Judul: Image Searching Using Heuristic Method for Image Retrieval System.
Abstrak: The development of image retrieval system and user demand for a fast and accurate search engine motivates research on finding efficient retrieval methods. Commonly, image searching process works through computing and comparing similarity value between input query and entire database images. This process is not efficient due to time-wasting during computation especially for large database. This research proposes heuristic method for image searching. The basic idea of this research deals with structural database content that reduces searching time. This research implements fitness landscape model. Fitness landscape is kind of directed graph whose labeled vertices and edges. Each node represents an image and each edge represents distance or similarity value of a node to other connected nodes. Similarity value between nodes are computed using combination of three image features, those are color, shape, and texture. Heuristic algorithm moves on these nodes with Breadth-First Search mechanism under certain constraints. Each visited node that fulfills the requirement will be retrieved as searching result. This retrieval result is then evaluated using recall precision parameter to get value of searching effectiveness. This experiment also computes retrieval time for each query. As the result, heuristic method obtains average retrieval time up to nine times faster compared with the non-heuristic one. Hence, this proposed method is promising to be used in image retrieval system because it provides fast image searching. Keywords: image searching, fitness landscape, heuristic, content based image retrieval.
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Judul: Algoritme Genetika untuk Optimasi Pembobotan Fitur pada Temu Kembali Citra
Abstrak: Content based image retrieval is developed to retrieve image based on color, shape, and texture feature. One of the problems to be solved in content based image retrieval is how to combine these features to get the optimum retrieval result. Combining multiple features in image retrieval process can be implemented using feature weight assignment. One of feature weight assignment methods is each feature weight is assigned by hand. However this approach is subjective and lack of theory foundation. In this research an automatic feature weight assignment approach based on genetic algorithm is proposed. Genetic algorithm is used for optimizing feature weight in order to get the optimum retrieval result. Image features is used in this research are color, shape, and texture feature. In genetic algorithm, a chromosom represented by features weight. These chromosomes get into genetic operator process such as selection, crossover, and mutation until maximum generation is reached. Result of genetic algorithm process get an optimum feature weight. It used for image retrieval process. The retrieval evaluation used recall precision graphic. The experiment showed feature weight assignment based on genetic algorithm can improve average precision in image retrieval.
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Judul: Purifikasi dan Karakterisasi Mangan Peroksidase (MnP) dari Isolat Leiotrametes flavida Galur ZUL62 dan Cerrena sp
Abstrak: Mangan Peroksidase (MnP) merupakan salah satu enzim ekstraseluler yang dihasilkan oleh jamur pelapuk putih. Leiotrametes flavida galur ZUL62 dan Cerrena sp. merupakan kelompok jamur pelapuk putih. Penelitian sebelumnya menyatakan bahwa kedua jamur tersebut memiliki potensi dalam menghasilkan MnP. Tujuan penelitian ini adalah melakukan purifikasi dan karakterisasi MnP dari kedua isolat. Leiotrametes flavida memiliki aktivitas tertinggi pada hari ke-4 setelah inkubasi, sedangkan Cerrena sp. pada hari ke-5. Aktivitas spesifik tertinggi diperoleh pada fraksi hasil desalting dengan aktivitas sebesar 9456.7 U/mg (Leiotrametes flavida) dan 6555.48 U/mg (Cerrena sp.). pH optimum kedua isolat yaitu pada pH 5, sedangkan suhu optimum Leiotrametes flavida yaitu 40 ºC dan Cerrena sp. 30 ºC. 2,6-Dimethoxyphenol (DMP) digunakan sebagai substrat untuk aktivitas enzim. MnP isolat Leiotrametes flavida memiliki nilai Vmaks 0.55 U/mL dengan km sebesar 1.89x10-1 mM, sedangkan MnP dari Cerrena sp. memiliki nilai Vmaks sebesar 0.1371 U/mL dengan km sebesar 0.096 mM. Penambahan ion Mn2+ dan Mg2+ merupakan ion yang dapat meningkatkan aktivitas untuk kedua isolat. sedangkan ion NaN3 dan Fe2+ dapat menghambat aktivitas enzim dari kedua isolat. galur
Keyword: Cerrena sp, jamur pelapuk putih, Leiotrametes flavida, mangan peroksidase