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All Journal Information Management For Educators And Professionals (IMBI) Joined Journal (Journal of Informatics Education JURNAL ILMIAH EDUKATIF Knowbase : International Journal of Knowledge in Database Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Teknik Mesin, Industri, Elektro dan Informatika Jurnal Ilmiah Teknik Informatika dan Komunikasi Salus Publica Journal of Information System and Education Development
Sarwo Derta
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Journal : Knowbase : International Journal of Knowledge in Database

 1 
Design of a Decision Support System to Determine Scholarship Recipients at SMKN 2 Padang Panjang Efandari, Ariati; Hari Antoni Musril; Sarwo Derta; Muhammad Iqbal Haikal bin Samia’an
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 1 (2025): June 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i1.10044

Abstract

This research is based on field findings through observations and interviews at SMKN 2 Padang Panjang, which revealed that the process of managing school fee relief scholarship acceptance data is still done manually. This condition causes slow data input processes, slows down administration, and increases the potential for errors in processing student data. Thus, the main focus of this research is to create a valid, practical and effective SPK design in determining scholarship acceptance. This research is a type of Research and Development (R&D) research, using the Analytical Hierarchy Process (AHP) method and the Agile development model. Based on the results of the validity test with 3 lecturers, the system obtained a score of 0.86, indicating a very high level of validity. The practicality test with 3 teachers obtained a score of 0.97, indicating that the system is easy to use. Meanwhile, the results of the effectiveness test with 22 students obtained a score of 0.87, indicating that this system is effective in supporting the scholarship recipient selection process. Unlike previous studies that generally only apply one decision-making method or use conventional development models, this study integrates AHP with an Agile approach to produce a system that is more accurate, practical, and adaptive to school needs. With these achievements, the developed decision support system is worthy of being used as a reliable and efficient tool in determining scholarship recipients at SMKN 2 Padang Panjang.  
Implementation of the C4.5 Algorithm to Build A Prediction Model for Student Success in Database Courses Nanda Pratama Alfyandri; Hari Antoni Musril; Sarwo Derta
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10083

Abstract

This study aims to implement the C4.5 algorithm to build a model for predicting student success in database system courses in the Informatics and Computer Engineering Education study program at UIN Sjech M. Djamil Djambek Bukittinggi. Using the Knowledge Discovery in Database (KDD) approach, this study includes the stages of data selection, cleaning, transformation, modeling, and evaluation. Secondary data from the academic information system of students enrolled from 2018 to 2023 included 1,177 entries, which after cleaning resulted in 1,030 valid data. Predictor attributes consisted of academic factors such as Algorithm Logic scores, 1st semester Grade Point Average (GPA), attendance, and credit load, as well as non-academic factors such as gender and UKT (Tuition Fee Category). The target variable was student success status. Modeling was performed using Altair RapidMiner 2025 software with the C4.5 algorithm, resulting in a decision tree model. Evaluation showed an accuracy of 82.10%, recall of 69.58%, and precision of 62.51%, indicating the algorithm's effectiveness in classifying students as potentially successful or unsuccessful. This model identifies the most influential attributes, both academic and non-academic, on student success. Overall, the application of the C4.5 algorithm supports Educational Data Mining (EDM) in higher education, helping study programs improve the quality of learning and the effectiveness of data-based academic interventions.
Co-Authors Desi Syafitri Efandari, Ariati Fikri Muhammad Firdaus Annas Hari Antoni Musril Lismawarti, Fitra Liza Efriyanti, liza Liza Efriyanti, Liza Efriyanti Marselino Syahputra Muhammad Anis Muharram Muhammad Iqbal Haikal bin Samia’an Nanda Pratama Alfyandri Riri Okra Sadar Martua Haholongan Sir Salfina, Rani Sauki Alfajri Sisca Wendi Harisa Sri Atiqah Tiara Hardiana Putri Tuti Yuniza Zakir, Supratman