by doktorsiundip | Apr 26, 2024 | News
Graduate School Graduation Ceremony
Diponegoro University The 174th period of the information systems doctoral study program has 4 people, 2024 which will be held on: Wednesday, April 24 2024 HOURS
15.00 WIB – finished Main Courtroom, Fl. I, TTB Building. A.
Diponegoro University Postgraduate School
Dr. Usman Ependi
Dr. Ahmad Abdul Chamid
Dr. Arif Setiawan
Dr. Muhammad Arifin
by doktorsiundip | Apr 26, 2024 | News
174th Graduation Ceremony of Diponegoro University
UNDIP’s 174th graduation ceremony was held for the first time at the Muladi Dome, Multipurpose Building (GSG) UNDIP.
For friends who graduate during this period, congratulations on passing the stages to a higher level. Passion to pursue dreams and success in the future
by doktorsiundip | Mar 20, 2024 | News
Muhammad Arifin successfully received a Doctoral degree after a Dissertation Examination at the Information Systems Doctoral Study Program (DSI) in the Main Meeting Room, Building A, Floor 1, Postgraduate School, Diponegoro University (Undip) on Tuesday, March 20 2024
Dr Muhammad Arifin conducted dissertation research with the title “Educational Data Mining Model Based on Gradient Boosted Trees for Predicting Student Academic Performance”
The Examining Team consists of Dr. R.B. Sularto, S.H., M.Hum (Dean of Undip Postgraduate School), Prof. Dr. Rahmat Gernowo, M.Si (Head of DSI Undip Study Program), Prof. Dr. Widowati, S.Si., M.Si. (Promoter), 2. Farikhin, S.Si., M.Sc., Ph.D. (Co Promoter), Dr. Maman Somantri, S.T., M.T. (Examiner 1), Prof. Dr. Adian Fatchur Rochman, S.T., M.T (Examiner 2), and Prof. Dr. Ridwan Sanjaya, S.E., S.Kom., MS.IEC (External Examiner from UNIKA. Soegijapranata Semarang)
According to Dr. Muhammad Arifin, this dissertation research was carried out by building an EDM model for student academic predictions based on the GBT algorithm using academic and non-academic data, finding the most influential features in predicting student academic performance, increasing prediction accuracy by optimizing hyperparameters in the GBT algorithm, and building said Dr. Dr. M. Arifin.
by doktorsiundip | Mar 14, 2024 | News
The Information Systems Doctoral Proposal Seminar Examination at the Postgraduate School of Diponegoro University has been held for the following students:
Name: Lilik Triyono
NIM: 30000322520039
dissertation title: Independent Navigation System for people with visual impairments Using Deep Learning
Tuesday, March 7, 2024
10.00 – 12.00 WIB
Information Systems Doctoral Conference Room
TTB B Building, 5th Floor Diponegoro University Postgraduate School
Jl. Imam Bardjo, SH. No. 5 Semarang
Dear.
1. Prof. Dr. Rahmat Gemowo, M.Si (Promoter Chair of the Session / Head of Information Systems Doctoral Study Program)
2. Prayitno, S.ST., M.T., Ph.D. (Co promoter / Semarang State Polytechnic)
3. Prof. Dr. Kusworo Adi, S.Si., M.T. (Examiner 1 / Undip Faculty of Science and Mathematics)
4.Dr. Darjat, ST., MT.g. (Examiner 2 / Undip Faculty of Engineering)
by doktorsiundip | Mar 7, 2024 | News
SEMARANG- Muria Kudus University (UMK) lecturer Arif Setiawan successfully won a Doctorate degree in the Information Systems Doctoral Study Program (DSI) at Diponegoro University (Undip) after the Dissertation examination in the Main Meeting Room, Building A, Floor 1, Undip Postgraduate School on Wednesday, March 6 2024.
Dr. Arif Setiawan S.Kom M.Cs conducted research entitled “Estimation of Body Weight of Live Shrimp Under Water Using Morphometric Characteristics Based on Digital Image Analysis and Machine Learning”
The Examining Team for the dissertation examination included Dr. R.B. Sularto, S.H., M.Hum (Dean of Undip Postgraduate School), Prof. Dr. Rahmat Gernowo, M.Si (Head of DSI Undip Study Program), Prof. Dr. Ir. Hadiyanto, S.T., M.Sc., IPU (Promoter), Dr. Drs. Catur Edi Widodo, M.T (Co Promoter), Prof. Dr. Kusworo Adi, S.Sc., M.T (Examiner 1), Prof. Dr. Ir. R. Rizal Isnanto, S.T., M.M., M.T., IPU, ASEAN Eng (Examiner 2) and Prof. Dr. Eko Sediyono, M.Kom (External Examiner from UKSW Salatiga).
According to Dr Arif Setiawan, shrimp is a product of marine cultivation that is much needed, and is able to boost the country’s economic output. Measuring the body weight of shrimp during the harvest period is very necessary to determine the condition of the shrimp in the water using a method without catching the shrimp directly.
“The aim of this research is to develop a new method for measuring the body weight of live shrimp in water without catching the shrimp directly, using morphometric characteristics based on digital image analysis and machine learning. The stages of this research consist of 4 stages, namely digital image data acquisition of shrimp, initial processing using edge detection and ROI detection methods, classification to distinguish shrimp from non-shrimp using machine learning methods, and estimating the weight of live shrimp in water using analysis-based morphometric characteristics. digital images and machine learning,” said Dr Arif Setiawan.
