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All Journal Scientific Journal of Informatics J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Wanti, Eka Pirdia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

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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. 
Pengidentifikasian Citra Ikan Berformalin Dengan Menggunakan Metode Multilayer Perceptron Wanti, Eka Pirdia; Muhathir, M
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.342

Abstract

The richness of Indonesia's natural resources in the marine area, makes the sea an ecosystem of the existing diversity of fish. Fish is one of the types of animal protein that can be consumed by humans. Fish also contains essential vitamins and amino acids needed by the body with a biological value of up to 90% with binding tissue that makes it easier for the body to digest them. With the large number of fish that fishermen get per day, fish traders also have to make the fish they sell durable, one of which is by preserving fish with formaldehyde. Formlain is also a dangerous substance if used for food, this is because this substance can cause death if consumed long term. So that the existing problems encourage the author to identify formalin fish images using the MLP (Multilayer Perceptron) method which is a fairly reliable method in the image detection process because the search process is very directional (paying attention to backpropagation) where the feature extraction used is GLCM ( Gray Level Co-Occurrence Matrix). From this study, it was found that the Accuracy value was 62%. Where the error rate is 50%. Recall is 85%, application is 39%, precisson is 58% and F1 score is 71%.
Pengidentifikasian Citra Ikan Berformalin Dengan Menggunakan Metode Multilayer Perceptron Wanti, Eka Pirdia; Muhathir, M
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1126.224 KB) | DOI: 10.30645/j-sakti.v5i1.342

Abstract

The richness of Indonesia's natural resources in the marine area, makes the sea an ecosystem of the existing diversity of fish. Fish is one of the types of animal protein that can be consumed by humans. Fish also contains essential vitamins and amino acids needed by the body with a biological value of up to 90% with binding tissue that makes it easier for the body to digest them. With the large number of fish that fishermen get per day, fish traders also have to make the fish they sell durable, one of which is by preserving fish with formaldehyde. Formlain is also a dangerous substance if used for food, this is because this substance can cause death if consumed long term. So that the existing problems encourage the author to identify formalin fish images using the MLP (Multilayer Perceptron) method which is a fairly reliable method in the image detection process because the search process is very directional (paying attention to backpropagation) where the feature extraction used is GLCM ( Gray Level Co-Occurrence Matrix). From this study, it was found that the Accuracy value was 62%. Where the error rate is 50%. Recall is 85%, application is 39%, precisson is 58% and F1 score is 71%.
Co-Authors Idrus, Syed Zulkarnain Syed Lubis, Andre Hasudungan Muhathir, M Muhathir, Muhathir Pariyandani, Ayu