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Bambang Supperianto
Universitas Dehasen Bengkulu

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Automated Medical Classification of Human Brain Tumors Leveraging the Xception Convolutional Neural Network Bambang Supperianto; Yuhandri; Sarjon Defit
Jurnal KomtekInfo Vol. 13 No. 2 (2026): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v13i2.679

Abstract

Student major recommendations are compiled to help students in the Communication Studies Program at the Faculty of Social Sciences, Dehasen University, Bengkulu, determine the most suitable concentration based on academic characteristics and learning data patterns. Based on this, the purpose of this study is to analyze major recommendations for students in the Communication Studies Program at the Faculty of Social Sciences, Dehasen University, Bengkulu, based on course grades.The Simple Multi-Attribute Rating Technique (SMART) was used in the process of weighting and assessing academic criteria, while K-Means was used to form major clusters based on the assessment results. This data set consists of 103 communication science students from the Faculty of Social Sciences obtained from the Dehasen Bengkulu University academic information system portal. The results of this study can recommend majors for Communication Science students at the Faculty of Social Sciences, Dehasen Bengkulu University, based on a decision support system. Based on the research results, Journalism was the most popular major with 63 students. This shows that students are more interested in journalism than in other majors. Meanwhile, Public Relations was chosen by 40 students. The contribution of this research is to improve the accuracy of student major selection in the Communication Studies Program, Faculty of Social Sciences, Dehasen University of Bengkulu. The use of the K-Means algorithm and the SMART method enables the Communication Studies Program, Faculty of Social Sciences, Dehasen University of Bengkulu to be more objective and efficient in the process of managing academic majors.