KLASIFIKASI TINGKAT KEMATANGAN BUAH MANGGIS MENGGUNAKAN METODE K-NEAREST NEIGHBORS BERDASARKAN EKSTRAKSI CIRI TEKSTUR LOCAL BINARY PATTERN (LBP) DAN EKSTRAKSI CIRI WARNA HSV

Muhamad Rizky Yusuf, . (2023) KLASIFIKASI TINGKAT KEMATANGAN BUAH MANGGIS MENGGUNAKAN METODE K-NEAREST NEIGHBORS BERDASARKAN EKSTRAKSI CIRI TEKSTUR LOCAL BINARY PATTERN (LBP) DAN EKSTRAKSI CIRI WARNA HSV. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Mangosteen is a horticultural plant that has many uses in every part. Mangosteen is one of the main export commodities in Indonesia, therefore the quality of the mangosteen fruit must be considered by paying attention to the maturity level of the mangosteen fruit. In this study, classification of mangosteen fruit maturity levels will be carried out using the K-Nearest Neighbors (KNN) method based on texture feature extraction with LBP and color characteristics with HSV color moment. The dataset used in this study contained 240 images consisting of 3 classes, namely cooked, half cooked and raw. Respectively each class consists of 80 image data. In this study, the initial stage was to pre-process the image, then perform feature extraction. After obtaining the results of feature extraction, the data is divided into 70% core data and 30% test data then forming a KNN classification model with k values of 1, 3, 5, 7, 9. After the classification process is carried out, the highest accuracy value is obtained at the value of k = 1 that is equal to 98.6%.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910511127] [Pembimbing: Ermatita] [Penguji 1: Bayu Hananto] [Penguji 2: Ria Astriratma]
Uncontrolled Keywords: Mangosteen, KNN, LBP, color moment, HSV
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Muhamad Rizky Yusuf
Date Deposited: 21 Aug 2023 04:54
Last Modified: 21 Aug 2023 04:54
URI: http://repository.upnvj.ac.id/id/eprint/25264

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