2022
DOI: 10.30812/matrik.v22i1.1880
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The Improvement of Artificial Neural Network Accuracy Using Principle Component Analysis Approach

Arief Hermawan,
Adityo Permana Wibowo,
Akmal Setiawan Wijaya

Abstract: An important problem in a classification system is how to get good accuracy results. A way to increase the accuracy of a classifier system is to improve the number of input data attributes. Improving the number of input data attributes can be done using the Principal Component Analysis (PCA) method. The aim of this research is to reduce the number of input data attributes to increase the accuracy in a mushroom classification system. The research method used in this study started from collecting datasets from K… Show more

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