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Classification of Patients with Polymorphism ß Fibrinogen Gene - 455G/A by Applying K-Nearest Neighbor Computation Method in Administering Fibrinogen Levels
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| Author:
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AL-KHOWARIZMI , MARISCHA ELVENY, RAHMAD SYAH
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| Abstract:
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The initial symptom of ischemic stroke is characterized by the presence of beta fibrinogen gene polymorphism -455 G/A, which to relieve fibrinogen in the human body. Fibrinogen levels that are given must match the size of hemoglobin (Hb), hematocrit (Ht), leukocytes, blood sugar levels (KGD), cholesterol, high density Lipoprotein (HDL), low density Lipoprotein (LDL). So that in order to make it easier in making decisions, a classification is needed which is one of several data mining techniques. The classification commonly used in the medical field is the K-Nearest Neighbor (K-NN) algorithm. The classification carried out by K-NN passes through resistance training and testing then searches for the K value with Euclidean distance where the paper classifies patients with Polymorphism beta fibrinogen gene -455 G / A with 136 datasets divided into 100 for training data and 36 testing data. Then at the testing stage, the accuracy measurement was carried out with MAPE and got the result1, 025725%. The MAPE value is the error percentage value at the testing stage so that the classification process in the field of Medicine and Health is only a support in decision making, not absolute for decision making.
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| Keyword:
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Classification, Fibrinogen, Polymorphism of Beta Fibrinogen Gene - 455 G / A, K-NN.
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2021.13.01.640
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| Download:
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