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KLASIFIKASI KEMATANGANBUAHKELAPASAWIT MENGGUNAKANMETODESUPPORTVECTORMACHINE(SVM)

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Penilaian

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Palm oil fruit has a uniqueness that comes from the color of the fruit which is almost the same, namely dark black or slightly yellowish black when unripe, and dark red when ripe. This makes it difficult to distinguish between ripe and unripe palm fruit. Palm oil fruit has a large number in each tree. A system is needed to classify palm oil fruit maturity automatically. The Support Vector Machine (SVM) method can be used to classify ripe and unripe palm oil fruit. This method has the advantage of offering high accuracy and works well with high dimensional spaces with the help of Hue Saturation Value (HSV) as feature extraction so that these problems can be resolved. Four scenarios in the training and testing process. Each Scenario will be trained and tested using a different kernel, namely Linear, Polynomial, and RBF. The results obtained are in scenario one, the polynomial kernel gets a very good accuracy value, which is 99.4%. In scenario two, the polynomial kernel gets a very good accuracy value of 99.25%. In scenario three, the polynomial kernel and the RBF kernel get the same accuracy value, which is 99.2%. In scenario four, the polynomial kernel gets an accuracy value of 99%. This proves that the Support Vector Machine (SVM) method with Hue Saturation Value (HSV) feature extraction can be used to classify palm oil fruit maturity with very good results.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207003617	T78541	T785412022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T785412022

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xii, 46 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.360 7

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Teknik Informatika
Program untuk Komputer Personal

Specific Detail Info

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Statement of Responsibility

SEPTA

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