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All Journal SELODANG MAYANG
Lisa Afrinanda
Program Studi Sistem Informasi, Universitas Islam Indragiri, Tembilahan
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Nursing Public Health Transportation Other

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PERANCANGAN SISTEM KLASIFIKASI UDANG BERACUN PADA JENIS UDANG TENGGEK MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN). Lisa Afrinanda; Ilyas Ilyas
Selodang Mayang: Jurnal Ilmiah Badan Perencanaan Pembangunan Daerah Kabupaten Indragiri Hilir Vol 6 No 1 (2020): JURNAL SELODANG MAYANG
Publisher : Badan Perencanaan Pembangunan Daerah Kabupaten Indragiri Hilir Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47521/selodangmayang.v6i1.140

Abstract

Shrimp is one of the seafood which is nutrient-rich needed by the body. However, due to the frequent case of the infected Tenggek-shrimp appeared, it makes people beware to consume it. The classification of Tenggek-shrimp by using image processing of the computer be able to classify the types of shrimp whether poisonous or not. The data mining techniques can be used to classify shrimp based on RGB colors (red, green, blue) and texture (energy, contrast, correlation, homogeneity). The class of Tenggek-shrimp is divided into two, The fresh Tenggek-shrimps that are caught naturally (Class A) and the poisoned Tenggek-shrimps that are caught by using the poison (Class B). The method used in this study is K-Nearest Neighbor (K-NN). This classification system is expected to help the people in selecting good and safe Tenggek-shrimp for consumption. Based on the evaluation results using the holdout method, obtained an average accuracy of 63% with an accuracy of identification of toxic tenggek shrimp of 71.66%, and the accuracy of identification of natural fresh shrimp is about 60%.
Co-Authors Ilyas, Ilyas