MétaCan
Menu
Back to cohort
Record W4384573791 · doi:10.59697/jsik.v6i2.188

Sistem Pendukung Keputusan Pemilihan Access Point Di Hotel Ibis Styles Medan Pattimura Menggunakan Metode MOORA

2022· article· id· W4384573791 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 Sistem Informasi Kaputama (JSIK) · 2022
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicDecision Support System Applications
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHumanitiesMathematicsComputer scienceArt

Abstract

fetched live from OpenAlex

Sistem pendukung keputusan adalah bagian dari sistem informasi berbasis komputer (termasuk sistem berbasis pengetahuan). Yang dipakai untuk mendukung pengambilan keputusan dalam suatu sistem. Sistem pendukung keputusan memberikan suatu keputusan yang bersifat semiterstruktur, dimana tidak seorang pun tau secara pasti bagaimana keputusan seharusnya dibuat.Pemilihan Access Point selalu memberikan kualitas yang terbaik kepada para IT untuk dipakai pada Hotel tersebut. Untuk mendapatkan kualitas yang terbaik maka para IT Hotel membutuhkan sebuah sistem pendukung keputusan. Pada penelitian ini penulis menerapkan metode Multi Objective Optimization On The Basic Of Ratio Analysis (MOORA Method)sebagai metode yang akan diterapkan di dalam sistem pendukung keputusan pemilihan Access Point dengan tidak terlalu banyak membuang waktu dalam memilih Access Point dan tentunya hasil pemilihan yang tersistem akan lebih efektif

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.719
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.004
Science and technology studies0.0050.000
Scholarly communication0.0070.010
Open science0.0050.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.004

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 head0.031
GPT teacher head0.272
Teacher spread0.241 · 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