Perbandingan Metoda Klasifikasi K-Nearest Neighbor dan Support Vector Machine pada Pengenalan Benda Terhalang berbasis Kode Rantai

RAHMADI KURNIA, MELIA ASMITA, ROZAKY IHSAN, IKHWANA ELFITRI, DANANG KUMARA HADI

Sari


ABSTRAK

Benda yang terhalang oleh benda lain memiliki bentuk yang tidak sempurna karena sebagian sisinya tidak terlihat. Untuk mengatasi permasalahan tersebut, digunakan metoda yang dapat mengenali bentuk pada benda pada sisi yang masih nampak. Penelitian ini membandingkan metoda klasifikasi K-Nearest Neighbor (KNN) dan Support Vector Machine (SVM) berbasis kode rantai untuk mendeteksi bentuk benda terhalang. Terdapat 15 sampel untuk lima bentuk bangun datar pada 2 jenis citra benda. Hasil untuk dua jenis citra, metoda KNN memiliki rata-rata ketepatan sebesar 89,6% sedangkan metoda SVM sebesar 88.4%. Waktu komputasi citra animasi menggunakan metoda SVM lebih cepat 0,044 detik dari pada metoda KNN dan lebih cepat 0,034 detik untuk citra riil. Rata-rata memori yang digunakan dengan metoda SVM pada citra animasi lebih sedikit 0,32 Mb dari pada metoda K-NN Pada citra riil rata-rata memori yang digunakan dengan metoda SVM lebih sedikit 0,44 Mb dari metoda K-NN.

Kata kunci: transformasi Hough, kode rantai, bentuk benda, KNN, SVM

 

ABSTRACT

Object that are blocked by other objects have an imperfect shape because some of their side are not visible. To overcome this problem, we propose a comparison the K Nearest Neighbor classification (K-NN) and the Support Vector Machine (SVM) method based on chain code algorithm. We used 15 samples for each shape of the object for two kind of images. The result of KNN method classification has an average accuracy of 89,6%. The SVM method has an average accuracy of 88.4%. The average computing time for the SVM method is 0,044 seconds faster than KNN method for drawing image and 0,0034 seconds faster for real images, The average memory for drawing image using the SVM method is 0,32Mb less than K-NN. In the real images the average memory used with the SVM method is 0,44 Mb less than the K-NN.

Keywords: hough transform, chain code, shape object, KNN, SVM


Kata Kunci


transformasi hough; kode rantai; bentuk benda; KNN; SVM

Teks Lengkap:

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v12i3.823

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ISSN (print) : 2338-8323 | ISSN (electronic) : 2459-9638

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