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All Journal Internet of Things and Artificial Intelligence Journal
Fitri, Fitri Aulia Huzaini
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Classification of Cow's Milk Freshness Based on Color and Homogeneity Using the Support Vector Machines (SVM) Method Fitri, Fitri Aulia Huzaini; anis, Anis Yusrotun Nadhiroh; wali, Wali Ja'far Shudiq
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 1 (2025): Volume 5 Issue 1, 2025 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i1.771

Abstract

Cow's milk is an important food ingredient in meeting human health needs, because cow's milk has high nutritional benefits and an overall healthy structure with very good nutritional proportions, so it has very important value for the younger generation, especially those who are still in school, who need protein. Animal origin from milk. Classifying milk that has various levels of suitability for consumption requires a method that has maximum accuracy so that accurate results are obtained so that we can distinguish between types of milk that can be consumed and those that cannot. This research proposes a Support Vector Machine (SVM) processing technique for classifying milk. The color and homogeneity of various kinds of milk in different positions and conditions of light contrast are used as data to classify types of milk. The results obtained by the SVM algorithm are efficient in classifying the color and homogeneity of milk. The resulting accuracy of applications using the SVM algorithm is 84.44%.
Co-Authors anis, Anis Yusrotun Nadhiroh wali, Wali Ja'far Shudiq