Umi, Murdika and Yessi, Mulyani Penilaian karya ilmiah untuk artikel “ Identifikasi Kualitas Buah Tomat dengan Metode PCA (Principal Component Analysis) dan Backpropagation”. Fakultas Teknik Universitas Lampung.

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Abstract

Principal component analysis is a method used in analyzing datasets to summarize their main characteristics. This PCA method reduces the dimension of the dataset by projecting each data point onto only the first few principal components to obtain lower dimensional data while maintaining as much variation of the data as possible. In this study, the PCA method was used to project image data in order to obtain feature extraction data with smaller dimensions. Furthermore, the Backpropagation method is applied to carry out the identification process. The dataset used is 30 data consisting of 10 test images data and 20 training data. From the simulation, it can be concluded that the PCA method applied has succeeded in reducing the dimensions of the data. Identification of tomato fruit quality using the Back-propagation method shows the level of accuracy with an accuracy of 76.7%. it indicates that this system has been running well.

Item Type: Other
Subjects: Q Science > Q Science (General)
Divisions: Fakultas Teknik (FT) > Prodi Teknik Elektro
Depositing User: Umi Murdika
Date Deposited: 16 Feb 2022 01:16
Last Modified: 16 Feb 2022 01:16
URI: http://repository.lppm.unila.ac.id/id/eprint/39337

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