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Record W2891897114 · doi:10.31980/jpetik.v4i1.8

PERANCANGAN SISTEM INFORMASI REKAM MEDIS RAWAT JALAN MENGGUNAKAN PENDEKATAN BERORIENTASI OBJEK DI RUMAH SAKIT KHUSUS GIGI DAN MULUT (RSKGM) KOTA BANDUNG

2018· article· id· W2891897114 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

VenueJURNAL PETIK · 2018
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHumanitiesMedicineGynecologyArt

Abstract

fetched live from OpenAlex

Rekam medis kedokteran gigi adalah suatu dokumen yang sistematis mengenai riwayat perawatan kesehatan gigi seorang pasien oleh sarana pelayanan kesehatan. Rumah Sakit Khusus Gigi dan Mulut (RSKGM) Kota Bandung yang mengkhususkan diri pada pelayanan gigi dan mulut merupakan Rumah Sakit Khusus tipe C, rumah sakit ini telah menggunakan Sistem Informasi Manajemen Rumah Sakit (SIMRS), namun rekam medis masih berupa lembaran-lembaran berkas yang harus diisi kembali baik oleh pasien yang mengisi identitas, maupun dokter/perawat yang telah selesai melakukan pemeriksaan dan tindakan. Selain itu, masalah yang sering terjadi adalah berkas yang sudah dikirimkan ke poli sering terjadi kesalahan dalam pencarian, terkadang berkas tidak ada atau pun belum sampai ke poli sehingga membuat pasien menunggu cukup lama dalam menerima pelayanan rumah sakit. Perancangan sistem informasi rawat jalan ini menggunakan pendekatan berorientasi objek dengan penggambaran menggunakan alat bantu Unified Modelling Language (UML) dan menggunakan bahasa pemrograman PHP dan Database MySQL. Diharapkan melalui perancangan ini proses pelayanan rekam medis dapat lebih efektif dan efisien.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0040.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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