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All Journal J-Sil (Jurnal Teknik Sipil dan Lingkungan) MEDIA KONSERVASI Jurnal Bahtera - Jurnal Pendidikan Bahasa dan Sastra Indonesia Widya Winayata: Jurnal Pendidikan Sejarah Diponegoro Journal of Accounting Jurnal Keteknikan Pertanian Rekursif: Jurnal Informatika Jurnal Pseudocode FLYWHEEL : Jurnal Teknik Mesin Untirta Jurnal Pengabdian Kepada Masyarakat Universitas Bangka Belitung Turbo : Jurnal Program Studi Teknik Mesin IT JOURNAL RESEARCH AND DEVELOPMENT Machine : Jurnal Teknik Mesin At-Tawassuth: Jurnal Ekonomi Islam Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Report of Biological Education Technologic MACHINERY: Jurnal Teknologi Terapan Jurnal Teknologi Informasi Cyberku CELEBES Agricultural Borobudur Informatics Review Dharma Pengabdian Perguruan Tinggi (DEPATI) Electrician : Jurnal Rekayasa dan Teknologi Elektro APPA : Jurnal Pengabdian Kepada Masyarakat Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Yudi Setiawan
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Journal : Jurnal Teknologi Informasi Cyberku

 1 
PENGENALAN POLA HURUF HIJAIYAH TULISAN TANGAN MENGGUNAKAN FUZZY FEATURE EXTRACTION DAN JARINGAN SYARAF TIRUAN BACKPROPAGATION Helsi Tia Vermala; Diyah Puspitaningrum; Yudi Setiawan
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 12 No 2 (2016): Jurnal Teknologi Informasi CyberKU Vol. 12, no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

This research to build a pattern recognition hijaiyah letters handwriting application. In this offline pattern recognition research, a digital handwriting input is captured by a scanner. In this research we try to recognize digital handwriting based on feature classification using Backpropagation Neural Network and Fuzzy Feature Extraction method for feature extraction. This application is built using Matlab language programming and designed using Data Flow Diagram (DFD). Meanwhile the system development life cycle method that used is Waterfall. Experiments were performed on a single Hijaiyah letters isolated from 900 samples gave results of generalization ability of artificial neural networks for 96.11% and the ability to generalize the ability of Neural Network memorization for 98.33%.
Co-Authors Aan Erlansari Aan Erlansari Abd Malik A Madinu Afid Nuryadi Agus Ponco Ahmad Mustofa Ajei Ibnu Rahmat Ali Dzulfigar Amelia Putri Angga Nurwanto Anosa Putri Ruise Arie Vatresia Arif Kurnia Wijayanto Asahar Johar Asep Suheri Aswin Rahadian Asy'Ari, Rahmat Aulia Ulfa Azelia Dwi Rahmawati Azizah Nur Islam Al Rosyid Boby Putra Perdana Boko Susilo Citra Putri Perdana Danik Septianingrum Desi Andreswari Desi Andreswari Dimas Anugrah H.A Diyah Puspitaningrum Doni Pranata Edi Irwan EKA SARI Eka Sari Wijiaanti Eka Sari Wijianti Eka Sari Wijianti Eka Sari Wijiyanti Endang Widi Winarni Erwin Nandes Etna Nur Afri Yuyetta Gilang Yulianta Hanum Resti Saputri Harry Imantho Haryono, Wasis Helsi Tia Vermala Herni Natasha Aulia I Wayan Astika I Wayan Pardi Ibnu Dinar Impron Irfan Wahyudi Iwan Giri Waluyo Julia Purnama Sari Ketut Sedana Arta Ketut Wikantika Kikin Hamzah Muttaqin Kurnia Anggriani LILIK BUDIPRASETYO M. Sidqi Albadawi. Malta Daerangga Marfi, Khairani Putri Misnawati Misnawati Misnawati. Moh Yanuar J Purwanto Muhammad Agus Muljanto Muhammad Buce Saleh Muhammad Ikhwan Ramadhan MUHAMMAD ILHAM Muhammad Irfan Septiyanda Muhammad Nurdiansyah Nabila Nadiya Khairunisa Neviaty P Zamani NEVIATY PUTRI ZAMANI Nur Rahmadhanti, Intan Oxa Aspera Endiviana Oxa Aspera Endiviana Pramulya, Rahmat Puspitasari, Raditya Febri R. Priyoko Prayitnoadi Rahmat Asy'ari Rahmat Asy’ari Resi Tri Utami Sahid Hudjimartsu Salsabila Nur'Aini Saparin, Saparin Selvianing Tiyas Slamet Widodo Sugiarto Sri Dadi Suhdi Suhdi Suhdi, Suhdi Sultan Arkar Syahrul Gunawan Taufiq Yuliawan Usnil Khotimah Utama, Ferzha Putra Verawati Ayu Lestari Wildan Maynardy Wicaksono Wiwik Handayani