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Thesis Defence of Doctoral in Information Technology : Andini Sintawati and Onny Marleen


On 21st March 2012, Doctoral Program Gunadarma University conducted doctoral thesis defence in Informastion Technologu at Auditorium of Gunadarma University, Pondok Cina, Depok.

The first session given oppurtunity to promovenda Andini Sintawati who defended her dissertation title "Strategies and Methods for Ontology Versioning Object Tracking Taxonomic Diversity of Botany", which promoted by Prof. Dr. I Wayan Simri Wicaksana, SSi., MEng and Dr.rer. nat. I Made Wiryana, SKom., MAppSc with Dr. Lintang Y. Banowosari, SKom., MSc as co-promoter.In her dissertation Promovenda Andini SIntawati do research to find method that track object in common ontology in the case of diversity of plants/plant. Taxonomic changes often occur inplants vertically (changing levels) and horizontally (change group). To detect an object (species name) then used the model to represebt the plant taxonomy ontology. Obtology object search on different ontology (ontology versioning) can be done with the model semantics or formal representasion.

The Senate Commitee of Gunadarma University determine this promovenda Andini Sintawati was graduated with honors and 46th a Doctor of Information Technology in Gunadarma University.

The second session with promovenda Onny Marleen, who defended her dissertation entitled " Lessions in Image Segmentation Method with Morphological Image Servicografi and Gray Level Support Cooccurrence Matrice as Precancerous and Cervical Cancer Diagnosis". which promoted by Prof. Dr. dr. Johan Harlan and Prof. Dr. Sarifuddin Madenda with Dr. dr. Junita Indarti, SpOG as co-promoter.

The purpose of the research promovenda Onny Marleen is making a prototype as a tool to detect areas of precancerous lesions and cervical cancer by utilizing image processing disciplines. Making the prototype consists of three main processes, namely the removal of the reflected beam, lesion segmentation and texture extraction or analysis. Color segmentation is done by using a threshold value. Image morphology is used to identify and extract candidate area of the lesion. Analiis texture contrast and implemented with the parameters in the Gray Level Cooccurrence homogeneous matrice, which is used to calculate the surface roughness of the lesion.

The results of research is a prototype that can identify and locate the lesion candidate area through color-based segmentation of lesions and the degree of surface roughness is calculated by using analysis of contrast and texture with homogeneous parameters.

The Senate Commitee of Gunadarma University determine this promovenda Onny Marleen was graduated with honors and 47th a Doctor of Information Technology in Gunadarma University.