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

HAFIS, MUHAMMAD and Sukemi, Sukemi and Oklilas, Ahmad Fali (2023) ANALISA PATH LOSS PREDICTION MENGGUNAKAN PEMODELAN MACHINE LEARNING DAN MODEL PROPAGASI DI KOTA PALEMBANG. Undergraduate thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Path Loss, Machine Learning, Model Propagasi
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Muhammad Hafis
Date Deposited:	07 Jul 2023 02:25
Last Modified:	07 Jul 2023 02:25
URI:	http://repository.unsri.ac.id/id/eprint/114965

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