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Record W2775963605 · doi:10.24127/trb.v4i2.72

PENGARUH PENINGKATAN KUALITAS SERAT RESAM TERHADAP KEKUATAN TARIK, FLEXURE DAN IMPACT PADA MATRIKS POLYESTER SEBAGAI BAHAN PEMBUATAN DASHBOARD MOBIL

2017· article· id· W2775963605 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTurbo Jurnal Program Studi Teknik Mesin · 2017
Typearticle
Languageid
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsImpact
Fundersnot available
KeywordsComposite materialPhysicsMaterials scienceNuclear chemistryChemistry

Abstract

fetched live from OpenAlex

Tanaman resam (dicranopteris linearis) merupakan pakis hutan yang hidup di perkebunan karet dan tumbuh hampir diseluruh provinsi di Indonesia. Tumbuhan ini menjalar dan memiliki panjang kurang lebih 7 meter. Penelitian yang sudah dilakukan oleh peneliti lain menunjukkan bahwa penggunaan serat alam sebagai bahan komposit dapat ditingkatkan dengan NaOH. Tujuan penelitian ini adalah untuk mendapat bahan komposit baru, hasil dari perlakuan kimia dengan larutan NaOH terhadap serat resam. Tahapan proses penelitian ini yaitu pembuatan sampel uji, pengujian mekanik dan analisis data. Bahan-bahan untuk pembuatan sampel diantaranya adalah serat, resin Yukalac 157 BQTN-EX, MEKPO sebagai hardener, 5% NaOH dan wax glasses sebagai pencegah menempelnya resin ke cetakan. Benda uji dibuat dengan cara mencampurkan secara acak serat ke resin. Sebelumnya serat sudah dibuat tiga ukuran panjang yaitu: 20 mm, 40 mm, dan 60 mm. Ukuran benda uji dibuat berdasarkan standar uji tarik (ASTM D 638), uji flexure (ASTM D 790) dan uji impact (ISO-179). Nilai paling tinggi uji tarik 30,750 MPa, modulus elastisitasnya 9400 MPa. Nilai maksimum tegangan flexure 138 MPa dan nilai paling tinggi uji impact adalah 54,14 kJ/m2. Kesimpulan dari penelitian ini adalah hasil uji tarik, uji flexure dan uji impact sudah memenuhi standar plastic yang digunakan dashboard mobil.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0110.003
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.043
GPT teacher head0.350
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it