The Influence of Transformational Education Prediction on Softskills of Madrasa Student using Data Mining

The Influence of Transformational Education Prediction on Softskills of Madrasa Student using Data Mining

Authors

  • Andin Aprila Sari Program and Partnership, Google Developer Student Club
  • Annisa Sugi Pramesty Program and Partnership, Google Developer Student Club
  • Asma Zulfiah Malik Program and Partnership, Google Developer Student Club
  • Dini Nurul Haq Al-Hidayah Program and Partnership, Google Developer Student Club
  • Laela Shintia Alviani Program and Partnership, Google Developer Student Club
  • Rifka Alia Assyifa Program and Partnership, Google Developer Student Club

DOI:

https://doi.org/10.15575/kjrt.v1i1.157

Keywords:

data mining, education, k-nearest neigbor, madrasa, naive bayes, soft skills

Abstract

Currently, transformative education is oriented towards students' independence in solving a problem they face. In other words, transformative education has its own influence on the soft skills of students. This research was conducted with the aim of providing predictions regarding the effect of transformative education on the soft skills possessed by students. The subjects in this study were students of Madrasah Aliyah Negeri 2 Bandung, ranging from grade 10 to grade 12. The research method used was the Naïve Bayes and K-Nearest Neighbor algorithm by taking datasets from an independent survey that had been carried out previously. The Naïve Bayes and K-Nearest Neighbor algorithms themself are included in supervised learning and can be used to predict with a high degree of accuracy. Supervised learning is one of the existing methods in machine learning by means of labeling the data trained by the machine. Testing the data using the Naïve Bayes and K-Nearest Neighbor algorithm obtains predictions that transformative education affects students' soft skills and produces a very high level of accuracy for the Naïve Bayes algorithm, namely 98% of the 100 existing datasets and accuracy of the K-Nearest Neighbor is 76,67%.

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Published

2023-06-01

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