Classification System for Comments and Suggestions of the People towards the Government Project with Artificial Intelligence Methods

Abstract

People participation system for public comments and suggestions on government projects, using web-board for public participation is variety and the text data cannot be interpreted. The messages are not clearly categorized without summary of comments and suggestions data on government projects in order to demonstrate public responses. This article aims to present the classification system for public comments towards the government project with artificial intelligence methods. This study used experimental research methodology with the model evaluation. The four indicators including precision value, recall value accuracy value and F-Measure value were conducted to measure. The study indicated that the model evaluation details are as follows: three data characteristics are categories of comments and suggestions indicated that precision = 0.88, recall = 0.86, accuracy = 86.69% and F-Measure = 0.87; project type indicated that precision = 0.87, recall = 0.85, accuracy = 85.23% and F-Measure = 0.85; and government agencies or provinces indicated that precision = 0.86, recall = 0.83, accuracy = 83.94% and F-Measure = 0.84.