Author:
Afrianto E,Suseno J E,Warsito B
Abstract
Abstract
The research intends to create an application program which is able to make analysis data in a school to classify students who is entitled to accept Indonesian Smart Card. It was a government program that aims to finance school education free of charge, for children from poor families. Problems arose when the distribution to students, some children from poor families did not get it but rich families actually got it. Analysis and the right way are needed so that the distribution can be right on target to eligible students. This study used a decision tree method with C4.5 algorithm to classify students who are entitled to receive the Indonesian Smart Card. This application is developed with C4.5 algorithm to determine the decision tree method. Research data was carried out at Junior High School One of Jatibarang, Brebes. Data record of 300 students, with 240 as training data while 60 as testing data. From the test results were accuracy was 97%, it is proven this method has a high accuracy so that the application can help the decision makers solved the distribution problems to eligible students. The impact is that poor students will get the right to receive Indonesian Smart Card.
Reference17 articles.
1. The poverty reduction strategy papers: An analysis of a hegemonic link between education and poverty;Tarabini;International Journal of Educational Development,2012
2. Do more educated neighbourhoods experience less property crime? Evidence from Indonesia;Nguyen;International Journal of Educational Development,2019
3. Education, development and poverty reduction: A literature critique;Cremin;International Journal of Educational Development,2012
4. Decision support system of scholarship grantee selection using data mining;Sugiyarti;International Journal of Pure and Applied Mathematics,2018
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A poverty index prediction model for students based on PSO-LightGBM;Annals of Operations Research;2023-11-03
2. Selecting of Pet Adopters using C4.5 Decision Tree Model Algorithm;2022 2nd International Conference in Information and Computing Research (iCORE);2022-12