Jurnal Ilmu Komputer
Vol. 1 No. 1 (2018)

Segmentasi Fuzzy C-Means Untuk Membantu Identifikasi Kualitas Beras Berdasarkan Nilai Threshold, Warna Dan Ukuran

Iwan Setiawan Wibisono (Universitas Ngudi Waluyo)
Sri Mujiyono (Universitas Ngudi Waluyo)



Article Info

Publish Date
31 Dec 2018

Abstract

Abstrak— There are several types of rice circulating in Indonesian society, namely: fragrant pandan rice, rojolele, membramo, IR 64, IR 42, C4, etc. To get rice quality assurance, it is necessary to check the quality of rice which is usually done by experienced inspectors. This study aims to produce a tool for inspectors who can process the image of rice and classify the quality of rice and analyze the performance of the classification system. The steps that will be carried out include: preprocessing, feature extraction, and classification. The feature extraction method used is Statistical Feature Extraction in terms of its texture which is one of the physical characteristics of rice. While for classifying quality using the Fuzzy C-Means (FC-M) method. From the results of the study, it was found that the 3 final cluster centers were center cluster 1 (5.89333; 2.05), center cluster 2 (6.28199; 2.546), and center cluster 3 (6.96583; 2.999167) and validation was generated amounting to 92.82%.Keywords— Klasifikasi Beras. Image Processing, FC-M, Computer Vison

Copyrights © 2018






Journal Info

Abbrev

mm

Publisher

Subject

Computer Science & IT

Description

Jurnal Multimatrix ini sebagai media publikasi artikel penelitian, pengabdian masyarakat dalam bidang ilmu ...