Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm
Dublin Core
Title
Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm
Subject
inclusive student; education; decision support system; ID3 algorithm; classification
Description
Inclusive student education has become one of the most important agendas for UNESCO and the Indonesian government.
Developing inclusive children's education is critical to adjust their abilities while attending school. However, most parents and
educators who assist students in selecting their future secondary school after finishing primary school are frequently not aware
of their genuine ability. The problem is mainly because the decision is not based on objective assessments like IQ, average and
mental scores. In this study, we aims to create a school-type decision support system using data mining as a factor analytic
approach in extracting rules for the knowledge model. The system uses some variables as the basic principles for building
school-type classification rules using the ID3 decision tree method. This system can also assist educators in making decisions
based on existing graduate data. Evaluation showed that the proposed system produced an accuracy of 90% by allocating 75%
of data for training and 25% for testing. The accuracy value from evaluation phase stated that the ID3 Decision tree algorithm
have a good peformance. This system also can dynamically create new decision trees based on newly added datasets. Further
research is expected to have more variable and more dynamic system that can have more accurate result for the inclusive
student classification of secondary school.
Developing inclusive children's education is critical to adjust their abilities while attending school. However, most parents and
educators who assist students in selecting their future secondary school after finishing primary school are frequently not aware
of their genuine ability. The problem is mainly because the decision is not based on objective assessments like IQ, average and
mental scores. In this study, we aims to create a school-type decision support system using data mining as a factor analytic
approach in extracting rules for the knowledge model. The system uses some variables as the basic principles for building
school-type classification rules using the ID3 decision tree method. This system can also assist educators in making decisions
based on existing graduate data. Evaluation showed that the proposed system produced an accuracy of 90% by allocating 75%
of data for training and 25% for testing. The accuracy value from evaluation phase stated that the ID3 Decision tree algorithm
have a good peformance. This system also can dynamically create new decision trees based on newly added datasets. Further
research is expected to have more variable and more dynamic system that can have more accurate result for the inclusive
student classification of secondary school.
Creator
Rizal Prabaswara, Julianto Lemantara, Jusak Jusak
Source
http://jurnal.iaii.or.id
Publisher
Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association
Date
October 2023
Contributor
Sri Wahyuni
Rights
ISSN Media Electronic: 2580-0760
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Rizal Prabaswara, Julianto Lemantara, Jusak Jusak, “Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm,” Repository Horizon University Indonesia, accessed February 3, 2026, https://repository.horizon.ac.id/items/show/10123.