Klasifikasi Kualitas Wortel Menggunakan Metode K-Nearest Neighbor Berbasis Android

Farich Al Azami(1*), Aditya Akbar Riadi(2), E Evanita(3),


(1) Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muria Kudus
(2) Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muria Kudus
(3) Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muria Kudus
(*) Corresponding Author

Abstract


In several studies, many have produced various programs or applications specifically designed to identify plants, fruits, leaves or others based on the specified characteristics. Of the various kinds of fruits and vegetables, carrots are vegetables that have many benefits and are liked by the majority of people. So it is necessary to choose good quality fruit to produce quality products as well. However, so far, the selection of quality carrots is still using the manual method with the human sense of sight to determine good and bad quality carrots. . Image processing in this application uses the K-Nearest Neighbor (KNN) algorithm which is a method that classifies objects based on the learning data that is closest to the object. In the development of the carrot quality classification application, it is hoped that it can help farmers, industry, or the general public in sorting out good and efficient carrot quality. On the results of the classification using this classification system got a percentage of 74.19%

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References


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DOI: http://dx.doi.org/10.30645/jurasik.v7i1.413

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v7i1.413.g390

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