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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
Aly, Moustafa H.
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Computer Science & IT Decision Sciences, Operations Research & Management

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Palm Oil Quality Based on Free Fatty Acid Using SVM Prayogi, Andi; Aly, Moustafa H.; Ikhwan, Ali; Pane, Muhammad Akbar Syahbana; Siregar, Ratu Mutiara
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24797

Abstract

Background: Palm oil is one of the key commodities in both the food and non-food industries, with its quality largely influenced by the level of Free Fatty Acid (FFA). Obejctive: High FFA content can reduce the stability and market value of the oil. Classify palm oil quality based on FFA levels using the Support Vector Machine (SVM) algorithm. Methods: FFA levels were measured across multiple samples with varying usage frequencies (0, 5, 7, and 9 cycles) using the alkalimetric titration method. The measured data was categorized as "Suitable" if FFA ≤ 0.3% and "Unsuitable" if it exceeded this threshold. The developed SVM model was trained using 70% of the data and tested with the remaining 30%. Results: Evaluation results indicate that the model achieved an accuracy of 95%, a precision of 92%, and a recall of 94%, demonstrating SVM's effectiveness in classifying data. Additionally, hyperplane visualization using PCA provided a clearer distinction between oil categories based on FFA levels. Conclusion: This study highlights that SVM can serve as an effective alternative for FFA-based palm oil quality classification. The implementation of this model is expected to enhance efficiency in the palm oil industry, particularly.
Co-Authors Ali Ikhwan Muhammad Akbar Syahbana Pane Prayogi, Andi Ratu Mutiara Siregar