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All Journal Scientific Journal of Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknoinfo JOURNAL OF INFORMATICS AND COMPUTER SCIENCE INCODING: Journal of Informatics and Computer Science Engineering Mejuajua Journal of Renewable Energy, Electrical, and Computer Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) Al'Adzkiya International of Computer Science and Information Technology Journal
Muhathir, Muhathir
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Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Other

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Journal : Scientific Journal of Informatics

 1 
Utilization of SVM Method and Extraction of GLCM Features in Classifying Fish Images with Formalin Muhathir, Muhathir; Wanti, Eka Pirdia; Pariyandani, Ayu; Idrus, Syed Zulkarnain Syed; Lubis, Andre Hasudungan
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.26806

Abstract

Purpose: Fish is a type of animal protein that can be consumed by humans to supplement protein in the body. Due to the fact that there is an abundance of fish in Indonesia, traders often experience losses because of rotting fish. A small proportion of traders tricked the buyers by mixing fish with formaldehyde to preserve fish in order to prevent fish spoilage until it can be consumed.  Thus, every fish buyer must be aware of fraud by traders. Methods: To be able to find out that the fish has been mixed with formalin, the solution offered is computerized by utilizing the GLCM feature extraction as information extraction on the fish image and the SVM method as a classification method. Result: The results showed an average accuracy of 0.784, precision of 0.799, recall of 0.784, and f-measure of 0.781. Novelty: The effect of the SVM classification method on the performance measurement of the model is not too big compared to previous studies, but it is better. 
Utilization of SVM Method and Extraction of GLCM Features in Classifying Fish Images with Formalin Muhathir, Muhathir; Wanti, Eka Pirdia; Pariyandani, Ayu; Idrus, Syed Zulkarnain Syed; Lubis, Andre Hasudungan
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.26806

Abstract

Purpose: Fish is a type of animal protein that can be consumed by humans to supplement protein in the body. Due to the fact that there is an abundance of fish in Indonesia, traders often experience losses because of rotting fish. A small proportion of traders tricked the buyers by mixing fish with formaldehyde to preserve fish in order to prevent fish spoilage until it can be consumed.  Thus, every fish buyer must be aware of fraud by traders. Methods: To be able to find out that the fish has been mixed with formalin, the solution offered is computerized by utilizing the GLCM feature extraction as information extraction on the fish image and the SVM method as a classification method. Result: The results showed an average accuracy of 0.784, precision of 0.799, recall of 0.784, and f-measure of 0.781. Novelty: The effect of the SVM classification method on the performance measurement of the model is not too big compared to previous studies, but it is better. 
Co-Authors Al Khowarizmi Albar, Rizka Dwipayana, Mahendar Ermita Wulandari, Tika Fadli, MHD. Fajar Alry Fadlisyah Fadlisyah Fauzi Fauzi Fitra , Akbario Gultom, William Habib Satria Idrus, Syed Zulkarnain Syed Juliansyah Putra Tanjung Lubis, Andre Hasudungan Maghfirah Maghfirah Maizana, Dina Maizana, MT, Dina Marpaung, Febriady Moerni, Saufa Yardha Mungkin, Moranaim Nasution, Annisa Noor, Fredy Nurul Khairina Pariyandani, Ayu Purba, Sentia Ovania Rahman Aldori, Yopan Rizki Muliono, Rizki Sibarani, Theofil Tri Saputra Simanjuntak, Juan Siregar, Erlina Siregar, Muhammad Fadlan Sitopu, Essay Puspita Susilawati, Susilawati Syafitri Rambe, Yunita Syahputra, Dinur Syuhada, Rahmad Tampubolon, Moulando Wanti, Eka Pirdia Wibawa, M. Bayu Yahya, Yanawati Yahya, Yanawati Binti Zebua, Meniati Zuhar Musliyana, Zuhar zulfikar sembiring, zulfikar