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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Jeffrey Simanjuntak
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Penyakit Infeksi Saluran Pernapasan Akut (ISPA) dengan menerapkan Metode Fuzzy K-Nearest Neighbor Jeffrey Simanjuntak; Edy Santoso; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 11 (2021): November 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Acute Respiratory Infection (ARI) is an infection of the respiratory tract, this respiratory disease causes symptoms such as cough, cold, and fever. Acute Respiratory Infection disease can be very dangerous, ARI will spread throughout the respiratory system if not treated quickly. Groups of people who are susceptible to this disease are those who have weak body divine power, namely those who have immune system disorders, people with old age, and children. ARI can easily attack children because children have an immature immune system. In this study, the Fuzzy K-Nearest Neighbor algorithm is used on the system for classify ARI diseases. In this study, Acute Respiratory Infection was classified into mild Acute Respiratory Infection and severe Acute Respiratory Infection. The clarification process in this research consists of normalization, Euclidean distance, then Fuzzy K-Nearest Neighbor classification. The results of the test using 10 test data and 50 training data, obtained an accuracy of 90% at K = 10, then tested the effect of the K value on the accuracy at K between 2 to 10 with the highest result at K = 7 which is 90%. The accuracy value obtained by the system remains the same until K = 10, which is 90%.
Co-Authors Edy Santoso Marji Marji