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Record W4389358935 · doi:10.36595/jire.v6i2.819

PERANCANGAN JARINGAN WIFI DENGAN MENGGUNAKAN TOP DOWN NETWORK DESIGN

2023· article· id· W4389358935 on OpenAlexaboutno aff
Fritz Gamaliel, P. Yudi Dwi Arliyanto

Bibliographic record

VenueJurnal Informatika dan Rekayasa Elektronik · 2023
Typearticle
Languageid
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesComputer scienceArt

Abstract

fetched live from OpenAlex

Sebagian besar indekos menyediakan fasilitas internet WiFi kepada para penghuninya. Salah satu kelebihan WiFi daripada LAN adalah tanpa kabel sehingga fleksibel dan menjangkau pengguna bergerak. Namun ada kemungkinan-kemungkinan yang dapat mempengaruhi kualitas sinyal WiFi salah satunya adalah tembok pembatas. Pemilik indekos Calgary E1 membangun tembok pembatas antara rumah bagian depan dengan rumah bagian belakang yang menyebabkan sinyal WiFi dari router ISP yang ada di rumah bagian depan tidak terpancarkan dengan maksimal ke semua kamar penghuni yang ada di rumah bagian belakang. Hal tersebut dibuktikan dengan pemeriksaan kualitas sinyal WiFi dari kamar penghuni rumah bagian belakang mendapatkan -82dbm. Sedangkan penghuni indekos Calgary E1 bagian belakang juga membutuhkan fasilitas internet salah satunya untuk menunjang kegiatan WFH (Work From Home). Pada penelitian ini digunakan top down network design untuk mengembangkan jaringan existing yang ada pada indekos Calgary E1. Pada desain jaringan fisik, ditambahkan sebuah perangkat WiFi TL-WR841HP pada rumah bagian belakang. Berdasarkan hasil penelitian yang telah dilaksanakan, terbukti bahwa semua kamar penghuni yang ada di rumah bagian belakang telah dapat menggunakan WiFi melalui perangkat WiFi TL-WR841HP. Hal tersebut dibuktikan dengan pemeriksaan kualitas sinyal WiFi dari kamar penghuni rumah bagian belakang dimana kamar nomor 3 mendapatkan -66dbm dan kamar nomor 4 mendapatkan -49dbm.

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 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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.008
Science and technology studies0.0030.001
Scholarly communication0.0030.004
Open science0.0080.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.004

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 head0.042
GPT teacher head0.291
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations0
Published2023
Admission routes1
Has abstractyes

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