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All Journal Jurnal Inspiration Creative Information Technology Journal ILKOM Jurnal Ilmiah JurTI (JURNAL TEKNOLOGI INFORMASI) Angkasa: Jurnal Ilmiah Bidang Teknologi Informasi Interaktif Jurnal Tecnoscienza Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Explore
Emha Taufiq Luthfi
Universitas Amikom Yogyakarta
Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Physics Other

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Journal : Informasi Interaktif

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KLASIFIKASI JENIS REMPAH-REMPAH BERDASARKAN FITUR WARNA RGB DAN TEKSTUR MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR Kaharruddin Kaharruddin; Kusrini Kusrini; Emha Taufiq Luthfi
Informasi Interaktif Vol 4, No 1 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

 Indonesia is a country famous for its spices wealth, spices have many benefits such as cooking and can also be used as medicine, but nowadays there are many Indonesian people who cannot distinguish each type of spices especially the rhizomes that will be used due to their shape quite similar, even though the selection of the right type of spices in accordance with the needs is very important because the spices used for cooking or medicine have different taste and efficacy, therefore the use of computer technology needs to be used to facilitate and accelerate humans in conducting classifications, this research classifies spices based on RGB and Texture colors using K-Nearest Neighbor Algorithm and distance measurement using Euclidean Distance, from 30 times the test experiment gets the result that the level of truth with K = 1 is 76%, K = 3 is equal to 67% and K = 5 by 63%. From these results it is known that based on GE colors and computer textures can classify spices but with a fairly low accuracy so that further development is needed such as adding form features. Keywords: classification, spices, K-Nearest Neighbor.
Co-Authors Abdullah Ardi Arham Rahim Arief Setyanto Bambang Soedijono WA Berlilana Berlilana Dedi Tri Hermanto Ema Utami Fiyas Mahananing Puri Kaharuddin Kanafi Kanafi Kusrini Kusrini M. Suyanto Pranata, Caraka Aji Rizky Handayani Sigit Suryono Stabit Handoyo Supriyati Supriyati Veny Cahya Hardita Victor Saputra Ginting Wahyu Adie Saputro