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Fahmi Izhari
Universitas Pembangunan Pancabudi Medan
Education Public Health

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COMPARISON OF AIR QUALITY DATA ACCURATION USING DECISION TREE AND NEURAL NETWORK METHOD Fahmi Izhari; Hanna Willa Dhany
Jurnal Ipteks Terapan Vol 14, No 2 (2020): JIT
Publisher : LLDIKTI Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22216/jit.2020.v14i2.5389

Abstract

In research conducted on the Neural Network classification model that has been tested has an accuracy of 82.04% with a classification error rate of 17.96%. Meanwhile, the Decision Tree classification model has an accuracy rate of 99.38 %% with a classification error rate of 0.62%. Based on the test results from the two classification models, it can be concluded that the success of the Decision Tree can be used as a reference to improve the performance of the classification model's accuracy compared to the Neural Network Backpropagation model.
Co-Authors Hanna Willa Dhany