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<![CDATA[KOMPRESI FILE MENGGUNAKAN ALGORITMA HUFFMAN KANONIK ]]>
<![CDATA[Asrianda Asrianda]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.111
<![CDATA[Algoritma Huffman adalah salah satu algoritma kompresi. Algoritma huffman merupakan algoritma yang paling terkenal untuk mengompres teks. Terdapat tiga fase dalam menggunakan algoritma Huffman untuk mengompres sebuah teks, pertama adalah fase pembentukan pohon Huffman, kedua fase encoding dan ketiga fase decoding. Prinsip yang digunakan oleh algoritma Huffman adalah karakter yang sering muncul di -encoding dengan rangkaian bit yang pendek dan karakter yang jarang muncul di-encoding dengan rangkaian bit yang lebih panjang. Teknik kompresi algoritma Huffman mampu memberikan penghematan pemakaian memori sampai 30%. Algoritma Huffman mempunyai kompleksitas O(n log n) untuk himpunan dengan n karakter.]]>
<![CDATA[PROTOTIPE HAND-GEOMETRY SEBAGAI SISTEM VERIFIKASI ]]>
<![CDATA[Rizal Tjut Adek]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.102
<![CDATA[Geometric measurements of the human hand have been used for identity authentication in a number of commercial systems. In this project we have developed a prototype hand geometry-based verification system and analyzed it's performance. We have demonstrated the practical utility of this system by designing an application that uses hand geometry as opposed to password for restricting access to a web site. We present our preliminary verification results based on hand measurements of 50 individuals captured over a period of time.]]>
<![CDATA[IDENTIFIKASI MANUSIA MELALUI RADIOGRAF BIOMETRIKS DENTAL ]]>
<![CDATA[Nurdin Nurdin]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.103
<![CDATA[Dental biometrics utilizes dental radiographs for human identification. The dental radiographs provide information about teeth, including tooth contours, relative positions of neighboring teeth, and shapes of the dental work (e.g.,crowns, fillings, and bridges). The proposed system has two main stages: feature extraction and matching. The feature extraction stage uses anisotropic diffusion to enhance the images and a Mixture of Gaussians model to segment the dental work. The matching stage has three sequential steps: tooth-level matching, computation of image distances, and subject identification. In the tooth-level matching step, tooth contours are matched using a shape registration method, and the dental work is matched on overlapping areas. The distance between the tooth contours and the distance between the dental work are then combined using posterior probabilities. In the second step, the tooth correspondences between the given query (postmortem) radiograph and the database (antemortem) radiograph are established. A distance based on the corresponding teeth is then used to measure the similarity between the two radiographs. Finally, all the distances between the given postmortem radiographs and the antemortem radiographs that provide candidate identities are combined to establish the identity of the subject associated with the postmortem radiographs.]]>
<![CDATA[MATCHING SIDIK JARI MENGGUNAKAN TRANSFORMASI HOUGH ]]>
<![CDATA[Mukti Qamal]]>;
<![CDATA[Burhanuddin Burhanuddin]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.108
<![CDATA[Despite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSUVERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%.]]>
<![CDATA[PELOKALISIRAN CITRA IRIS MENGGUNAKAN WAVELET 2D ]]>
<![CDATA[Bustami Bustami]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.104
<![CDATA[The performance of an iris recognition system can be undermined by poor quality images and result in high false reject rates (FRR) and failure to enroll (FTE) rates. In this paper, a wavelet-based quality measure for iris images is proposed. The merit of the this approach lies in its ability to deliver good spatial adaptivity and determine local quality measures for different regions of an iris image. Our experiments demonstrate that the proposed quality index can reliably predict the matching performance of an iris recognition system. By incorporating local quality measures in the matching algorithm, we also observe a relative matching performance improvement of about 20% and 10% at the equal error rate (EER), respectively, on the CASIA and WVU iris databases.]]>
<![CDATA[PENDETEKSIAN TITIK – TITIK JANGKAR UNTUK VERIFIKASI FACE 3D ]]>
<![CDATA[Dahlan Abdullah]]>;
<![CDATA[Safwandi Safwandi]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.109
<![CDATA[This paper outlines methods to detect key anchor points in 3D face scanner data. These anchor points can be used to estimate the pose and then match the test image to a 3D face model. We present two algorithms for detecting face anchor points in the context of face verification; One for frontal images and one for arbitrary pose. We achieve 99% success in finding anchor points in frontal images and 86% success in scans with large variations in pose and changes in expression. These results demonstrate the challenges in 3D face recognition under arbitrary pose and expression. We are currently working on robust fitting algorithms to localize more precisely the anchor points for arbitrary pose images.]]>
<![CDATA[SISTEM SKETSA GENERATIF PEMODELAN RAMBUT MANUSIA ]]>
<![CDATA[Sayed Fachrurrazi]]>;
<![CDATA[Fadlisyah Fadlisyah]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.105
<![CDATA[In this paper, we present a generative sketch model for human hair analysis and synthesis. We treat hair images as2D piecewise smooth vector (flow) fields and, thus, our representation is view-based in contrast to the physically-based 3D hair models in graphics. The generative model has three levels. The bottom level is the high-frequency band of the hair image. The middle level is a piecewise smooth vector field for the hair orientation, gradient strength, and growth directions. The top level is an attribute sketch graph for representing the discontinuities in the vector field.Asketch graph typically has a number of sketch curves which are divided into 11 types of directed primitives. Each primitive is a small window (say 5 _ 7 pixels) where the orientations and growth directions are defined in parametric forms, for example, hair boundaries, occluding lines between hair strands, dividing lines on top of the hair, etc. In addition to the three level representation, we model the shading effects, i.e., the low-frequency band of the hair image, by a linear superposition of some Gaussian image bases andwe encode the hair color by a color map. The inference algorithm is divided into two stages: 1) We compute the undirected orientation field and sketch graph from an input image and 2) we compute the hair growth direction for the sketch curves and the orientation field using a Swendsen-Wang cut algorithm. Both steps maximize a joint Bayesian posterior probability. The generative model provides a straightforward way for synthesizing realistic hair images and stylistic drawings (rendering) from a sketch graph and a few Gaussian bases. The latter can be either inferred from a real hair image or input(edited) manually using a simple sketching interface. We test our algorithm on a large data set of hair images with diverse hair styles.]]>
<![CDATA[SISTEM INFORMASI PENJUALAN PADA KOPERASI SYARI’AT PERTI ]]>
<![CDATA[Irvanizam Zamanhuri]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.110
<![CDATA[Swalayan merupakan suatu organisasi yang didalamnya terdapat kegiatan jual beli barang, di mana organisasi tersebut berada di bawah tanggung jawab seorang manajer. Dalam hal pendataan Swalayan Gallery KSP masih dibilang sederhana, di mana masih menggunakan catatan buku. Maka dari itu penulis memberikan solusi menggunakan program Microsoft Visual Basic.NET dengan aplikasinya untuk membuatkan sistem informasi penjualan secara komputerisasi yang lebih efektif dan efisien. Pengembangan sistem informasi penjualan KSP ini dibuat melalui empat tahapan, pertama tahap studi kelayakan dimana Swalayan Gallery KSP dalam menjalankan kegiatannya terbagi dalam tiga bagian yaitu bagian gudang, administrasi dan bagian penjualan. Kedua tahap rencana pendahuluan, proses pembuatan sistem penjualan dimulai dengan pembuatan Diagram Alir Data (DAD) Sistem berlanjut ke Data Flow Diagram (DFD) hingga Normalisasi. Ketiga, analisis sistem yaitu tahap lanjutan dari rencana pendahuluan dengan menjabarkan sistem penjualan ke arah yang lebih detail. Keempat implementasi yaitu tahap pembuatan kode program dan cara kerja program. Sedangkan metode yang digunakan untuk mendapatkan data dalam pembuatan sistem penjualan yaitu dengan metode observasi, dan metode literatur. Simpulan dari penelitian ini adalah, sistem informasi Penjualan KSP akan dapat membantu dalam pengolahan data, meringankan proses kerja dan menghasilkan laporan yang akurat. Sehingga dapat menjawab pertanyaan yang selama ini muncul.]]>
<![CDATA[MULTIMODAL FACIAL GENDER DAN IDENTIFIKASI ETNIK ]]>
<![CDATA[Jalaluddin Jalaluddin]]>;
<![CDATA[Fadlisyah Fadlisyah]]>
<![CDATA[ TECHSI - Jurnal Teknik Informatika Vol 4, No 1 (2012) ]]>
Publisher : <![CDATA[Teknik Informatika Universitas Malikussaleh ]]>
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DOI: 10.29103/techsi.v4i1.106
<![CDATA[Human faces provide demographic information, such as gender and ethnicity. Different modalities of human faces, e.g., range and intensity, provide different cues for gender and ethnicity identifications. In this paper we exploit the range information of human faces for ethnicity identification using a support vector machine. An integration scheme is also proposed for ethnicity and gender identifications by combining the registered range and intensity images. The experiments are conducted on a database containing 1240 facial scans of 376 subjects. It is demonstrated that the range modality provides competitive discriminative power on ethnicity and gender identifications to the intensity modality. For both gender and ethnicity identifications, the proposed integration scheme outperforms each individual modality.]]>
