Pengujian Kontaminan pada Produk Peternakan Melalui Studi Kasus Laboratorium Terakreditasi

Testing for Contaminants in Livestock Products Through Accredited Laboratory Case Studies

Authors

  • Arya Dwiki Ramadhan Universitas Jenderal Soedirman

DOI:

https://doi.org/10.33369/pelastek.v4i2.41734

Keywords:

Machine Learning, Pengujian Kontaminan, Produk Peternakan, Laboratorium Terakreditasi, Keamanan Pangan

Abstract

Penelitian ini mengkaji penerapan machine learning (ML) dalam optimalisasi pengujian kontaminan pada produk peternakan, dengan fokus pada studi kasus laboratorium terakreditasi. Melalui tinjauan literatur komprehensif, studi ini mengungkapkan bahwa integrasi ML dalam pengujian laboratorium telah meningkatkan akurasi, efisiensi, dan kemampuan prediktif dalam deteksi kontaminan. Berbagai teknik ML, termasuk Random Forest dan Gradient Boosting, telah terbukti efektif dalam memprediksi keberadaan patogen dan mengoptimalkan proses pengujian. Studi ini juga membahas tantangan implementasi, standar regulasi, dan potensi pengembangan di masa depan. Hasil penelitian menunjukkan bahwa ML memiliki potensi signifikan untuk mentransformasi praktik laboratorium, meningkatkan keamanan pangan, dan memastikan kepatuhan terhadap standar regulasi dalam industri peternakan.

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Published

2025-06-23

How to Cite

Arya Dwiki Ramadhan. (2025). Pengujian Kontaminan pada Produk Peternakan Melalui Studi Kasus Laboratorium Terakreditasi: Testing for Contaminants in Livestock Products Through Accredited Laboratory Case Studies. JURNAL PENGELOLAAN LABORATORIUM SAINS DAN TEKNOLOGI, 4(2), 46–50. https://doi.org/10.33369/pelastek.v4i2.41734

Issue

Vol. 4 No. 2 (2024): November 2024

Section

Articles

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Copyright (c) 2025 Arya Dwiki Ramadhan

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