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PEMODELAN FUZZY DECISION TREE C4.5 UNTUK KLASIFIKASI PENYAKIT JANTUNG MENGGUNAKAN KOMBINASI FUNGSI KEANGGOTAAN LONCENG DAN KURVA-S
Heart disease is the leading cause of death in the world for the last 10 years. Classification of heart disease is very important in the diagnosis of cardiovascular disease. The purpose of this study was to classifying and determine the level of accuracy in heart disease. In this study, the existing data were analyzed using a fuzzy decision tree C4.5 algorithm using a membership function combined with a bell curve and an s-curve, with the step formation of fuzzy sets on the training data, then forming a tree by the C4.5 algorithm generated rules. The rules that have been formed had the testing process using the mamdani inference method. The result of defuzzification from mamdani inference can determine the classification output class. The testing results of the classification with the fuzzy decision tree algorithm C4.5 have an highest accuration value, which is 80,24% in the fuzziness control threshold by 75% to 80% with leaf decision threshold value of 3%.
Inventory Code | Barcode | Call Number | Location | Status |
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2207005118 | T84157 | T841572022 | Central Library (Referens) | Available but not for loan - Not for Loan |
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