CORE NETWORK EPC REDIMENSIONING 4G LTE DI WILAYAH REGIONAL SULAWESI
Bibliographic record
Abstract
Core network dibutuhkan sebagai penyedia content layanan kepada user. Proses dimenssioning core network 4G LTE di wilayah regional Sulawesi dengan melakukan studi kasus di PT. Telekomunikasi Selular (Telkomsel) hingga tahun 2022. Pada jaringan 4G LTE dengan CSFB diperlukan minimum elemen jaringan 9 MSS, 2 HSS, 5 S/PGW, dan 5 MME. Untuk dimensioning interface dapat mengetahui bandwidth minimum yang harus disediakan. Interface control plane terdiri dari S6a, S11, S10, S1-MME, S5/S8 memerlukan 0,4015 Gbps dan kebutuhan bandwidth interface user plane terdiri dari S5/S8 user plane, S1-U dan SGi adalah 20,075 Gbps. Dari hasil dimensioning element dan interface jaringan menghasilkan topologi jaringan EPC yang dapat diimplementasisan di wilayah regional Sulawesi. Untuk membentuk sistem yang handal dari segi teknikal dan biaya dengan topologi full connection mesh menggunakan pooling sistem. Penentuan link transport dari EPC menghasilkan dua skenario topologi planning core. Sehingga, infrastruktur topologi tersebut dapat menguntungkan baik dari sisi pelanggan maupun operator. Sehingga untuk biaya infrastruktur core network berbanding dengan efisiensi bandwidth yang disediakan dengan memilih rekomendasi link transport untuk skenario yang kedua.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".