Fadil Hamdani

Work place: Engineering Faculty, Department of Informatics, University of Lampung, Bandar Lampung, Indonesia

E-mail: fadil.hamdani@eng.unila.ac.id

Website: https://orcid.org/0000-0002-2814-6496

Research Interests:

Biography

Fadil Hamdani, S.T., M.T., On July 26, 1987. He was born in Bukit Tinggi, Indonesia. He is a lecturer of Electrical Engineering at Lampung University. His bachelor's degree was obtained from the University of Lampung in 2010, and his master's degree was obtained from Institute of technology Bandung in 2018. His main qualifications are in telecommunication systems.

Author Articles
Development of Past Learning Recognition Assessment Data Processing System for Professional Engineer Program Using Scrum Method

By Trisya Septiana Dikpride Despa Fadil Hamdani Deny Budiyanto Reza Andrea

DOI: https://doi.org/10.5815/ijieeb.2025.02.03, Pub. Date: 8 Apr. 2025

The University of Lampung is one of the universities mandated to run the Professional Engineer Program (PPI) through the Past Learning Recognition (RPL) pathway. Individuals following this RPL path must have at least five years of experience in the engineering field, where their education, work, and training data from formal and informal institutions can be converted into six courses totaling 24 credits. The RPL data assessment process, if conducted manually, takes a long time and hampers the administrative process in PPI. Therefore, an effective and efficient assessment process is automated through a web-based application by developing an RPL data final grade processing system (E-RAPEL), which addresses common problems in PPI and facilitates grade administration. The system development adopts the Scrum method to enhance product performance, teamwork, and the work environment. Data collection in this study was conducted through interviews and direct observation, and the results indicate that the system facilitates the final assessment process of RPL data using black box testing. The findings show that all test components functioned as expected and reduced the time required for the RPL data final assessment process in PPI.

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