PELATIHAN PEMBUATAN LAPORAN KEUANGAN SEDERHANA PADA PETANI JAHE MERAH DI BATURETNO
Bibliographic record
Abstract
Abstrak Baturetno Wonogiri, di wilayah tersebut terdapat banyak petani yang fokus pada budidaya jahe merah. Dapat diketahui bahwa jahe merah merupakan tanaman obat yang memiliki banyak manfaat diantaranya digunakan untuk menghangatkan badan, menyembuhkan sakit kepala, mencegah radang usus, menguatkan kekebalan tubuh, mengobati batuk, mengatasi mual dan menambah nafsu makan, menurunkan berat badan serta menjaga kondisi jantung. Dengan banyaknya manfaat jahe merah di atas membuat petani di Baturetno Wonogiri untuk terus membudidayakannya, bahkan petani jahe merah di Baturetno Wonogiri sudah bekerja sama dengan PT. Sidomuncul dalam memelihara kualitas jahe merahnya. Dengan adanya hubungan kerja sama antara petani jahe merah diharapkan petani jahe merah di Baturetno Wonogiri mampu memahami cara penyusunan laporan keuangan secara sederhana. Hal ini bertujuan agar petani jahe merah di Baturetno Wonogiri mampu mengelola keuangan dengan baik. Fenomena yang terjadi pada petani jahe merah Baturetno Wonogiri masih banyak petani yang belum memahami laporan keuangan secara sederhana, sehingga hal ini yang menjadi landasan bagi tim Pengabdian Kepada Masyarakat STIE AUB Surakarta untuk memberikan kontribusi terhadap pemahaman laporan keuangan dengan baik.Kata Kunci : Jahe Merah, Baturetno Wonogiri, Laporan Keuangan Sederhana
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.014 |
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".