Sri Handayani, ST, MT, a lecturer in Informatics Engineering at the Faculty of Information and Communication Technology (FTIK) at the University of Semarang (USM), successfully earned a doctorate in the Undip Information Systems Doctoral Study Program after passing her dissertation defense on Thursday, January 15, 2026. The promoters were Prof. Dr. Ir. R. Rizal Isnanto, ST, MM, MT, IPU, ASEAN Eng, and Co-promoter Dr. Budi Warsito, SSi, S.
The defense was chaired by Prof. Ir. Mochamad Agung Wibowo, MM, MSc, PhD, and Secretary Qidir Maulana Binu Soesanto, SSi, MSi, PhD, and Prof. Dr. Edy Winarno, ST, MEng (External Examiner). The first examiner was Dr. Oky Dwi Nurhayati, ST, MT, and the second examiner was Dinar Mutiara Kusumo Nugraheni, ST, M.InfoTech(Comp), PhD. According to Dr. Sri Handayani, ST, MT, students are assets that must be managed by universities, as they are one of the determinants of the survival and quality of universities. This article has been published on TribunJateng.com with the title Sri Handayani ST MT, USM FTIK Lecturer Receives Doctorate Degree in Information Systems UNDIP, https://jateng.tribunnews.com/pendidikan/1240796/sri-handayani-st-mt-dosen-ftik-usm-raih-gelar-doktor-sistem-informasi-undip.
“Higher education institutions must be able to maintain relationships with students, starting from attracting prospective students, managing registered students, to building relationships with alumni and alumni users. Universities sometimes have limited data about their students and alumni,” said Dr. Sri Handayani. “The application of co-training algorithms in student management is an alternative to overcome the limited amount of student data (labeled). Labeled data can be used to train models, because the amount needed is only between 1 percent and 10% and is representative enough to provide meaningful information,” she added. She further added that Co-training is designed to work with a limited dataset of labeled data, while the rest is unlabeled. This model relies on unlabeled data to improve training. This dissertation analyzes how to identify students as potential college customers using semi-supervised machine learning methods. This article has been published on TribunJateng.com with the title Sri Handayani ST MT, USM FTIK Lecturer Receives Doctorate Degree in Information Systems UNDIP, https://jateng.tribunnews.com/pendidikan/1240796/sri-handayani-st-mt-dosen-ftik-usm-raih-gelar-doktor-sistem-informasi-undip.
