APLIKASI M-LEARNING MATA PELAJARAN BAHASA INDONESIA MENGGUNAKAN ANDROID STUDIO
Bibliographic record
Abstract
Perkembangan teknologi khususnya pada ponsel pintar (smartphone) sangat pesat, apalagi dengan munculnya ponsel pintar (smartphone) yang menggunakan sistem operasi android yang mengakibatkan menurunnya ketertarikan manusia terhadap buku sebagai media untuk belajar. M-Learning merupakan aplikasi yang diterapkan sebagai media belajar, baik untuk memahami materi belajar ataupun sebagai sarana untuk mengasah pengetahuan terhadap materi belajar yang telah di dapat.Aplikasi ini merupakan aplikasi berbasis android yang dibangun menggunakan android studio. Aplikasi ini dapat menampilkan materi belajar Bahasa Indonesia untuk SMPN 4 Muara Teweh kelas VI,VII, dan IX. Aplikasi ini mampu menampilkan halaman latihan soal pilihan ganda dimana soal-soal yang diberikan menggunakan sistem acak atau random yang dapat dikerjakan langsung oleh pengguna dan setelah selesai mengerjakan soal latihan, pengguna bisa langsung mengetahui berapa skor yang di dapat, dan skor tertinggi baru yang dicapai. Kata Kunci : android studio, bahasa indonesia, m-learning
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.025 |
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".