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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Ivan Ricardo Jiwanata
Universitas Multi Data Palembang
Computer Science & IT

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Perbandingan Tingkat Akurasi Daging Bakso Berdasarkan Jarak Potret Menggunakan Fitur GLCM Dengan Metode JST Ivan Ricardo Jiwanata; Dedy Hermanto
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 4 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i4.5515

Abstract

The texture of meatballs is one of the parameters used by the community to determine the quality of meatball products. The problem is to determine the accuracy comparison of meatball meat using four different portrait distances using the JST backpropagation method with GLCM feature extraction. Training data and test data are extracted using GLCM features, and then JST training is conducted using 17 training functions. The portrait distances used are 10 cm, 13 cm, 15 cm, and 18 cm, with 5 neurons, 10 neurons, and 20 neurons, resulting in three different architectures. For each training function, there are five experiments for each architecture. Based on the research results, it can be concluded that the traincgb training function, which uses 5 neurons, achieves fairly good recognition results at a portrait distance of 15 cm with a total accuracy of 95.5%, precision of 88%, and recall of 95%.
Co-Authors Dedy Hermanto