Application Of Data Mining Using The Neural Network Backpropagation Method To Determine The Eligibility Of Smart Indonesia Program Scholarship Recipients
Keywords:
Data Mining, Classification, Neural Network BackpropagationAbstract
The government provides students from impoverished or vulnerable backgrounds with financial assistance, educational opportunities, and expanded access through this scholarship program. Underprivileged students at SD Negeri 04 Lembah Melintang are still selected manually by each homeroom instructor through the collection of student and student parent data. The dataset utilized is comprised of 407 data points, including 326 training data and 81 test data, collected from pupils at SD Negeri 04 Lembah Melintang between 2022 and 2024. The objective of this research is to develop, execute, and evaluate the Neural Network Backpropagation method for the classification of PIP scholarship eligibility determination. The following attributes are included in this study: the status of the father, the status of the mother, the income of the father and the income of the mother, the job of the father and the job of the mother, distance from home, number of dependents, and means of transportation, with the classification results Eligible and Ineligible. This research produces an accuracy rate of 95%, with Recall 90%, Precision 100% and F1-Score of 94%.
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