Andalas Journal of Electrical and Electronic Engineering Technology
Vol. 2 No. 2 (2022): November 2022

The Use of Artificial Neural Networks (ANN) in the Chayote Chips Dough Mixer

Roza Susanti (Politeknik Negeri Padang)
Zas Ressy Aidha (Politeknik Negeri Padang)
Surfa Yondri (Politeknik Negeri Padang)
Sir Anderson (Politeknik Negeri Padang)
Tri Oktaviandra (Politeknik Negeri Padang)

Article Info

Publish Date
30 Dec 2022

Abstract

This study uses a backpropagation neural network to determine the evenness of the chayote chip dough. The Tcs3200 Color Sensor mounted on the stirrer alt is used as a sensor to determine the color of the chayote emping dough. A regression score of 1 indicates that the input and target data match in the test results of the artificial neural network, which has an objective error (MSE) value of 0.0096306 achieved in the 313th epoch. Changes in RGB color readings on the TCS sensor from min values ??<40 and max values>52 in mixing dough are influenced by distance and light intensity which will be converted in the form of frequency.

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Journal Info
Andalas Journal of Electrical and Electronic Engineering Technology
Website

Abbrev

ajeeet

Publisher

Universitas Andalas

Subject

Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

Description

Electrical power and energy: Transmission and distribution, high voltage, electrical energy conversion, power electronics and drive. Telecomunication and Signal Processing: Antenna and wave propagation, network and systems, Modulation and signal processing, Radar and sonar, Radar imaging; Radio, ...