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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Komtekinfo Jurnal Pengabdian Masyarakat Bangsa JAR'S (Journal of Advanced Research in Informatics)
Budiarti, Lela
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Journal : JAR'S (Journal of Advanced Research in Informatics)

 1 
APLIKASI DATA MINING UNTUK MENENTUKAN LULUSAN MAHASISWA TEPAT WAKTU wendi, Al; Mandopa, Andi; Budiarti, Lela
Journal of Advanced Research in Informatics Vol 3 No 1 (2024): Journal of Advanced Research in Informatics
Publisher : Fakultas Teknik, Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/jars.v3i1.3792

Abstract

Untimely graduation rates have become an important problem in the world of education that can affect the quality of education and cause additional costs for students and educational institutions. This research aims to build a prediction model to predict the acceptance of prospective new students at Graha Nusantara University, especially in the Computer Science study program. In achieving the graduation process, students must meet the requirements including GPA, Gender, Region of Origin, School of Origin. The research results show that the prediction model built using the rule association algorithm in this study had good accuracy, namely 38.3 percent. This research examines the application of data mining methods with the association rule algorithm, to predict student graduation on time at Graha Nusantara University. This research produces findings that this method makes it easier to determine student graduation patterns. Association rule is a data mining technique that finds patterns, dependencies, and connections between items in data. These algorithms can be used to explain patterns in seemingly independent data, such as relational databases and transactional databases.
Rancang Bangun Sistem Pendukung Keputusan Seleksi Karyawan Dengan Metode Multi Attribute Utility Theory. wendi, al; budiarti, lela; mandopa, Andi saputra
Journal of Advanced Research in Informatics Vol 3 No 2 (2025): Journal of Advanced Research in Informatics
Publisher : Fakultas Teknik, Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/jars.v3i2.4184

Abstract

Decision making involving multiple criteria is often a challenge in the selection process, especially when having to choose the best alternative from a number of candidates. This study aims to build a Decision Support System (DSS) that is able to assist the selection process of the best candidates objectively, structured, and efficiently. The method used is the Multi-Attribute Utility Theory (MAUT), which has the ability to handle multi-criteria decision making with a utility approach, where each criterion is weighted based on its level of importance. This system is designed using the UML (Unified Modeling Language) modeling language to present a clear visual representation of the proposed system. The criteria used in the study consist of 5 criteria, namely: Work experience, education, age, status, and web address. Each alternative is assessed based on these five criteria, then the normalization process and calculation of the total utility value are carried out to determine the final ranking. The respondents or samples in this study consisted of 5 students registered in August 2024, from the five samples used, the highest utility result with code A02 in the name of Ahmad Suhery obtained the highest utility value of 0.6893, so that it was determined as the best alternative in the selection process. This system is expected to be a tool to assist in decision making.
Co-Authors Fitri Permata Sari, Fitri Permata Gunadi Widi Nurcahyo Hadiyanto, Tegas Harahap, Ramadhan Mandopa, Andi mandopa, andi saputra Shalsabila, Rizky Silalahi , Nike Sumijan Syahputra, Afriadi Syara, Dinda wendi, al Wirahmadayanti, Isna