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Thesis Defence of Doctoral in Information Technology: Widya Cholil dan Murni

Doctoral Program Gunadarma University conducted doctoral thesis defence in Information Technology on Friday, July 14, 2017 at Auditorium of Gunadarma University, Campus Depok.
Promovenda Widya Cholil promoted by Prof. Dr. Rer.nat A. Benny Mutiara, Dr. Eri Prasetyo Wibowo and Dr. Prihandoko as a co-promoter was given the opportunity in the first session to presenting her dissertation entitled SimCOBIT; Development of COBIT Model Framework for IT Audit in Indonesia. This research uses AHP (Analytic Hierarchi Process) method which is one of mathematical method that can be used for decision making based on Imperfect Information with Consistent Ratio supported on criteria in COBIT 5.

The dissertation uses the AHP method, so researchers can formulate a new IT Audit framework model, which is the optimized result of the COBIT 5 framework, which will better suit the needs, culture and user understanding of the organization or company in Indonesia in particular.

The open trial resumes for the second session with promovenda Murni supervisor Prof. Dr. Djati Kerami as a promoter, Alhadi Bustamam SSi, M.Kom, Ph. D and Dr. Ernastuti, S.Si, M.Kom as co-promoter with her dissertation entitled Parallel Algorithm of Multiplication Sparse Matrix Based Hypergraph Partitioning In Graphics Processing Unit (GPU). Promovenda in her presentation convey the calculation of multiplication of vector-matrix is needed in solving various calculation problems in real world, like in determining the solution of a system of linear equations. Large matrix size can affect the length of the calculation process is done so that it implicates the akurasu of the calculation results are not real-time

Promovenda in her dissertation uses hypergraph partitioning model to solve the problem. The subsequently designed hypergraph partitioning model is implemented in the Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA) in the C ++ programming language through the determination of blocksize associated with the number of hypergraph partitioning partitions and the parallel reductiin type used in such a way as to obtain optimum speed up. The sparse used is ten randomly generated matrices and one matrix on the design problem of computer components of memory circuit. Based on the multiplication of sparse matrix-vector test results obtained computation time reached 1229 x faster on GPU dibandingkab with CPU.

Based on the results of the commission senate promovenda Widya Cholil and Murni passed with honors and graduate as Doctor of Information Technology University Gunadarma the 112th. Congratulations for achieving this success.