Decision Support System Design for Informatics Student Final Projects Using C4.5 Algorithm - Rafika Sari; Hasan Fatoni; Khairunnisa Fadhilla Ramdhania (PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic, 2023)
Academic consultation activities between students and academic supervisors are necessary to help students carry out academic activities. Based on the transcript of grades obtained, many students do not choose the appropriate final project/thesis specialization fields based on their academic abilities, resulting in a lot of inconsistencies between the course grades and the final project specialization fields. The purpose of this research is to minimize the subjectivity aspect of students in choosing their final project academic supervisors and minimize the inconsistencies between the course grades and the final project specialization fields. The method used in this research is classification data mining using the Decision Tree and C4.5 Algorithm methods, with the attributes involved being courses, course grades, and specialization courses. The C4.5 Decision Tree algorithm is used to transform data (tables) into a tree model and then convert the tree model into rules. The implementation of the C4.5 Decision Tree algorithm in the specialization field decision support system has been successfully carried out, with an accuracy rate of 70% from the total calculation data. The data used in this research is a sample data from several senior students in the Informatics program at Ubhara-Jaya. The results of the research decision support system can be used as a good recommendation for the Informatics program and senior students to direct their final project research. It is expected that further research will use more sample data so that the accuracy rate will be better and can be implemented in website or mobile-based applications.