Klasifikasi Tingkat Kematangan Cabai Rawit dengan Ekstraksi HSV-GLCM dan Metode Klasifikasi Support Vector Machines (SVMs)

Akbar Sofyan, Azriel (2024) Klasifikasi Tingkat Kematangan Cabai Rawit dengan Ekstraksi HSV-GLCM dan Metode Klasifikasi Support Vector Machines (SVMs). Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Chili peppers are one of the common commodities consumed by the Indonesian community and have high economic value. With their high economic value, chili peppers are widely cultivated in Indonesia. In their cultivation, the quality of chili peppers needs to be considered as it affects their price. One of the factors that determines the quality of chili peppers is the quality of sorting during post-harvest handling. Generally, sorting is done manually by humans, which can lead to fatigue and reduce the accuracy of sorting. Therefore, computer vision assistance in the form of artificial intelligence models is needed to classify the maturity level of chili peppers. Moreover, previous studies have not utilized the extraction of color and texture features simultaneously to build a classification model, so it is necessary to investigate the performance of the model when using both features simultaneously. This study attempts to build a classification model for maturity level using HSV-GLCM feature extraction and Support Vector Machines One Vs All. The results of this study show that HSV-GLCM feature extraction can be applied as a classification feature and produces the best classification model for chili pepper maturity level with an accuracy of 92.12%.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Puspita Sari, Anggraini	NIDN0716088605	anggraini.puspita.if@upnjatim.ac.id
Thesis advisor	Aji Putra, Chrystia	NIDN0008108605	ajiputra@upnjatim.ac.id

Subjects:

T Technology > T Technology (General)

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

Azriel Akbar Sofyan

Date Deposited:

20 Sep 2024 06:51

Last Modified:

20 Sep 2024 06:51

URI:

https://repository.upnjatim.ac.id/id/eprint/29630