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@article{J.Gauss16946, author = {Chainur Hasibuan and Moch. Mukid and Alan Prahutama}, title = {KLASIFIKASI DIAGNOSA PENYAKIT DEMAM BERDARAH DENGUE (DBD) MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM) BERBASIS GUI MATLAB}, journal = {Jurnal Gaussian}, volume = {6}, number = {2}, year = {2017}, keywords = {Dengue Hemorrhagic Fever (DHF), Classification, Support Vector Machine (SVM), hold-out, Kernel Function.}, abstract = { Dengue Hemorrhagic Fever (DHF) is a disease caused by the bite of infected Aedes mosquito by one of the four types of dengue virus with clinical manifestations of fever, muscle aches or joint pain which followed by leukopenia, rash, thrombocytopenia and hemorrhagic diathesis. There are six criteria for determining and catagorizing a positive or negative dengue patients, the variable gender of the patient, the patient's age, the increase in hemoglobin (Hb), increased hematocrit (Hct), the level of platelet and leukocyte levels.Based on these criteria, data of positive and negative catagorized patient will be classified by Support Vector Machine (SVM) using Matlab software. The concept of classification with SVM define as a search for the best hyperplane which serves as a divider of two classes of data in the input space. Kernel function is used to convert the data into a higher dimensional space to allow separation. In order to determine the best parameters of kernel function, hold-out method is used. In the classification by SVM method, 96.4286% obtained as the best accuracy value by using polynomial kernel function. Keywords: Dengue Hemorrhagic Fever (DHF), Classification, Support Vector Machine (SVM), hold-out, Kernel Function. }, issn = {2339-2541}, pages = {171--180} doi = {10.14710/j.gauss.6.2.171-180}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/16946} }
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Keywords: Dengue Hemorrhagic Fever (DHF), Classification, Support Vector Machine (SVM), hold-out, Kernel Function.
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