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JUTI: Jurnal Ilmiah Teknologi Informasi

juti
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Published by Institut Teknologi Sepuluh Nopember Surabaya

ISSN : 24068535 EISSN : 14126389 DOI : http://dx.doi.org/10.12962/j24068535

Core Subject : Health, Science, Education,

Computer Science & IT Dentistry Education Library & Information Science

JUTI (Jurnal Ilmiah Teknologi Informasi) is a scientific journal managed by Department of Informatics, ITS.

Arjuna Subject : -

Articles 8 Documents

Search results for , issue "Vol 7, No 3, Januari 2009" : 8 Documents clear

RANCANGAN DAN IMPLEMENTASI GALERI VIDEO DAN ANIMASI PADA SITUS LAPAN POLAR SATELLITE Soewarto Hardhienata; Medria Kusuma Dewi
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Lapan Tubsat satellite has produced large number of videos or satellite images since the first launch from the Satish Dhawan Space Center, Sriharikota India, on January 10, 2007. LAPAN expect that the results of the satellite tracking needs a storage media that enables it to be more accessible and attractive to the public. Therefore, a facility is designed and implemented to meet the user requirements. The built of an interactive video gallery which is embedded with the site is the main focus of this paper. In addition, animations and video player are also implemented so that Lapan Polar Satellite Sites (SLPS) become more interactive and interesting to the site visitors.

EMBEDDED LINUX BASED ALBUM BROWSER SYSTEM AT MUSIC STORES Suryadiputra Liawatimena
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

The goal of this research is the creation of an album browser system at a music store based on embedded Linux. It is expected with this system; it will help the promotion of said music store and make the customers activity at the store simpler and easier. This system uses NFS for networking, database system, ripping software, and GUI development. The research method used are and laboratory experiments to test the system’s hardware using TPC-57 (Touch Panel Computer 5.7" SA2410 ARM-9 Medallion CPU Module) and software using QtopiaCore. The result of the research are; 1. The database query process is working properly; 2. The audio data buffering process is working properly. With those experiment results, it can be concluded that the summary of this research is that the system is ready to be implemented and used in the music stores.

KINERJA ALGORITMA PARALEL UNTUK PENCARIAN KATA DENGAN METODE BOYER-MOORE MENGGUNAKAN PVM Maria Angela Kartawidjaja; Stania Vandika
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Search process is one of important activity in data processing. Searching can take more time if conducted in the huge search space. Therefore, it is needed an efficient search technique. One technique that can be used is parallel computing. This article discusses the search process in parallel using the Boyer-Moore algorithm. Parallel scope is emulated with PVM (Parallel Virtual Machine) software. From the research results, it can be concluded that the performance of parallel computing will increase the word searching compared to the computing performance for its word sequencial search consisting of one letter, and will drop to the word search consisting of two letters or more.

REPRESENTASI KUERI SPASIAL WARNA DENGAN LOGIKA FUZZY PADA SISTEM PEROLEHAN CITRA M Rahmat; Widyanto Maria; Susan Anggreainy
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Image acquisition system is a field of research that flourished along with the growing number of number of is a collection of images. Zoran has developed an image acquisition system using low-level attribute that is spatial color. But the system is still found a deficiency of the approach used is crisp, with this approach there are images that are relevant but the image is not obtained, which should be obtained. In this paper fuzzy logic is proposed as an approach to represent the spatial color of the system image acquisition. Fuzzy membership functions are proposed to model the spatial gaussian two colors are in - dimensions (2D). Experiments carried out with the image data 760 by using the domain name database by category painting abstract. Test results showed that this system successfully to improve the previous approach of represent - spatial query sentasikan color. This system can provide a more natural queries to the user.

APLIKASI WEB CRAWLER UNTUK WEB CONTENT PADA MOBILE PHONE Sarwosri Sarwosri; Ahmad Hoirul Basori; Wahyu Budi Surastyo
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Crawling is the process behind a search engine, which served through the World Wide Web in a structured and with certain ethics. Applications that run the crawling process is called Web Crawler, also called web spider or web robot. The growth of mobile search services provider, followed by growth of a web crawler that can browse web pages in mobile content type. Crawler Web applications can be accessed by mobile devices and only web pages that type Mobile Content to be explored is the Web Crawler. Web Crawler duty is to collect a number of Mobile Content. A mobile application functions as a search application that will use the results from the Web Crawler. Crawler Web server consists of the Servlet, Mobile Content Filter and datastore. Servlet is a gateway connection between the client with the server. Datastore is the storage media crawling results. Mobile Content Filter selects a web page, only the appropriate web pages for mobile devices or with mobile content that will be forwarded.

PENERAPAN METODE ANALISA DISKRIMINAN MAJEMUK DENGAN PENDEKATAN TRANSFORMASI FUKUNAGA KOONTZ Rully Soelaiman; Wiwik Anggraini; M Mujahidillah
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Linear discriminant analysis is one of method frequently used and developed in the field of pattern recognition. This method tries to find the optimal subspace by maximizing the Fisher Criterion. Application of pattern recognition in highdimensional data and the less number of training samples cause singular within-class distribution matrix. In this paper, we developed Linear Discriminant Analysis method using Fukunaga Koontz Transformation approach to meet the needs of the nonsingular within-class distribution matrix. Based on Fukunaga Koontz Transformation, the entire space of data is decomposed into four subspaces with different discriminant ability (measured by the ratio of eigenvalue). Maximum Fisher Criterion can be identified by linking the ratio of eigenvalue and generalized eigenvalue. Next, this paper will introduce a new method called complex discriminant analysis by transforming the data into intraclass and extraclass then maximize their Bhattacharyya distance. This method is more efficient because it can work even though within-class distribution matrix is singular and between-class distribution matrix is zero.

PEMODELAN ARIMA DAN DETEKSI OUTLIER DATA CURAH HUJAN SEBAGAI EVALUASI SISTEM RADIO GELOMBANG MILIMETER Achmad Mauludiyanto; Gamantyo Hendrantoro; Mauridhi Hery P; Suhartono Suhartono
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

The purpose of this paper is to provide the results of Arima modeling and outlier detection in the rainfall data in Surabaya. This paper explained about the steps in the formation of rainfall models, especially Box-Jenkins procedure for Arima modeling and outlier detection. Early stages of modeling stasioneritas Arima is the identification of data, both in mean and variance. Stasioneritas evaluation data in the variance can be done with Box-Cox transformation. Meanwhile, in the mean stasioneritas can be done with the plot data and forms of ACF. Identification of ACF and PACF of the stationary data is used to determine the order of allegations Arima model. The next stage is to estimate the parameters and diagnostic checks to see the suitability model. Process diagnostics check conducted to evaluate whether the residual model is eligible berdistribusi white noise and normal. Ljung-Box Test is a test that can be used to validate the white noise condition, while the Kolmogorov-Smirnov Test is an evaluation test for normal distribution. Residual normality test results showed that the residual model of Arima not white noise, and indicates the existence of outlier in the data. Thus, the next step taken is outlier detection to eliminate outlier effects and increase the accuracy of predictions of the model Arima. Arima modeling implementation and outlier detection is done by using MINITAB package and MATLAB. The research shows that the modeling Arima and outlier detection can reduce the prediction error as measured by the criteria Mean Square Error (MSE). Quantitatively, the decline in the value of MSE by incorporating outlier detection is 23.7%, with an average decline 6.5%.

KERNEL LOGISTIC REGRESSION-LINEAR FOR LEUKEMIA CLASSIFICATION USING HIGH DIMENSIONAL DATA S P Rahayu; S W Purnami; A Embong; Jasni Mohammad Zain
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 3, Januari 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Kernel Logistic Regression (KLR) is one of the statistical models that has been proposed for classification in the machine learning and data mining communities, and also one of the effective methodologies in the kernel–machine techniques. Basely, KLR is kernelized version of linear Logistic Regression (LR). Unlike LR, KLR has ability to classify data with non linear boundary and also can accommodate data with very high dimensional and very few instances. In this research, we proposed to study the use of Linear Kernel on KLR in order to increase the accuracy of Leukemia Classification. Leukemia is one of the cancer types that causes mortality in medical diagnosis problem. Improving the accuracy of Leukemia Classification is essential for more effective diagnosis and treatment of Leukemia disease. The Leukemia data sets consists of 7120 (very high dimensional) DNA micro arrays data of 72 (very few instances) patient samples on the state of Leukemia types. In Leukemia classification based upon gene expression, monitoring data using DNA micro array offer hope to achieve an objective and highly accurate classification. It can be demonstrated that the use of Linear Kernel on Kernel Logistic Regression (KLR–Linear) can improve the performance in classifying Leukemia patient samples and also can be shown that KLR–Linear has better accuracy than KLR–Polynomial and Penalized Logistic Regression.

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Editorial Address Gedung Teknik Informatika Lantai 2 Ruang IF-230, Jalan Teknik Kimia, Kampus ITS Sukolilo, Surabaya, 60111

Location Kota surabaya, Jawa timur INDONESIA

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Contact Name
-

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Journal Mail Official
juti.if@its.ac.id

Editorial Address
Gedung Teknik Informatika Lantai 2 Ruang IF-230, Jalan Teknik Kimia, Kampus ITS Sukolilo, Surabaya, 60111

Location
Kota surabaya,

Jawa timur

INDONESIA