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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Jeffry Atur Firdaus
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Pengukur Kesegaran Daging Sapi menggunakan Metode K-Nearest Neighbor (K-NN) dengan Fitur Penambahan Data Latih berbasis EEPROM Jeffry Atur Firdaus; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 5 (2020): Mei 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the food products that is in demand by the people of Indonesia because it has high nutritional value. 70% air, 20% protein, 9% fat and 1% ash. The freshness of beef affects the quality of beef. Simple characteristics of beef that is still fresh is the color of fresh red meat, soft flesh fiber and yellow fat. The quality loss in beef can be marked by changes in color, taste and smell. This is caused by the development of microorganisms in beef. Eating beef contaminated by microorganisms can cause food poisoning and other health problems. In this research, a system can classify beef quality using the K-Nearest Neighbor algorithm and Arduino nano EEPROM. This system uses beef RGB color input using TCS3200 sensor, gas quality to measure the intensity of NH3/ammonia gas using the MQ135 sensor and push-button as a medium of user interaction with the system. Further sample data is classified using K-Nearest Neighbor on Arduino Nano using training data stored on EEPROM. The results of the classification of "fresh" "medium" or "rotten" grade beef will be shown on the LCD. In addition, data on the EEPROM can also be added and removed for system development through a menu on the LCD. The average computation time obtained in the system to classify beef quality is 117ms and the classification system with 81 training data on 27 test data obtains an accuracy of up to 85%.
Co-Authors Dahnial Syauqy Eko Setiawan