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All Journal Jurnal Informatika dan Teknik Elektro Terapan Internet of Things and Artificial Intelligence Journal
anis, Anis Yusrotun Nadhiroh
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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%.
PERAMALAN PENJUALAN DENGAN DECISION TREE UNTUK OPTIMASI KEUNTUNGAN DI GARMENT NURUL JADID Anis, Anis Yusrotun Nadhiroh; Nur, Nur Holisah; nafisah, Nafisah Dwi Anggi Yulistina; Syafana, Syarafana Usaimah Mirza
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.7986

Abstract

Study This aim For predict sale products at Nurul Jadid Garment for optimize profit company through implementation Decision Tree algorithm . Problems faced is fluctuations sales that cause inaccuracy in production and distribution , so that influence efficiency operational and profit . The method used in study This is approach quantitative with Decision Tree algorithm as tool analysis main . Sales data historical collected and processed For identify patterns sale based on attributes like type product , season , and sales volume . Research results show that the Decision Tree model is capable of classify and predict trend sale with level adequate accuracy . Based on results prediction said , the company can plan better production and marketing strategies appropriate target . Conclusion of study This is that use of Decision Tree as tool forecasting sale effective in help taking decision business and can increase profit through efficiency production and reduction excess stock .
Co-Authors Fitri, Fitri Aulia Huzaini nafisah, Nafisah Dwi Anggi Yulistina Nur, Nur Holisah Syafana, Syarafana Usaimah Mirza wali, Wali Ja'far Shudiq