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Thesis Defence of Doctoral in Information Technology: Mufid Nilmada and Jufriadif Naam


On 25th January 2017, Doctoral Program Gunadarma University conducted doctoral thesis defence in Information Technology at Auditorium of Gunadarma University, Campus D, Jl. Margonda Raya, Pondok Cina, Depok.


As the first candidat, Mufid Nilmada presented his thesis dissertation with title A New Interconnection Network Topology: Enhanced-Extended Fibonacci Cube. The advisors committee are Prof. Dr. Djati Kerami as a Promotor also Dr. Ernastuti, SSi., MKom. and Dr. Sulistyo Puspitodjati, SSi., MSc(CS) as Co-Promotor, and as external examiner is Prof. Dr. Budi Murtiyasa, MKom.


In this research a new model called Enhanced Extended Fibonacci Cube (E2FC) is designed. Graph theoretic approach is employed to analyze structural, enumeration and Hamiltonicity properties in E2FC. Decomposition recursive, isomorphism, Hamming distance and 1-Gray code are used in all proofing steps in this research.


The entirety of the results showed that E2FC has better properties than EFC and EQ, while maintaining the special qualities possessed Fibonacci cube graphs family. This new network model can be used as an alternative option by the user to build a network. The E2FC model can be used as a reference in designing the next network model to be more optimal.


The second candidate is Jufriadif Naam with Prof. Dr. dr. Johan Harlan, S.Si, M.Sc as The Promotor, also Prof. Dr. Sarifuddin Madenda and Dr. Eri Prasetyo Wibowo as CoPromotor, and Dr. Pulus Januar S., drg., MS. as a external examiner. He defended his thesis dissertation with title Development of Morphology Gradient Method For Identifying Proximal Caries In Panoramic Dental X-Ray


This study aims to sharpen and improve the quality of information contained in the image of Dental X-Ray radigraph, namely Panoramic Dental X-Ray, and to clarify the edges of the objects contained in the image, making it easier in the identification of proximal caries and its severity. It applies morphological method, consisting of a process of dilation, erosion and gradient. This study develops a gradient morphology process, which is called multiple Morphology Gradient (mMG)


The results indicate that the image enhancement process in each iteration stage can display caries objects clearly. Thus, it helps facilitate accurate identification of proximal caries and its severity. The improvement in the accuracy detection is 47,5% and the coefficient correlation is 0.7187.


The  Senate Committee of Gunadarma University determined these two candidates were graduated with honors. Doctor Mufid Nilmada and Jufriadif Naam are 101st and 102nd Doctor of Information Technology in Gunadarma University.


Expected from the results of these study can contribute and benefit theoretically and technology development.