JUTI: Jurnal Ilmiah Teknologi Informasi
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REPRESENTASI KUERI SPASIAL WARNA DENGAN LOGIKA FUZZY PADA SISTEM PEROLEHAN CITRA
Get PDFImage 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
FRONTAL FACIAL SYMMETRY DETECTION USING EIGENVALUE METHOD
Get PDFFacial symmetry is correspondence of face components on the both sides of face, left and right of a dividing line or about a center or an axis. Most of the research use face component like eyes, nose and ears component to identify facial symmetry. In this paper we suggest to add mouth as another face component to increase accuracy in facial symmetry detection. The results of facial symmetry detection are used for authentication process, analysis in medical, psychology and anthropology scope. By using MATLAB 7.1 we develop a program that can analyze face,asymmetry or not with utilizing eigenvalue. The contribution of this analysis is to know whether eigenvalue is suitable or not in analyzing facial symmetry. Keywords: Eigenvalue, Face Components, Facial Symmetr
CATATAN DEWAN REDAKSI
Get PDFPada bulan Agustus 2008, akan ada kegiatan konferensi internasional tahunan Information and Communication Technology and Systems (ICTS). Untuk itu kami mengundang pembaca untuk ikut berpartisipasi dalam kegiatan tersebut baik sebagai pemakalah maupun sebagai peserta.Berikut kami sertakan Call for Papers untuk ICTS 2008
PENJADWALAN MATAKULIAH DENGAN MENGGUNAKAN ALGORITMA GENETIKA DAN METODE CONSTRAINT SATISFACTION
Get PDFCourse scheduling problem has gained attention from many researchers. A number of methods have been produced to get optimum schedule. Classical definition of course scheduling cannot fulfill the special needs of lecture scheduling in universities, therefore several additional rules have to be added to this problem. Lecture scheduling is computationally NP-hard problem, therefore a number of researches apply heuristic methods to do automation to this problem. This research applied Genetic Algorithm combined with Constraint Satisfaction Problem, with chromosomes generated by Genetic Algorithm processed by Constraint Satisfaction Problem. By using this combination, constraints in lecture scheduling that must be fulfilled can be guaranteed not violated. This will make heuristic process in Genetic Algorithm focused and make the entire process more efficient. The case study is the case in Informatics Department, Faculty of Information Technology, ITS. From the analysis of testing results, it is concluded that the system can handle specific requested time slot for a lecture, that the system can process all the offered lectures, and that the system can produce schedules without violating the given constraints. It is also seen that Genetic Algorithm in the system has done optimation in finding the minimum student waiting time between lectures
PERAMALAN MENGGUNAKAN METODE VECTOR AUTOREGRESSIVE MOVING AVERAGE (VARMA)
Get PDFForecasting technique is an important component of decision making because it aims to predict values of data in the future. Many existing forecasting methods only predict single variable data and thus do not consider correlation between variable in a dataset. This paper proposes Vector Autoregressive Moving Average (VARMA) as a forecasting method to predict data with more than one variable. This method combines regression concept i.e. autoregressive (VAR) and moving average method (VMA) for multi-variables data. The first step in VARMA method is testing the stationary of the data. Differencing process is conducted in order to change non stationary data to stationary. The next step is to identify the order of the VARMA model of the stationary data. The parameters are then estimated according to the order and co-integration test is conducted on the variables. The model is tested to assess its validity. If the model is valid then forecasting can be done using the model generic formula. The errors of the forecast are calculated to evaluate the performance of the model. Random values are found in the forecast of VARMA method. However, the error remains within a certain interval. The error interval is below 10% so it can be argued that this model is very accurate in predicting the data. Keywords: Forecasting, Multi-Variables, VAR, VMA, VARM, Co-integration Tes
PENERAPAN ALGORITMA WEIGHTED TREE SIMILARITY UNTUK PENCARIAN SEMANTIK
Get PDFFull-text search and metadata-enabled search have weakness in the precision of the searched article. This research offers weighted tree similarity algorithm combined with cosine similarity method to count similarity in semantic search. In this method metadata is constructed based on the tree of labelled node, labelled and weighted branch. The structure of tree metadata is constructed based on semantic information like taxonomi, ontologi, preference, synonim, homonym and stemming. From testing result, the precision of search using weighted tree similarity algorithm is better that full-text search and metadata-enabled search
APLIKASI TIGA DIMENSI VIRTUAL DENGAN MENGGUNAKAN 5DT DATA GLOVE 5 ULTRA
Get PDFOne of active area in information technology research is development of virtual reality (VR). It is a technology which can simulate real world activities in a virtual world. Virtual reality consists of software and hardware which is usually in the form of device that captures human movement. Then VR sends signal of that movement to computer. The signal will be received and processed and shown on the screen, so that the movement can be simulated. In this research, we develop an application that can receive hand movement input with 5DT Data Glove 5 Ultra and create natural and accurate hand movement animation output for hand opening closing and other gestures. Experiments show that there are some gestures though have different physical shapes but are recognized as the same gestures because of sensor limitation in data glove. Keywords: data glove, animation, virtual realit
ALGORITMA SHARED NEAREST NEIGHBOR BERBASIS DATA SHRINKING
Get PDFShared Nearest Neighbor (SNN) algorithm constructs a neighbor graph that uses similarity between data points based on amount of nearest neighbor which shared together. Cluster obtained from representative points that are selected from the neighbor graph. The representative point is used to reduce number of clusterization errors, but also reduces accuracy. Data based shrinking SNN algorithm (SSNN) uses the concept of data movement from data shrinking algorithm to increase accuracy of obtained data shrinking. The concept of data movement will strengthen the density of neighbor graph so that the cluster formation process could be done from neighbor graph components which still has a neighbor relationship. Test result shows SSNN algorithm accuracy is 2% until 8% higher than SNN algorithm, because of the termination of relationship between weak data points in the neighbor graph is done slowly in several iteration. However, the computation time required by SSNN algorithm is three times longer than SNN algoritm computational time, because SSNN algorithm constructs neighbor graph in several iteration
A STUDY ON RANKING METHOD IN RETRIEVING WEB PAGES BASED ON CONTENT AND LINK ANALYSIS: COMBINATION OF FOURIER DOMAIN SCORING AND PAGERANK SCORING
Get PDFRanking module is an important component of search process which sorts through relevant pages. Since collection of Web pages has additional information inherent in the hyperlink structure of the Web, it can be represented as link score and then combined with the usual information retrieval techniques of content score. In this paper we report our studies about ranking score of Web pages combined from link analysis, PageRank Scoring, and content analysis, Fourier Domain Scoring. Our experiments use collection of Web pages relate to Statistic subject from Wikipedia with objectives to check correctness and performance evaluation of combination ranking method. Evaluation of PageRank Scoring show that the highest score does not always relate to Statistic. Since the links within Wikipedia articles exists so that users are always one click away from more information on any point that has a link attached, it it possible that unrelated topics to Statistic are most likely frequently mentioned in the collection. While the combination method show link score which is given proportional weight to content score of Web pages does effect the retrieval results
ANALISA KERAPATAN TRABECULAR BONE BERBASIS GRAPH BERBOBOT PADA CITRA PANORAMA GIGI UNTUK IDENTIFIKASI OSTEOPOROSIS
Get PDFOsteoporosis is bone disease indocated by low bone mass density and micro architectures disorder which lead to bone fragility or fractures. Graph may be useful to describe density of trabeculae bone due to morphological change on mandibular bone in dental panoramic radiographs. The density of trabecular bone can be discribed by generating graph. Trabecular image firstly was transformed to binary image. A white pixel on the binary image presented as part of trabeculae, which assumed as an isolated node on the graph. Graph generation by Erdos and Royi method was used to build connections between an isolated node and others. This paper introduced the use of weight on each node based on probabilities average of its neigbourhoods. Graph’s properties which used to measure the density were degree and cluster coefficient. Both of properties are used to build feature space. Feature space indicated distribution of node on dense or sparse area. Early indication of osteoporosis could be assumed that ratio of nodes on dense area were greater than that on sparse area. We achieved accuration of 54%, sensitivity of 60%, and spesificity of 49%. Keywords: osteoporosis, trabeculae, random graph, graph berbobo