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All Journal Berkala Fisika Indonesia : Jurnal Ilmiah Fisika, Pembelajaran dan Aplikasinya JINOP (Jurnal Inovasi Pembelajaran) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Physics: Theories and Applications Krea-TIF: Jurnal Teknik Informatika Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Novel Engineering Science and Technology
Sabarudin Saputra
IKIP MUHAMMADIYAH MAUMERE
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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Implementation of Naïve Bayes for Fish Freshness Identification Based on Image Processing Sabarudin Saputra; Anton Yudhana; Rusydi Umar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 3 (2022): Juni 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (746.63 KB) | DOI: 10.29207/resti.v6i3.4062

Abstract

Consumption of fish as a food requirement for the fulfillment of community nutrition is increasing. This was followed by an increase in the amount of fish caught that were sold at fish markets. Market managers must be concerned about the dispersion of huge amounts of fish in the market in order to determine the freshness of the fish before it reaches the hands of consumers. So far, market managers have relied on traditional ways to determine the freshness of fish in circulation. The issue is that traditional solutions, such as the use expert assessment, demand a human physique that quickly experiences fatigue. Technological developments can be a solution to these problems, such as utilizing image processing techniques classification method. Image processing with the use of color features is an effective method to determine the freshness of fish. The classification method used in this research is the Naive Bayes method. This study aims to identify the freshness of fish based on digital images and determine the performance level of the method. The identification process uses the RGB color value feature of fisheye images. The stages of fish freshness identification include cropping, segmentation, RGB value extraction, training, and testing. The classification data are 210 RGB value of extraction images which are divided into 147 data for training and 63 data for testing. The research data were divided into fresh class, started to rot class, and rotted class. The research shows that the Naive Bayes algorithm can be used in the process of identifying the freshness level of fish based on fisheye images with a test accuracy rate of 79.37%.
Co-Authors Aang Anwarudin Adi Jufriansah Anton Yudhana Azmi Khusnani Fitrah Juliansyah hikmatiar, hamzarudin Kristina Theresia Leto Nurfitriah Safrudin Nursina Sya'bania Rezki Ramdhani Rusydi Umar Tanti Diyah Rahmawati Yudhiakto Pramudya