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Jurnal SINTA 2

Classification of Clove Leaf Blister Blight Disease Severity Using Pre-trained Model VGG16, InceptionV3, and ResNet

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 17 No. 2 (2024) · pp. 159–166

DOI
10.21609/jiki.v17i2.1237
ISSN
2502-9274, 2088-7051
Published
2024-06-03
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Clove is one of the precious plants produced in Indonesia. Clove has many benefits for humans, but clove cultivation often experiences problems due to disease attacks, including Leaf Blister Blight Disease(CDC). The handling of CDC disease is carried out based on the severity of the symptoms that can be seen on the affected leaves. This research was conducted to obtain a CDC disease classification model, so appropriate treatment can be carried out. This study used the pre-trained VGG16, InceptionV3, and ResNet models for classification. VGG16 got the highest average accuracy of 96.7%. Aside from that, k-fold cross validation improved the model's accuracy.

Collaboration network of the authors

11 authors · 55 co-authorship links

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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Classification of Clove Leaf Blister Blight Disease Severity Using Pre-trained Model VGG16, InceptionV3, and ResNet</dc:title>
	<dc:creator>Pramesti, Putri Ayu</dc:creator>
	<dc:creator>Supriyadi, Muhamad Rodhi </dc:creator>
	<dc:creator>Alfin, Muhammad Reza </dc:creator>
	<dc:creator>Noveriza, Rita </dc:creator>
	<dc:creator>Wahyuno, Dono </dc:creator>
	<dc:creator>Manohara, Dyah </dc:creator>
	<dc:creator>Melati</dc:creator>
	<dc:creator>Miftakhurohmah</dc:creator>
	<dc:creator>Warman, Riki</dc:creator>
	<dc:creator>Hardiyanti, Siti</dc:creator>
	<dc:creator>Asnawi</dc:creator>
	<dc:description xml:lang="en-US">Clove is one of the precious plants produced in Indonesia. Clove has many benefits for humans, but clove cultivation often experiences problems due to disease attacks, including Leaf Blister Blight Disease(CDC). The handling of CDC disease is carried out based on the severity of the symptoms that can be seen on the affected leaves. This research was conducted to obtain a CDC disease classification model, so appropriate treatment can be carried out. This study used the pre-trained VGG16, InceptionV3, and ResNet models for classification. VGG16 got the highest average accuracy of 96.7%. Aside from that, k-fold cross validation improved the model's accuracy.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2024-06-03</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1237</dc:identifier>
	<dc:identifier>10.21609/jiki.v17i2.1237</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 17 No. 2 (2024): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 159-166</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v17i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1237/513</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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