ANALISIS KINERJA SISTEM PEMBANGKIT LISTRIK TENAGA SURYA SEBAGAI PENGGERAK PROPELLER PADA PERAHU NELAYAN
Bibliographic record
Abstract
Indonesia sebagai negara yang terletak di wilayah garis Khatulistiwamemiliki potensi penyinaran 12 jam setiap hari sepanjang tahun. Semakin menipisnyacadangan minyak bumi membuat manusia harus mencari energi yang terbaharukan.Solar sel merupakan sebuah alat yang dapat mengkonversi energi cahaya menjadienergi listrik. Penggunaan solar sel telah berkembang dalam berbagai bidang industriantara lain sebagai pendorong kegiatan ekonomi dan bahkan kebutuhan transportasi.Pada penelitian ini, solar sel digunakan sebagai sumber penggerak perahumenggunakan motor dc. Motor dc yang digunakan 0,9 Hp dengan 5 pengaturankecepatan maju dan menggunakan perahu fiber kayu dimensi 8,2m x 0,75m x 0,7m.Hasil penelitian bahwa beban maksimum pada pengaturan kecepatan 5 dengan beban4 orang (265 kg). Kecepatan maksimum 6,37 km/jam dan dapat bertahan hingga 2jam 22 menit menggunakan baterai 100Ah. Dari pengujian, aplikasi ini dapatditerapkan dan bahkan dikembangkan dengan daya motor yang lebih besar.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".