Browsing by Author "Tutut Herawan"

Now showing 1 - 4 of 4
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    Cluster Validation Analysis on Attribute Relative of Soft Set Theory
    (Springer Link, 2016) Rabiei Mamat; Ahmad Shukri Mohd Noor; Tutut Herawan
    Data clustering on categorical data pose a difficult challenge since there are no-inherent distance measures between data values. One of the approaches that can be used is by introducing a series of clustering attributes in the categorical data. By this approach, Maximum Total Attribute Relative (MTAR) technique that is based on the attribute relative of soft-set theory has been proposed and proved has better execution time as compared to other equivalent techniques that used the same approach. In this paper, the cluster validity analysis on the technique is explained and discussed. In this analysis, the validity of the clusters produced by MTAR technique is evaluated by the entropy measure using two standards dataset: Soybean (Small) and Zoo from University California at Irvine (UCI) repository. Results show that the clusters produce by MTAR technique have better entropy and improved the clusters validity up to 33%.
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    Incremental-Eclat Model
    (Lecture Notes in Electrical Engineering, 2016) Wan Aezwani Bt Wan Abu Bakar; Zailani B. Abdullah; Md. Yazid B. Md Saman; Masita@Masila Bt Abd Jalil; Mustafa B. Man; Tutut Herawan; Abdul Razak Hamdan
    Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. With the aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases or other data repositories, the end product of association rule mining is the analysis of pattern that could be a major contributor especially in managerial decision making. Most of previous frequent mining techniques are dealing with horizontal format of their data repositories. However, the current and emerging trend exists where some of the research works are focusing on dealing with vertical data format and the rule mining results are quite promising. One example of vertical rule mining technique is called Eclat which is the abbreviation of Equivalence Class Transformation.
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    IncSPADE
    (Springer International Publishing Switzerland, 2016) Omer Adam; Zailani Abdullah; Amir Ngah; Kasypi Mokhtar; Wan Muhamad Amir Wan Ahmad; Tutut Herawan; Noraziah Ahmad; Mustafa Mat Deris; Abdul Razak Hamdan; Jemal H. Abawajy
    In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. In order to evaluate this algorithm, we conducted the experiments against three different artificial datasets. The result shows that IncSPADE outperformed the benchmarked algorithm called SPADE up to 20%.
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    Review of Replication Techniques for Distributed Systems
    (LNCS, 2015) Ahmad Shukri Mohd Noor; Nur Farhah Mat Zian; Mustafa Mat Deris; Tutut Herawan
    Distributed systems primarily provide the access to data intensive computation through a wide range of interfaces. Due to the advances of the systems, the scales and complexity of the system have increased, causing faults are likely bound to happen leading into diverse faults and failure conditions. Therefore, fault tolerance has become a crucial property for distributed system in order to preserve its function correctly and available in the presence of faults. Replication techniques particularly concentrates on two fault tolerance manners; masking the failures on the fly as well as reconfiguring the systems in response. This paper presents a brief reviews on different replication techniques, such as Grid Configuration (GC), Box-Shaped Grid (BSG) and Neighbor Replication on Grid (NRG) by comparing and formalizing its communication costs and availabilities analysis based on k-out-of-n model. Each of these techniques presents their own merits and demerits which form the subject matter of this review.