Sistem Klasifikasi Kualitas Daging Ayam menggunakan Metode K-Nearest Neighbors berbasis Arduino - Zamaliq Zamaliq; Fitri Utaminingrum; Eko Setiawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
Chicken meat is one of the most abundant sources of animal protein consumed by the community. Chicken meat consumption needs will always increase due to several factors, namely, the price of chicken meat that is relatively affordable compared to beef, has good nutritional quality, and is easily processed into various types of cuisine. Chicken meat sellers in the market or on the side of the road sometimes their sales results are not fully sold in the hands of consumers for various economic reasons, storability and ignorance of the public using hazardous additives and preservatives may be done some examples of abuse on food products is the use of synthetic preservatives for example formalin and borax. In overcoming this problem the determination of the classification of tiren chicken meat, rotten chicken, and formalin chicken, then the right method is needed to do the classification. K-NN method can work independently on each object features to be classified. In this system, several components are used: Arduino Mega Mini microcontroller to process data and perform calculations, the TGS2602 sensor is useful for detecting aroma in chicken meat, the accuracy of the error generated by 3.42% is placed in a container, the Ph BNC Electrode sensor Probes with an accuracy error level of 25.89% are useful to measure acid base levels in chicken meat. For classification using the K-NN presentation method the accuracy was found to be 80.95%.