PENERAPAN METODE DECISION TREE MENGGUNAKAN ALGORITMA C4.5 UNTUK DIAGNOSIS PENYAKIT DIABETES MELITUS
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
GAFFAR, ANDI WIDYA MUFILA
Kuswardani, Dwina
Agtriadi, Herman Bedi
Kuswardani, Dwina
Agtriadi, Herman Bedi
Subject
Teknik Informatika
Datestamp
2020-02-11 08:21:05
Abstract :
Diabetes is one of a group of chronic disease characterized by high-level of the blood sugar levels where pancreas unable to produce insulin as needed. Many diabetic people diagnose after experiencing complications. In fact, if diagnose is done before, then the treatment can do rapidly and the complication is avoided. One of the method is use for clasification of diabetes melitus disease dataset is called decision tree method using c4.5 algorithm. The calculation of c4.5 algorithm is calculated by enthropi and gaininf information from data set such as age, pregnancy, pedigree, glucose, blood pressure and body weight which can be produce the rule then implemented into application for diagnosing diabetes melitus disease and doing data test. The source of data research are from UCI machine learning repository : Indian Pima Diabetes Dataset conducted by the National Institute of Diabetes and Digestive and Kidney (NIDDK) in United States of America. Based on the classified results the use of C4.5 Algorithm showing that the levels of accuracy is 75,6% and is effectly used to predict of the diagnosis diabetes mellitus disease.
Diabetes is one of a group of chronic disease characterized by high-level of the blood sugar levels where pancreas unable to produce insulin as needed. Many diabetic people diagnose after experiencing complications. In fact, if diagnose is done before, then the treatment can do rapidly and the complication is avoided. One of the method is use for clasification of diabetes melitus disease dataset is called decision tree method using c4.5 algorithm. The calculation of c4.5 algorithm is calculated by enthropi and gaininf information from data set such as age, pregnancy, pedigree, glucose, blood pressure and body weight which can be produce the rule then implemented into application for diagnosing diabetes melitus disease and doing data test. The source of data research are from UCI machine learning repository : Indian Pima Diabetes Dataset conducted by the National Institute of Diabetes and Digestive and Kidney (NIDDK) in United States of America. Based on the classified results the use of C4.5 Algorithm showing that the levels of accuracy is 75,6% and is effectly used to predict of the diagnosis diabetes mellitus disease.
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