KLASIFIKASI PENYAKIT CORONAVIRUS (COVID)-19 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION (PSO) DAN ALGORITMA NAÏVE BAYES

Minarni, Prilian Ayu (2022) KLASIFIKASI PENYAKIT CORONAVIRUS (COVID)-19 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION (PSO) DAN ALGORITMA NAÏVE BAYES. Masters thesis, Institut Informatika dan Bisnis Darmajaya.

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Abstract

Coronavirus (COVID) 19 disease was a contagious disease caused by the SARSCoV2 virus. Most of people were infected with the virus causing mild-to-moderate respiratory illness and were recovered without special treatment. The early detection to identify COVID19-infected people was through specimen collection e.g., Rapid Antigen Test and a Polymerase Chain Reaction (PCR) Test. The background of this research was that each of these efforts had its drawbacks. To be able to overcome this problem, a lot of researches had been carried out in computer science field. The objective of this research was generating better accuracy than the previous research. The method of this research was the feature selection and the Naïve Bayes Algorithm. The data was tested through K-Fold. This research had been conducted through Particle Swarm Optimization (PSO) and Naïve Bayes Algorithm to obtain better accuracy results than the previous research. The result of this research was that the level of accuracy was 97.17%, the level of precision was 93.79%, and the level of recall was 91.43%. The obtained value of the level of accuracy and precision was the highest value compared to the other K-Fold values, but the value of recall was 91.43% which was not better than the other K-Fold values. Keywords: Covid 19, Classification, PSO, Naïve Bayes

Item Type: Thesis (Masters)
Subjects: Ilmu Komputer
eTheses
Divisions: Pasca Sarjana > Magister Teknik Informatika
Depositing User: Prilian Ayu Minarni
Date Deposited: 05 Jan 2023 01:53
Last Modified: 05 Jan 2023 01:53
URI: http://repo.darmajaya.ac.id/id/eprint/10226

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