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All Journal IPTEK The Journal of Engineering JURNAL PENGABDIAN KEPADA MASYARAKAT Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Rekayasa Material, Manufaktur & Energi Jurnal EDUCATIO: Jurnal Pendidikan Indonesia Jurnal Ilmiah Teknik Mesin "MEKANIK" Sprocket : Journal of Mechanical Engineering PAKAR Pendidikan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Indonesia Berdaya AEEJ : Journal of Automotive Engineering and Vocational Education Instal : Jurnal Komputer International Review of Practical Innovation, Technology and Green Energy (IRPITAGE) JTPVI: Jurnal Teknologi dan Pendidikan Vokasi Indonesia Abdi Reksa The Indonesian Journal of Computer Science
Hanapi Hasan
Pendidikan Teknik Otomotif, Universitas Negeri Medan
Aerospace Engineering Arts Humanities 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 Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

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Academic Performance Prediction of PTIK Students through Machine Learning Models at Universitas Negeri Medan Tansa Trisna Astono Putri; Reni Rahmadani; Rosma Siregar; Hanapi Hasan
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 7, No 1 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v7i1.29570

Abstract

This study addressed the need for an effective approach to predicting student academic performance in higher education using data-driven methods. The study aimed to implement machine learning models to predict the academic performance of students in the Information and Communication Technology Education Study Program at Universitas Negeri Medan. A quantitative predictive design was employed using a dataset of 40 student records. Five classification models were tested, namely Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Naïve Bayes. The results showed that all models produced strong predictive performance. Decision Tree achieved the highest accuracy at 93.1%, Logistic Regression produced the highest precision at 95.9% and the highest F1-score at 93.2%, while Support Vector Machine obtained the highest recall at 93.2%. These findings indicated that machine learning was feasible for predicting student academic performance in the study program. The study concluded that Logistic Regression provided the most balanced overall performance and had strong potential to support early academic intervention and data-based academic decision making in higher education.
Self-Efficacy: Meningkatkan Jiwa Kewirausahaan Di Era Digital Marta, Rizkayeni; Ganefri; Yulastri, Asmar; Riyanda, Afif Rahman; Hasan, Hanapi; Yunus, Yuliawati
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3641

Abstract

In the digital era which is full of rapid changes and complex challenges, success in the world of entrepreneurship is not only determined by technical knowledge and skills, but also by psychological factors. The entrepreneurial spirit is very important economically and socially so that entrepreneurship is very important both economically and socially. One of the factors driving the entrepreneurial spirit in the digital era is self-efficacy. Self-efficacy is essential for the willingness to act entrepreneurially, to identify and seize opportunities. Self-efficacy plays an important role in building an entrepreneurial spirit. The method for writing this article adopts the literature review method, articles sourced from the Google Scholar, elsevier, tanfonline platforms. In an effort to improve the entrepreneurial spirit in the digital era, contributions from the world of education are needed, so that educational programs can influence individuals' self-efficacy and self-confidence, supporting them to try, learn, and persist in pursuing an entrepreneurial future. Thus, individuals who have high self-efficacy regarding entrepreneurship will have high self-confidence, thereby triggering enthusiasm to become someone who has an entrepreneurial spirit.
Co-Authors Abdullah, MT, Dr. Rijal Afif Rahman Riyanda Agus N Putra Aini Nurul Ambiyar, Ambiyar Asmar Yulastri Bambang Sudarmanta Bayu Angga Wijaya Dahrul Aman Harahap Danang Pujianto Dwiki Muda Yulanto Edwin Agung Wibowo, Edwin Agung Eswanto, Eswanto Eswanto, Eswanto Fadhilah Fadhilah Fahmi Rizal Ganefri Giatman, M Gunawan, Safri Hasan Maksum Irma Yulia Basri Januariyansah, Sapitri Marta, Rizkayeni Marthen Paloboran Martias Martias Muhammad Shiddiq Muhammadon, Muhammad Fairullah Bin Munir, Musbakhul Nizwardi Jalinus Nuzul Hidayat, Nuzul Pakpahan, Binsar Maruli Tua Pamungkas, Okvian Dwi Purwanto, Wawan Putri, Tansa Trisna Astono Rasyid Ridho Harahap Remon Lapisa Reni Rahmadani Riadini Wanty Lubis Rosma Siregar Safri Gunawan Sembiring, Michael Fernando Siman Siman Siman, Siman Simanjuntak, Janter Pangaduan Siregar, Hanafi Sugiarto, Toto Sugiono, Dimas Suprapto Suprapto Waskito Wulansari, Rizky Ema Yuliawati Yunus