Sistem Cerdas Klasifikasi Gejala Awal COVID-19 dan Influenza Menggunakan Metode Support Vector Machine

Sandra, Bella Aprilia and Sabita, Hary (2024) Sistem Cerdas Klasifikasi Gejala Awal COVID-19 dan Influenza Menggunakan Metode Support Vector Machine. Skripsi thesis, Institut Informatika dan Bisnis Darmajaya.

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Abstract

Self-Diagnosis means deciding by yourself what disease you are suffering from based on the knowledge you have or the information obtained related to the complaints (White & Horvitz, 2009). How to classify the early symptoms of COVID-19 and Influenza so there will be no mistake in self-diagnosis. The purpose of this research is to produce a classification between the COVID-19 virus and Influenza based on the patient''s early symptoms data using Support Vector Machines method. In this research, the data collection method used are a literature study conducted by reading and citing some notes from supporting libraries and documentation by collecting information, compiling and analyzing documents both written, photographed and electronic (Faedah, 2016). Based on Smart System Classification of Early Symptoms of COVID-19 and Influenza using Support Vector Machine Method, it can be concluded that SVM model is able to classify the early symptoms of COVID-19 and Influenza which can be seen if the results of medical diagnoses are not confirmed, the patient can be diagnosed only has Influenza, while if the results of the medical diagnosis show suspected Covid and Probable Covid, the patient still has to get an examination from the laboratory and if the results of the medical diagnosis are confirmed, it can be preconcerted that the patient is positive of COVID-19 virus.From the conclusions that have been described, suggestions are given for the further development of Smart System for Classification of Early Symptoms of COVID-19 and Influenza to be able to increase the number of datasets in order to make a better accuracy of the model and create an interface design for system so it can be used by both medical personnel and the wider community. Key words: COVID-19, SVM, Influenza, Classification, Self-Diagnosis

Item Type: Thesis (Skripsi)
Subjects: Ilmu Komputer
eSkripsi
Divisions: Skripsi/TA & PKPM/KP - Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Bella Aprilia Sandra
Date Deposited: 31 May 2024 04:15
Last Modified: 31 May 2024 04:15
URI: http://repo.darmajaya.ac.id/id/eprint/16292

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