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PENERAPAN FUNGSI KEANGGOTAAN NON LINIER PADA METODE FUZZY DECISION TREE ITERATIVE DICHOTOMISER 3 (ID3) UNTUK KLASIFIKASI PENYAKIT JANTUNG
According to data from World Health Organization (WHO) in 2021, an estimated 17,9 million people die from heart disease, which is the leading cause of death globally. This research discussed the classification of heart disease using the fuzzy decision tree iterative dichotomiser 3 (id3) method with a non-linear membership function. Making a decision tree that generates the rules, will be used in determining whether a patient has heart disease or not. The data used is data on heart disease patients from an academic medical center, namely Cleveland Clinic Foundation in the form of age, tresbps, chol, thalach, oldpeak, sex, chest pain, fasting blood sugar, restecg, exang, slope, ca, thal, and num. This research begins with making of fuzzy sets on numerical variable training data with non-linear membership function, making a decision tree with id3 algorithm, testing the rules on testing data using Mamdani inference then calculate the accuracy. That process is carried out on several different ratios of training data and testing data with FCT values by 70% and 80%. The highest accuration value is 85,19% with data ratio by 90:10 and FCT value by 75% to 80% having the same accuracy. The accuracy value means that out of 100 patients, 85 patients can be classified correctly by the resulting model.
Inventory Code | Barcode | Call Number | Location | Status |
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2207004946 | T82510 | T825102022 | Central Library (Referens) | Available but not for loan - Not for Loan |
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