganteus)
Bibliographic record
Abstract
ABSTRACT Bamboo can be used as an alternative raw material to replace wood. Bamboo is a fast-growing plant that requires quality improvement. One type of bamboo that has not been utilized optimally is sembilang bamboo. Quality improvement can be done through heat modification. Heat treatment can improve the mechanical properties of a material but can cause discoloration. This study aimed to determine the effect of heat treatment on the discoloration of sembilang bamboo. This research was conducted by giving sembilang bamboo heat treatment at 180°C for 3 hours and 6 hours. The results obtained were sembilang bamboo, after heat treatment for 3 hours and 6 hours became darker than the control. The longer the heating time, the greater the value of the color change.  Keywords: color change, heat treatment, sembilang bamboo  ABSTRAK Bambu dapat dijadikan sebagai bahan baku alternatif pengganti kayu. Bambu termasuk tanaman cepat tumbuh yang memerlukan peningkatan kualitas. Salah satu jenis bambu yang belum dimanfaatkan secara optimal adalah bambu sembilang. Peningkatan kualitas dapat dilakukan dengan cara modifikasi panas. Perlakuan panas dapat meningkatkan sifat mekanis suatu bahan namun dapat menyebabkan perubahan warna. Tujuan penelitian ini adalah mengetahui efek perlakuan panas terhadap perubahan warna bambu sembilang. Penelitian ini dilakukan dengan memberikan perlakuan panas pada bambu sembilang dengan suhu 180°C selama 3 jam dan 6 jam. Hasil yang didapatkan adalah bambu sembilang setelah perlakuan panas selama 3 jam dan 6 jam menjadi lebih gelap dibandingkan kontrolnya. Semakin lama waktu pemanasan maka nilai perubahan warnanya semakin besar.  Kata kunci: bambu sembilang, perlakuan panas, perubahan warna
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".