Comparative Analysis of Classification Methods of KNN and Naïve Bayes to Determine Stress Level of Junior High School Students

Authors

  • Yohanes Christopher Tapidingan Universitas Katolik De La Salle Manado
  • Debby Paseru Universitas Katolik De La Salle Manado

DOI:

https://doi.org/10.24002/ijis.v2i2.3035

Keywords:

Stres, Naïve Bayes, KNN, Akurasi, Perbandingan

Abstract

Stress is generally defined as a state where someone is mentally disturbed as the response to the adversity that he/she experiences. Junior High School students usually are not aware of the stress that they encounter. This research aims to compare two classification methods of KNN and Naïve Bayes to determine stress level. The data of this research were gathered from 254 respondents from Catholic Junior High School of Don Bosco Bitung. The tests of k-cross validation and percentage split from the data showed that Naïve Bayes method excelled KNN method. With k=3, KNN accuracy reached 86.61% at the highest and Naïve Bayes reached 87.40%. Meanwhile, based on percentage split test, the average of Naïve Bayes accuracy was higher than KNN with percentage of 88.31%. Moreover, for the precision and recall, Naïve Bayes was higher than KNN with 88.30% and 87.40% seen from the k-cross validation.

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Published

2020-02-26

How to Cite

Tapidingan, Y. C., & Paseru, D. (2020). Comparative Analysis of Classification Methods of KNN and Naïve Bayes to Determine Stress Level of Junior High School Students. Indonesian Journal of Information Systems, 2(2), 80–89. https://doi.org/10.24002/ijis.v2i2.3035