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All Journal Indonesian Journal of Contemporary Multidisciplinary Research Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Naza Sefti Prianita
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Penerapan Metode C4.5 dan K-Nearest Neighbor untuk Klasifikasi Kelulusan Mahasiswa Berdasarkan Data Akademik Dina Amalia Putri; Naza Sefti Prianita; Elkin Rilvani
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v3i4.1032

Abstract

The issue of determining the number of students' graduation times is one of the important indicators in transmitting the quality and effectiveness of the higher education process in universities. The rate of on-time graduation not only impacts accredited institutions, but also becomes a concern for campus management in designing learning strategies and academic guidance. This study aims to apply and compare two classification algorithms in data mining, namely C4.5 and K-Nearest Neighbor KNN, in predicting the accuracy of students' graduation times. Predictions are made based on academic attributes such as Grade Point Average GPA, number of credits that have been achieved, and Semester Grade Point Average IPS as input variables. The method used in this study is Knowledge Discovery in Database KDD which includes data selection, preprocessing, transformation, data mining, and evaluation of results. The study was conducted using the RapidMiner tool, with a dataset of 279 Informatics Study Program students from the 2015 to 2019 intake. The data was classified into two categories: "graduated on time" and "not graduated on time". The test results showed that the KNN algorithm provided better performance compared to C4.5. KNN produced an accuracy of 76.08%, with a precision of 73.11% and a recall of 41.92%. Meanwhile, the C4.5 algorithm produced an accuracy of 73.49%, with a precision of 64.62% and a recall of 41.89%. This difference in accuracy indicates that KNN is more effective in capturing patterns in the data and providing more accurate predictions in this context. Thus, the KNN algorithm can be considered a more optimal method to assist universities in predicting potential student admissions in a timely manner, thus enabling early intervention for students at risk of late graduation. This research also contributes to the development of data mining-based academic decision support systems in higher education.
The Role of Social Media in Developing an Online Learning Community for Islamic Religious Education Prasetyo, Fabian Eka; Roswanda Nuraini; Naza Sefti Prianita; H. Amali
Indonesian Journal of Contemporary Multidisciplinary Research Vol. 3 No. 3 (2024): May 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/modern.v3i3.9100

Abstract

Social media has become a crucial platform for supporting and developing online learning communities for Islamic education. This platform provides easy access for individuals and groups to share knowledge, experiences, and perspectives related to Islam globally. In online learning communities, social media acts as a bridge connecting students with educators, scholars, and fellow learners from various backgrounds and geographic regions. Interactive features such as discussion forums, study groups, and Q&A sessions enable active and collaborative participation in the learning process. Additionally, social media provides a space for sharing educational content such as articles, videos, and podcasts that enrich the understanding of Islamic region. However, it is important to maintain the quality of content and ensure the accuracy of the information shared. By utilizing social media wisely, online learning communities for Islamic education can grow and contribute positively to the enhancement of religious understanding and practices in the digital age
Co-Authors Dina Amalia Putri Elkin Rilvani H. Amali Prasetyo, Fabian Eka Roswanda Nuraini