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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muchamad Rafi Dharmawan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Pembeda Daging Sapi dan Daging Babi berdasarkan Warna dan Kadar Amonia menggunakan Metode Jaringan Syaraf Tiruan Berbasis Android Muchamad Rafi Dharmawan; Dahnial Syauqy; Gembong Edhi Setyawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Protein is a substance that is needed by humans to be able to carry out daily activities. Aside from being a source of energy, a lot of other benefits provided by the protein for the body of human. Beef is one of source by protein that's much favoured by the peoples. But, with the high interest making naughty seller take advantage of this situation by mixing pork with beef. These conditions occur because the lack of public knowledge about the difference between both of them coupled with the prices of beef relatively higher. This made the majority people of Indonesians are scared, especially Muslims. So we need a study of systems that can distinguish between beef and pork. With this research it's expected to be able to solve existing problems and minimize cheating by sellers and losses by consumers. This system is designed using TCS3200 color sensor and MQ135 gas sensor because in this study, parameters to distinguish two types of meat are color and ammonia levels. The results of the sensors are used as input for processing by Arduino Nano using Artificial Neural Network (ANN) method to get result of classification by system. The architecture of ANN used in this study consisted of 4 input neurons, 5 hidden layers, and 1 output layer. The main system will be only used for prediction process based on readings value of the sensor. The training process for getting weight values is running on other devices using MATLAB. The results of tests on 30 meat samples as test data produce an accuracy rate up to 90% with an average of computation time 45.3 millisecond.
Co-Authors Dahnial Syauqy Gembong Edhi Setyawan