Anggara AlFaridzi Tamba
Universitas Islam Negeri Sumatera Utara, Medan

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Implementasi Jaringan Syaraf Tiruan Backpropagation Pada Klasifikasi Grade Teh Hitam Muhammad Ikhsan; Armansyah Armansyah; Anggara AlFaridzi Tamba
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5312

Abstract

Black tea is the most widely produced type of tea in Indonesia, where Indonesia itself is the 5th largest black tea exporter in the world. According to the provisions of SNI-1902-2016, the quality requirements of black tea through appearance include the shape, size and weight (density), and the color of the black tea particles themselves. This study aims to determine the workings of the backpropagation method and the implementation of python on black tea grade classification, and to determine the level MSE of accuracy in the results of black tea grade classification using backpropagation. The model used in this study uses 4 input layers, 5 hidden layers, and 3 output layers. In the input layer, 4 input variables are used, namely shape, size, density, and color. The results of the classification using backpropagation with a number of iterations of 1000 iterations on the training data obtained an error of 0.096.