Classification Model Development Student Academic Eligibility In Capstone Project Course Enrollment Use C4.5 Decision Tree Algorithm

Abstract

Capstone Project course is an important aspect in the implementation of higher education to ensure that students have met the academic requirements and are ready to complete the final project. The process of determining eligibility is generally based on several criteria, such as the number of semester credit units (SKS) taken, Grade Point Average (GPA), and completion of prerequisite courses. This study aims to analyze the application of the Decision Tree algorithm using the C4.5 method in classifying student eligibility to take the Capstone Project course . The C4.5 method was chosen because it is able to form a classification model based on relevant attributes and produces decision rules that are easy to understand and interpret. The research stages include collecting student academic data, data preprocessing, attribute selection, forming a decision tree based on the Gain Ratio value , the results of the study are expected to produce a classification model that is able to determine student eligibility consistently based on predetermined academic criteria. The model can then be used as a basis for developing a decision support system to assist study programs in evaluating student eligibility more objectively, efficiently, and transparently. Thus, the application of the C4.5 algorithm is expected to support the improvement of the quality of academic governance and provide a basis for more structured decision-making in the implementation of the Capstone Project course .

Keywords : C4.5, Classification , Capstone Project , System Decision Support