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All Journal Jurnal Ilmiah Kursor Jurnal Sains Matematika dan Statistika Indonesian Journal of Artificial Intelligence and Data Mining JISA (Jurnal Informatika dan Sains) Abdimasku : Jurnal Pengabdian Masyarakat Unnes Journal of Mathematics IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Pengabdian Sosial
Putri, Aina Latifa Riyana
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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

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Early Detection of COVID-19 Disease Based on Behavioral Parameters and Symptoms Using Algorithm-C5.0 Joko Riyono; Aina Latifa Riyana Putri; Christina Eni Pujiastuti
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 1 (2023): Maret 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i1.22074

Abstract

The spread of COVID-19 disease has continued since it was first discovered at the end of 2019 until now. Transmission of COVID-19 is very fast, including through close contact through droplets and through the air. Therefore, early detection of COVID-19 is very important for patients and also those around them to be able to fight the COVID-19 pandemic because if patients get proper and fast treatment, then other people around them will be protected. In this study, an analysis of the classification of decision making for COVID-19 detection was carried out based on behavioral parameters and symptoms that could trigger exposure to COVID-19 using the C5.0 algorithm, followed by measuring the performance of the model using the Confusion Matrix. The C5.0 algorithm is a decision tree-based data mining method. The results of the C5.0 algorithm use a comparison of training data and test data of 70:30. After going through the Confusion Matrix test, an accuracy value of 98% is obtained which indicates that the resulting classification is very good, so that the resulting model can be used for early detection of COVID-19 patients.
Co-Authors Amalia, Raisha Ayu, I Gusti De Bashiran, Himam Brian Nugraha Wiyono Christina Eni Pujiastuti Dewanti, Anggun Dody Prayitno Gabriella F Pandiangan Harnoko, Sri Namira Putri Joko Riyono Joko Riyono Kania, Putri Emas Mega Yuliani Ramme Nurkaromah Dwidayati, Nurkaromah Prameswari, Mayesq Pujiastuti, Christina Eni Puspa, Sofia Debi Putri, Dianing Novita Nurmala Setyaningsih, Destina Bekti Silaen, Ferdinan Supriyadi Supriyadi Supriyadi Syahid Nur Khomsyi Syahida, Shafa Tamara, Donna Nur Zahra, Indy Aurellia Az