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All Journal International Journal of Computing Science and Applied Mathematics-IJCSAM
Dwi Ratna Sulistyaningrum
Institut Teknologi Sepuluh Nopember
Mathematics

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Application of Daubechies Wavelet Transformation for Noise Rain Reduction on the Video Siti Khotijah; Dwi Ratna Sulistyaningrum
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 5 No. 1 (2019)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

Put option is a contract to sell some underlying assets in the future with a certain price. On European put options, selling only can be exercised at maturity date. Behavior of European put options price can be modeled by using the Black-Scholes model which provide an analytical solution. Numerical approximation such as binomial tree, explicit and implicit finite difference methods also can be used to solve Black-Scholes model. Some numerical methods are applied and compared with the analytical solution to determine the best numerical method. The results show that numerical approximations using the binomial tree is more accurate than explicit and implicit finite difference method in pricing European put options. Moreover when the value of T is higher then the error obtained is also higher, while the error obtained is lower when the value of N is higher. The value of T and N cause the increase of the computation time. When the value of T is higher the computation time is lower, while computation time is higher if the value of N is higher. Overall, the lowest computation time is obtained by using an explicit finite difference method with an exceptional as the value of T is big and the value of N is small. The lowest computation time is obtained by using a binomial tree method.
Texture-Based Woven Image Classification using Fuzzy C-Means Algorithm Soetrisno Soetrisno; Dwi Ratna Sulistyaningrum; Isi Bifawa’idati
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 8 No. 1 (2022)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

There are a lot of texture-based image data stored in the storage media Internet. Most of these data portray the cultural fabric texture results from a State. Because of the many variants of the existing texture, the data need to be easily accessible through the Internet. Moreover, the area of origin of weaving the surface is easily known. Therefore, it is necessary to develop a classification system based on woven image data. The texture of the image data stored in a database on the Internet can be grouped/clustered well, making it easy to access. This study examines a texture-based woven image classification using fuzzy c-means algorithm. This method combines extraction methods Gabor filter, fuzzy c-means algorithm and Euclid distance similarity measure. An experiment was done using the system as many as 60 woven images from Bali, NTT and Central Java areas, each taken as many as 25 images weaving. The test results stated that testing using the test images taken from the images in the database generates a 100% accuracy rate, and testing using test images taken from outside the database produces an accuracy rate of 94%.
Co-Authors Isi Bifawa’idati Siti Khotijah Soetrisno Soetrisno