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CCIT Journal
Article . 2019 . Peer-reviewed
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Deteksi Tingkat Kesegaran Daging Ayam Menggunakan K-Nearest Neighbor

Authors: Kusrini Kusrini; M. Afriansyah; Irfan Purwanto;

Deteksi Tingkat Kesegaran Daging Ayam Menggunakan K-Nearest Neighbor

Abstract

The high demand for meat and the limited availability of meat on the market, make the price of meat become expensive and more and more traders are mixing rotten meat into fresh meat. To avoid risk, the public as consumers must be aware and know the characteristics of rotten meat and the difference with fresh meat. This study developed a fresh meat detection device using the TCS-230 RGB color sensor. The tool works by measuring the composition of RGB colors in identified meat and comparing with the reference composition of fresh meat RGB color. K-Neirest Neighbor as a method for introducing the freshness of chicken meat tested. The input used in the K-Neirest Neighbor is in the form of RGB color values ??obtained from the color sensor.In this study, meat freshness was tested using TCS-230 color sensor with an accuracy rate of 87% with a positive precision of 92% and negative precision of 67%

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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