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All Journal IJoICT (International Journal on Information and Communication Technology) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Community Development Journal: Jurnal Pengabdian Masyarakat REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Intan Nurma Yulita
Universitas Padjadjaran
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Public Health

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Journal : Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)

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Machine Learning Prediction of Time Series Covid-19 Data in West Java, Indonesia Intan Nurma Yulita; Afrida Helen; Mira Suryani
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 2 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i2.58505

Abstract

In 2019, the COVID-19 pandemic appeared. There have been several efforts to curb the spread of this virus. West Java, Indonesia, employs social restrictions to prevent the spread of this disease. However, this method destroyed the economy of the people. If no instances were detected in the region, the World Health Organization (WHO) authorized the social restrictions to be relaxed. If the government lifts the social limitation, the decision must also consider the potential of future confirmed instances. By utilizing machine learning, it is possible to forecast future data. This work utilized the following algorithms: linear regression (LR), locally weighted learning (LWL), multi-layer perceptron (MLP), radial basis function regression (RBF), and support vector machine (SVM). The study investigated daily new instances of COVID-19 in West Java, Indonesia, from March 2, 2020, to October 15, 2020. The RBF algorithm was the best in this investigation. Mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and relative absolute error (RAE) were 48.85, 89.73, 88.67, 62.99, and 60.88, respectively. The RBF prediction model may be proposed to the government of West Java for assessing data on COVID-19 instances, particularly in social restriction management. It is anticipated that West Java would have a minimum of 275 new cases every day for the following 30 days beginning on October 16, 2020. Consequently, the easing of societal limitations requires careful consideration.
Co-Authors Afrida Helen Aniati Murni Arymurthy Anindya Apriliyanti Pravitasari Fajar Indrayatna Fauzan Akmal Hariz Gumgum Darmawan Ihda Anwari Ino Suryana Mira Suryani Mohamad Ivan Fanany Mulya Nurmansyah Ardisasmita Mulya Nurmasnsyah Ardisasmita Triyani Hendrawati Yeni Rizka