Fadli, Muhammad (2019) Pengenalan Tulisan Tangan Dengan Smooth Support Vector Machine Dan Diagonal Based Feature Extraction. Other thesis, Universitas Komputer Indonesia.
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Abstract
Penelitian ini bertujuan untuk mengetahui tingkat akurasi pengenalan tulisan tangan menggunakan metode klasifikasi Smooth Support Vector Machine (SSVM) dan metode ekstraksi ciri Diagonal Based Feature Extraction. Adapuun tahapan dalam penelitian ini yaitu tahap pengumpulan data karakter tulisan tangan teridiri dari karakter hurf A-Z, a-z dan angka 0-9. Dalam penelitian ini sebelum melakukan proses klasifikasi, citra tulisan tangan akan melalui tahap preprocessing yang teridiri dari Grayscale, Threshold, Segmentasi, Scalling dan ekstraksi fitur Diagonal Based Feature Extraction. Selanjutnya dilakukan proses pelatihan dan pengujian dengan metode Smooth Support Vector Machine. Sample citra karakter tulisan tangan di peroleh dari 30 orang koresponden dan akan digunakan sebagai data latih dan data uji. Berdasarkan hasil pengujian yang dilakukan terhadap data uji, maka didapatkan akurasi terbaik 72,6%.
| Item Type: | Thesis (Other) |
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| Uncontrolled Keywords: | Kecerdasan Buatan, Smoooth Support Vector Machine, Diagonal Based Feature Extraction, Feature Extraction, pengenalan citra tulisan tangan, pengolahan citra, SSVM. |
| Subjects: | 000_COMPUTER SCIENCE, INFORMATION & GENERAL WORKS. > 004_Data Processing & Computer Science |
| Divisions: | S1_SKRIPSI > FTIK_Teknik Informatika (01) |
| Depositing User: | Mrs. Calis Maryani |
| Date Deposited: | 13 Jan 2020 01:29 |
| Last Modified: | 13 Jan 2020 01:29 |
| URI: | http://elibrary.unikom.ac.id/id/eprint/1598 |
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