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All Journal Algoritme Jurnal Mahasiswa Teknik Informatika
Kevita Titany Suhanto
Universitas Multi Data Palembang
Computer Science & IT

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Identifikasi Kadar Ikan Pada Pempek Dengan Fitur LBP Dan Metode Pengenalan SVM Kevita Titany Suhanto; Gasim Gasim
Jurnal Algoritme Vol 3 No 1 (2022): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i1.3363

Abstract

The main ingredients commonly used by the community in making pempek are ground fish and sago flour. The people of Palembang usually make pempek into several variants such as egg pempek, pempek pistel, pempek curly, pempek submarine, pempek roasted, pempek lenggang, etc. In the previous study, the dataset was 4 types of pempek lenjer with different levels of snakehead fish and flour, where each comparison was equal to 200 grams. The comparisons are: 1 snakehead fish to 1 sago flour, 1.5 snakehead fish to 1 sago flour, 2 snakehead fish to 1 sago flour, 1 snakehead fish to 2 sago flour. In this study, the dataset used is a photo image using a 2MP camera resolution which is the best dataset from previous research (Amatullah, 2021) which obtained an accuracy rate of 23.33% and the number of test data recognition was 56 out of 240 test data. Then this research was conducted using LBP feature extraction and the introduction of the Support Vector Machine method which resulted in an accuracy rate of 22.92%.
Co-Authors Gasim