Senescence is the gradual degeneration of function characteristic of most complex life forms. Bioinformatics is a multidisciplinary research that combines biology, computer science, mathematics and statistics into a general field that will have erudite percussion on all fields of life sciences. In this paper, considering the senescence data gathered from four model organisms which are lumbricina (worm), saccharomyces (yeast), diptera (fly), and mus (mouse). By applying the classification

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... like Naïve Bayes, 1-Nearest Neighbour, it gives less efficiency. To increase the efficiency, new attribute selection methods are proposed which uses the Support Vector Machine (SVM) algorithm to organize the senescence-related data. The intention of these hierarchical attribute selection methods which uses the SVM algorithm, to organize organism genes into either anti-longevity or pro-longevity genes that gives the better results than with the use of Naïve Bayes algorithm.