Iterative Dichotomiser Three (Id3) Algorithm For Classification Community of Productive and Non-Productive

Abstract

One way to tackle poverty is to provide information about productive and non-productive communities in each rural. This is very beneficial for the government, especially in each rural regarding the classification of community data. This research aims to classify productive and non-productive people so that the government can prioritize assistance for people deemed necessary to be more creative in fulfilling their family's economy. The research method used is the Iterative Dichitomiser Three (ID3) algorithm to build a decision tree. The process in the decision tree is changing the shape of the data (table) into a tree (tree) and generating rules based on the highest Entropy and Gain values. The study's conclusion shows that this algorithm can be processed in a shorter time, with shorter decision rules and higher prediction accuracy, by displaying the highest gain value. The parameters used to consist of education, age, income, and employment status, which results in the following rule if higher education and high income, then the result is a productive society, whereas if high school education and low income, then the result is a non-productive society.