Klasifikasi Citra Batik Aceh Menggunakan Metode KNearest Neighbor (K-NN) Berbasis Androi

Hilda Fajira, Indrawati Indrawati, Aswandi Aswandi

Sari


Batik is a pictorial cloth that is specially made by writing or applying wax to the cloth, then processing it in a certain way that has its own characteristics. In Indonesia, there are so many different batik motifs from each region. One of the problems with batik is that batik has very diverse motifs and colors, so it is very difficult to classify batik into certain classes. This study was conducted to classify Acehnese natik into classes or regional origins based on batik motifs and characteristics and understanding of batik. The method used is the K-Nearest Neighbor method which is used to determine the closeness between the test image and the training image based on the motif features of the Aceh batik image obtained. This application system recognizes the type of Aceh batik, which reaches 80% Keywords: K-Nearest Neighbor, K-NN, Batik Aceh

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Referensi


I

P. Hidayatullah. 2017. Pengolahan Citra Digital. Penerbit Andi.

Yogyakarta.

Ignatia Dhian E.K.R., Kristian Adi Nugraha. 2016. “Klasifikasi Batik

Menggunakan Knn Berbasis Wavelet” Program Studi Teknik

Informatika, Fakultas Teknologi Informasi, Universitas Kristen Duta

Wacana Yogyakarta.

Hamdi Arfa, Iwan Tritoasmoro, Ratri Dwi Atmaja. 2002.“Klasifikasi

Motif Batik Berdasarkan Citra DigitalMenggunakan Metode Support

Vector Machine. Program Studi Teknik Informatika, Fakultas Ilmu

Komputer, Universitas Dian Nuswantoro Semarang.

Cahaya Jatmoko, Daurat Sinaga. 2019.” Ektraksi Fitur Glcm Pada KNn Dalam Mengklasifikasi Motif Batik”. Program Studi Teknik

Informatika, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Semarang.

Syafitri, Nesi. 2010. “Perbandingan Metode K-Nearest Neighbor (KNn) Dan Metode Nearest Cluster Classifier (Ncc) Dalam

Pengklasifikasian Kualitas Batik Tulis”. Jurnal Teknologi Informasi

Dan Pendidikan, Vol. 2, No.1.

Yodha, J.W, Kurniawan, A.W. 2014. “Pengenalan Motif Batik

Menggunakan Deteksi Tepi Canny Dan KNearest Neighbor”. Techno.Com, Vol. 13, No. 4

Novianty, Eka. 2014. “Implementasi Jaringan Syaraf Tiruan

Backpropagation Untuk Klasifikasi Dan Identifikasi Motif Batik.

Tugas Akhir Pada Telkom University Bandung

Putra, Darma. 2010. Pengolahan Citra Digital. Edisi Pertama. Penerbit

Andi. Yogyakarta

Robi, Firmanda. 2014. “Rancang Bangun Aplikasi Deteksi Motif Batik

Berbasis Pengolahan Citra Digital Pada Platform Android”. Tugas

Akhir Pada TelkomUniversity Bandung


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