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All Journal Innovation in Research of Informatics (INNOVATICS)
Syarah, May Siti
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Klasifikasi Penderita ISPA Menggunakan Metode Naive Bayes Classifier Syarah, May Siti; Wati, Masna; Puspitasari, Novianti
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 1 (2022): Maret 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i1.4427

Abstract

Information related to the classification of ARI disease suffered by the community in a public health is essential. This is because the public health is one of the community health centers that is a reference for treatment for the community. Public health must identify the right type of ARI disease so that treatment for ARI sufferers can be given optimally. This study classified the data of patients with ARI in a public health based on the determining factors, namely the disease suffered, age, and period of stay. Classification is carried out using the Naive Bayes Classifier method with the Confusion Matrix testing method. The results of applying the Naive Bayes Classifier method to patient data resulted in three types of ARI, namely mild, moderate and severe. The highest number of ARI patients is severe ARI. The results of the Confusion Matrix test that have been carried out prove that this method has an accuracy of 93.33% so it is suitable for use to classify ARI diseases.
Co-Authors Puspitasari, Novianti Wati, Masna