Skripsi

ANALISA PATH LOSS PREDICTION MENGGUNAKAN PEMODELAN MACHINE LEARNING DAN MODEL PROPAGASI DI KOTA PALEMBANG

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Penilaian

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The prediction of path loss plays a crucial role in the planning and construction of communication technology networks. Path loss itself describes the attenuation that occurs in signals transmitted from the transmitting antenna to the receiving antenna. In this research, the Random Forest machine learning model and the Okumura-Hata propagation model were used to seek accuracy. The objective of this study was to find the best accuracy value based on Root Mean Square Error (RMSE), then analyze and compare the accuracy results obtained to determine the model that is more relevant and accurate in making predictions. The data used for this study was obtained by conducting a drive test along the Trans Musi busway route corridor 5 in Palembang City. The results of this research yielded RMSE values for each model, and Random Forest outperformed the Okumura-Hata model in terms of prediction performance.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307005603	T114965	T1149652023	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1149652023

Publisher

Indralaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiii, 64 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.607

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Sistem Komputer
Jaringan komunikasi

Specific Detail Info

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Statement of Responsibility

FIRA

Other version/related

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