Recognition System Modeling INTRODUCTION

Proceedings of the 2 nd International Conference on Sustainable Technology Development selection is done from the implementation of the pattern founding in Aksara Bali image databases, based on the accumulated frequency of occurrence of each pattern model. As can be seen from the percentage of errors and processing time, this method proved quite effective and produces better performance for the Aksara Bali recognition, as compared with the pattern of Indonesia Signature models. 4.2. The special pattern base on Localized Arc Pattern Method for Balinese image character, are formed by the characteristic point in a square 5 x 5 produces 125 pieces of possible initial patterns that can be grouped into an 103 patterns early models. 4.3. Reduction of processing time is done by selection of 125 patterns. The selection patterns are performed by using computer program to calculate the frequency of each pattern appeared on a number of binary image of the Balinese character. Sample data that is used to establish the pattern of the model are 600 pieces of Aksara Bali image which is taken from some books and the internet. Patterns are obtained from the model selection process as many as 23 pieces pattern 4.4. Performance of the system is measured by two types of errors, namely: the rejection error false rejection and reception errors false acceptance. The system developed has a minimum percentage of error in all combinations of the constant multiplier threshold Cd 2.0: 3.0: 4.0: 5.0 and the constant of cutting q-value of Eigen value 3, with an average system error is 3.6 to obtain a success rate of 96.4. REFERENCE Agung BW, Rudy Hermanto I Gede, Retno Novi D ang. 2009. Pengenalan Huruf Bali dengan Menggunakan metode Modified Direction Feature MDF dan Learning Vector Quantization LVQ. Konferensi Nasional Sistem dan Informatika 2009. Institut Teknologi Telkom, Bandung. yudiagusta.files.wordpress.com...007-012-knsi09-002- pengenalan-huruf-bali-menggunakan-metode-modified-direction-feature-_mdf Oka Sudana, AA. K. 2006. Rancang Bangun Sistem Verifikasi Tandatangan dan Pengenalan Tulisan Tangan dengan Metode Pola Busur Terlokalisasi. Proceeding of the Research and Studies III . TPSDP – DIKTI 2006. Oka Sudana, AA.K. 2007. Implementasi Pola Model Tandatangan Jepang dan Tandatangan Indonesia untuk Verifikasi Tandatangan Latin. Jurnal Pakar, Vol 7, No 4, Yogyakarta. Shin-ichi Kikuchi, Takehiro Furuta, Takako Akakura. 2008. Periodical Examinees Identification in e-Test Systems Using the Localized Arc Pattern Method. Distance Learning and the Internet Conference 2008. p.213-220 . Waseda University, Japan. Suamba Dharmayasa, I Komang Gede. 2009. Pengenalan Karakter Bali Cetak Menggunakan Metode Moment dan Jaringan Syaraf Tiruan Learning Vector Quantization; Teknik Elektro Udayana, Jimbaran, Bali. Yoshimura, I., Shimizu, T. dan Yoshimura, M.. 1993. A Zip Code Recognition System using the Localized Arc Pattern Method. Proceedings of 2 nd International Conference on Document Analysis Recognition. IEEE Computer Society. p183-186 . Yoshimura, M. dan Yoshimura, I., 1988, “Writer Identification Based on the Arc Pattern Transformation”,Proceedings of 9 th International Conference on Pattern Recognition, November 14-17, 1993, IEEE Computer Society, Washington, p.353-361 . Yoshimura, I. dan Yoshimura, M., 1994, “Arc Pattern Method for Writer Recognition as an Aid for Person Identification”, Nagoya University p.71-82. ___.___. 2010. Aksara Bali. http:wapedia.mobiidAksara_Bali . Diakses tanggal 09 Oktober 2010.