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Record W3121242123 · doi:10.52643/jti.v6i2.1140

Monitoring Konektivitas Internet Dengan Load Balancing Menggunakan Metode Equal Cost Multi Path Pada SMK Yadika 12 Depok

2021· article· id· W3121242123 on OpenAlexaff
Toni Sukendar, Mohammad Ikhsan Saputro

Bibliographic record

VenueJurnal Teknologi Informasi · 2021
Typearticle
Languageid
FieldComputer Science
TopicIoT-based Control Systems
Canadian institutionsNicolet Chartrand Knoll (Canada)
Fundersnot available
KeywordsComputer scienceOperating systemThe InternetComputer networkLoad balancing (electrical power)Mathematics

Abstract

fetched live from OpenAlex

ABSTRAKKebutuhan akses internet untuk mencari informasi dan komunikasi dari hari ke hari semakin meningkat. Saat ini SMK Yadika 12 Depok menggunakan dua koneksi dari penyedia layanan internet yang berbeda untuk menjaga agar proses belajar mengajar dapat tetap berjalan dengan baik. Namun, pemanfaatan kedua koneksi Internet tersebut belum seimbang dan metode pengalihan jalur koneksi yang mengalami kendala masih dilakukan secara manual sehingga membutuhkan waktu yang cukup lama untuk proses pengalihan jalur tersebut. Oleh karena itu, tujuan penelitian ini adalah menerapkan teknik load balancing) dengan router mikrotik menggunakan metode Equal Cost Multi Path. Hasil pengujian menunjukkan jaringan kedua Lab SMK Yadika 12 Depok menjadi satu jaringan yang sama dan memiliki dua sumber access internet. Acces internet yang dilakukan oleh client akan dibebankan ke kedua ISP yang ada. Beban bandwith sudah ada pembatasan per client menjadi 512k pada saat mengunduh dan dan mengunggah file. Kata kunci : ECMP, load balancing, mikrotik

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.034
GPT teacher head0.264
Teacher spread0.230 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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