Classification of human development index using particle swarm optimization based on support vector machine algorithm

Abstract Human Development Index (HDI) is the comparative of life expectancy, education and standard of living to all countries. Human Development Index used as an indicator to assess the quality of the construction. Human Development Index may also be used to classify the city or state whether a country of developed countries, developing countries, or the state of underdeveloped and as well as to gauge the effects of economic policy on the quality of life. In the study is done capability of classifications Human Development Index in Indonesia. Methods Used to know Classifications of Human Development Index this is using Support Vector Machines algorithms base Particle Swarm Optimization. Support Vector Machine algorithms based Particle Swarm Optimization is a-method that has the capacity for the Classification of Human Development Index data. In research was built model of Support Vector Machines algorithms based Particle Swarm Optimization. Results from the human development index is in the country or province 24 96 data not be in class, very high with human development index is at the high is 952, data while in the medium is 2018 data and there are at the level of low 201 data with an accuracy to 96.26 %, weighted mean recall 97.74 %, weighted mean precision 99.09.