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All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Muhammad Ikhsan
Department of Computer Science, Faculty of Science and Technology, Universitas Islam Negeri Sumatera Utara, Medan, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Detection of Ripeness of Manggosteen Fruit Using Hsv Color Space Transformation Method Mhd. Furqan; Muhammad Ikhsan; Annafiah Dalimunthe
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i4.171

Abstract

Rapid advances in innovation in the PC field are increasingly making applications and exploration of image handling strategies created. Image processing has an important role in various fields. Image processing applications are concerned with image processing with regard to color transformation. In this case, the method of transforming the color space as part of the image processing helps in detecting the colors in the image and processing them. Color space is a mathematical model that describes the color represented in the number model. HSV color space is a color space composed of 3 components, namely Hue, Saturation, Value. Hue is related to purity (color pattern), Saturation is related to the saturation of the color, Value expresses the brightness level of the color. In this study, based on the results of testing using mangosteen fruit imagery to detect the type of ripeness by transforming RGB color space into HSV color space conducted using sample data as much as 60 fruit data consisting of 45 training samples consisting of 15 images of mangosteen fruit in each type of ripeness, and 15 test samples consisting of 5 samples of ripe mangosteen fruit,  5 samples of half-cooked mangosteen fruit and 5 samples of raw mangosteen fruit obtained success rate accuracy of 86.6%, so it can be concluded that the HSV Color Space Transformation method can be used to detect the ripeness of mangosteen fruit.
Detection of Ripeness of Manggosteen Fruit Using Hsv Color Space Transformation Method Mhd. Furqan; Muhammad Ikhsan; Annafiah Dalimunthe
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.82 KB) | DOI: 10.30645/ijistech.v5i4.171

Abstract

Rapid advances in innovation in the PC field are increasingly making applications and exploration of image handling strategies created. Image processing has an important role in various fields. Image processing applications are concerned with image processing with regard to color transformation. In this case, the method of transforming the color space as part of the image processing helps in detecting the colors in the image and processing them. Color space is a mathematical model that describes the color represented in the number model. HSV color space is a color space composed of 3 components, namely Hue, Saturation, Value. Hue is related to purity (color pattern), Saturation is related to the saturation of the color, Value expresses the brightness level of the color. In this study, based on the results of testing using mangosteen fruit imagery to detect the type of ripeness by transforming RGB color space into HSV color space conducted using sample data as much as 60 fruit data consisting of 45 training samples consisting of 15 images of mangosteen fruit in each type of ripeness, and 15 test samples consisting of 5 samples of ripe mangosteen fruit,  5 samples of half-cooked mangosteen fruit and 5 samples of raw mangosteen fruit obtained success rate accuracy of 86.6%, so it can be concluded that the HSV Color Space Transformation method can be used to detect the ripeness of mangosteen fruit.
Co-Authors Annafiah Dalimunthe Mhd. Furqan