Classification of medicine characteristic using Super Vector Machine (SVM) at Palopo regional public Hospital Sawerigading
N Nirsal, Solmin Paembonan, Fajar Novriansyah Yasir, Vicky Bin Djusmin · Journal of Physics Conference Series · 2021
Abstract 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.