PENGEMBANGAN MODUL PUBLIC USERS PADA SISTEM INFORMASI KEARSIPAN AKADEMIK ELEKTRONIK (Studi Action Research Pengembangan Modul Public Users Pada Sistem Informasi Kearsipan Akademik Elektronik (SiAMEL) Di Fakultas Ilmu Komunikasi Universitas Padjadjaran)
Bibliographic record
Abstract
This research aims to know the needs of student information which can be met from SiAMEL. This research also aims to develop the database, and display the output from the application of the Public Users on SiAMEL module. The method used in this study is Action Research. Data collection techniques by way of observation, interview, note the field and study the literature. This research has resulted in the development of SiAMEL that can meet the needs of student information as Public Users among others: Data Lecturer, Data institution/ Institutions for MORNING, data proposed problem, as well as data about the schedule. Through this research has been done on the conversion some tables that are adjusted with the needs of the Public Users SiAMEL. In addition, page view early SiAMEL become open to public Users and changes to the navigation buttons (menu) SiAMEL. Some of the output SiAMEL changed some details that adjusted with the status of access authority SiAMEL, whether as administrator or as a Public Users. Penelitian ini bertujuan untuk mengetahui kebutuhan informasi mahasiswa yang dapat dipenuhi dari SiAMEL. Selain itu juga penelitian ini bertujuan untuk mengembangkan database, tampilan serta output dari aplikasi Modul Public Users pada SiAMEL. Metode yang digunakan pada penelitian ini adalah Action Research . Teknik pengumpulan data yaitu dengan cara observasi, wawancara, catatan lapangan, serta studi literatur. Penelitian ini telah menghasilkan pengembangan SiAMEL yang dapat memenuhi kebutuhan informasi mahasiswa sebagai Public Users antara lain: Data Dosen, Data Instansi/ Lembaga untuk PKL, data Usulan Masalah, serta data tentang Jadwal Sidang. Melalui penelitian ini telah dilakukan pengubahan pada beberapa tabel yang disesuaikan dengan kebutuhan Public Users SiAMEL. Selain itu, tampilan halaman awal SiAMEL menjadi terbuka untuk Public Users serta perubahan pada navigasi (menu) SiAMEL. Beberapa output SiAMEL diubah beberapa detail yang disesuaikan dengan status otoritas akses SiAMEL, apakah sebagai Administrator atau sebagai Public Users .
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.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".