Open AccessClassification of medicine characteristic using Super Vector Machine (SVM) at Palopo regional public Hospital Sawerigading
Author(s) -
N Nirsal,
Solmin Paembonan,
Fajar Novriansyah Yasir,
Vicky Bin Djusmin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1833/1/012028
Subject(s) - support vector machine , artificial intelligence , computer science , machine learning , dimension (graph theory) , structured support vector machine , function (biology) , supervised learning , pattern recognition (psychology) , data mining , artificial neural network , mathematics , evolutionary biology , pure mathematics , biology
One of the implementation of machine learning in medical world is to analyze medical dataset. Medical dataset used in this research was by using medicine dataset. Support Vector Machine Method is classification method of supervised learning, its algorithm works by using nonlinear mapping to change the data of real training into higher dimension. Selection of SVM Method is as solution to classify the characteristics of medicine. This method has function to make some similar medicines to be a group of certain data. The aim of this research was to obtain classification model which has high accuracy or small error in conducting classification of medicine data. Based on testing conducted, medicine classification using SVM produced accuracy=0,87.