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Ulva Febriana
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Penyakit Typhoid Fever (TF) dan Dengue Haemorhagic Fever (DHF) dengan Menerapkan Algoritma Decision Tree C4.5 (Studi Kasus : Rumah Sakit Wilujeng Kediri) Ulva Febriana; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fever is a rise in body temperature is higher than usual. Fever is not a disease, but the initial symptoms of a person affected by the disease. There are many diseases caused by fever, such as Typhoid Fever and Dengue Haemorragic Fever. Both diseases when observed clinically will be difficult to distinguish them. Because the two diseases almost have the same symptoms and if there is an error in diagnosing it will cause a fatal thing in the patient. Typhoid Fever disease is a fever caused by Salmonella Typhi bacteria that spread throughout the body and Haemorragic Fever Dengue fever caused by Aedes Aegypti mosquito bites. To overcome this, then made a classification system of disease diagnosis Typhoid Fever and Dengue Haemorragic Fever based on symptoms possessed by patients by applying desicion tree algorithm C4.5. Accuracy obtained by Typhoid Fever (TF) and Dengue Haemorhagic Fever (DHF) classification system by k-folds cross validation test showed the highest accuracy value on 5-fold cross validation with accuracy of 91,875% using 32 data test and Training data of 128 data. The results of the 4th test on 5-fold cross validation test resulted in the highest accuracy of 97%. While the analysis by conducting 16-fold cross validation test of the test data of 10 data and training data of 150 data, obtained the result of the test value of 100% on the 2nd, 3rd, 4th, 6th, The 9th, the 11th, the 12th and the 16th. Although the 100% accuracy value obtained in this test is numerous, the average accuracy of the 16-fold cross validation test is still below the average score of accuracy obtained by testing 5-fold cross validation.
Co-Authors Bayu Rahayudi Muhammad Tanzil Furqon