Improving K-Means Clustering Accuracy for Academic Success Investigation With Extreme Gradient Boosting Algorithm

Irma Darmayanti; Laily Farkhah Adhimah; Rizki Sadewo; Nurul Hidayati; Pungkas Subarkah

doi:10.24014/ijaidm.v7i1.26657

Improving K-Means Clustering Accuracy for Academic Success Investigation With Extreme Gradient Boosting Algorithm

Irma Darmayanti, Laily Farkhah Adhimah, Rizki Sadewo, Nurul Hidayati, Pungkas Subarkah

Abstract

Human Resources (HR) has a very important role in the development of the nation, so to improve the quality of human resources, education is needed. Education has a role in developing science, disseminating, socializing, and applying it. So that education is one of the important factors in advancing a nation. However, there are still many challenges in achieving quality education, especially in developing countries such as Indonesia, such as parental education level, socioeconomic status, and environmental conditions can also affect the quality of education and students' opportunities for academic success. The research methods used in this research are problem identification, data collection, data analysis, and evaluation. The results in this study are an increase in accuracy of 38.55% from the difference in the K-Means accuracy value of 14% resulting from the David Bounded Index and the use of the extreme gradient adaboost algorithm.

Keywords

Academic; Algorithm; Education; Extreme Gradient Adaboost; K-Means

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DOI: http://dx.doi.org/10.24014/ijaidm.v7i1.26657

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