RANCANG BANGUN SISTEM DETEKSI KANDUNGAN DAGING BABI PADA PRODUK BAKSO MENGGUNAKAN KAMERA SMARTPHONE BERBASIS MACHINE LEARNING

Nabila Luthfi Nadhifah, NIM.: 21106020019 (2025) RANCANG BANGUN SISTEM DETEKSI KANDUNGAN DAGING BABI PADA PRODUK BAKSO MENGGUNAKAN KAMERA SMARTPHONE BERBASIS MACHINE LEARNING. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

This research aims to design, manufacture, and test a system for detecting pork content in meatball products using a smartphone camera based on machine learning. The system was developed through hardware assembly and software design using MATLAB. Images are processed through the following stages: input, augmentation, preprocessing, feature extraction, and clustering using three algorithms K-Means, Gaussian Mixture Model (GMM), and GMM with Gaussian Filtering. The testing was conducted by calculating the accuracy and precision of each algorithm. The results show an accuracy of 80% for K-Means, 54% for Gaussian Mixture Model (GMM), and 94% for GMM with Gaussian Filtering. Precision of 100%, 71%, and 93%. Based on these results and in accordance with the SNI ISO/IEC 17025:2017 standard, GMM with Gaussian Filtering was found to have the best performance. This study is expected to contribute to the development of halal product assurance instrumentation systems, especially for processed meat products such as halal and non-halal meatballs.

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