PATH LOSS PREDICTION DENGAN MENGGUNAKAN RANDOM FOREST DAN MODEL COST-HATA PADA AREA JALUR BUSWAY KOTA PALEMBANG

FADLI, MUHAMMAD WAHYU and Oklilas, Ahmad Fali and Sukemi, Sukemi (2022) PATH LOSS PREDICTION DENGAN MENGGUNAKAN RANDOM FOREST DAN MODEL COST-HATA PADA AREA JALUR BUSWAY KOTA PALEMBANG. Undergraduate thesis, Sriwijaya University.

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Abstract

Path loss is a phenomenon in which attenuation occurs in a wireless network when transmitting from transmitter to receiver due to environmental field conditions. In order to achieve efficieny in telecommunication design, accurate and efficient calculations are required. Machine learning – based path loss prediction models, Random Forest and Cost – Hata as an empirical propagation model for comparing accuracy levels, are employed in this final project research. Machine learning – based path loss models have a low complexity with very high predictability. The data was collected through the drive test method in Palembang, South Sumatra, Indonesia, especially the Transmusi busway area with corridor 5 on the 4G network. From the research conducted, it is obtained that the prediction accuracy of Random Forest with the validation of the MAPE error values is better when compared to Cost – Hata.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Prediksi path loss, Drive Test, Machine Learning, Random Forest, Cost - Hata, MAPE.
Subjects:	H Social Sciences > HE Transportation and Communications > HE9713-9715 Cellular telephone services industry. Wireless telephone industry Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television > TK5103.2.S83 Wireless communication systems Wireless LANs
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Mr. Muhammad Wahyu Fadli
Date Deposited:	23 May 2022 02:56
Last Modified:	23 May 2022 02:56
URI:	http://repository.unsri.ac.id/id/eprint/70283

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