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All Journal Techne : Jurnal Ilmiah Elektroteknika
Nauval Dwi Primadya
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination Nauval Dwi Primadya; Adhitya Nugraha; Sahrul Yudha Fahrezi; Ardytha Luthfiarta
Techné : Jurnal Ilmiah Elektroteknika Vol. 23 No. 2 (2024)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31358/techne.v23i2.435

Abstract

The security of Internet of Things devices is a factor that must be considered because device damage and data theft can occur. Internet of Things devices are very useful in various sectors, such as health, transportation, and industrial sectors. Attacks on Internet of Things devices increase every year. To overcome this, it is necessary to take a research approach with machine learning. The dataset used is CIC IoT Attacks 2023 from the University Of New Brunswick. To be able to produce good data, it is necessary to do random under sampling as a way to overcome data imbalance. Then, modeling is done using the KNN algorithm, Random Forest, Logistic Regression, Adaboost, And Perceptron. The result of this research is that random forest has the best accuracy result of 99.73%. From these results, it can be concluded that the random under-sampling technique can improve the accuracy of data imbalance.
Co-Authors Adhitya Nugraha Ardytha Luthfiarta Sahrul Yudha Fahrezi