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All Journal International Conference on Education and Language (ICEL) Technomedia Journal CCIT (Creative Communication and Innovative Technology) Journal ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) IAIC Transactions on Sustainable Digital Innovation (ITSDI) Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Sisfotek Global Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Pengabdian Sosial
Nasril Sany
Institut Teknologi PLN
Religion Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Nursing Public Health Social Sciences Other

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Prediction of Student Major Selection at High School Using a Machine Learning Approach Sany, Nasril; Dody, Dody; Muchlis, Esa Firmansyah; Hasanudin, Muhaimin; Berlinton, Budi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 4 No. 1 (2025): March 2025
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v4i1.4983

Abstract

The primary objective of this research was to develop and evaluate a machine learning prediction system that matches Senior High School (SMA) Nusa Putra Kota Tangerang students with their potential school majors based on their academic interests and performance levels. This research method employs machine learning algorithms, including Random Forest, Support Vector Machine (SVM), logistic regression, K-Nearest Neighbor (K-NN), and Naive Bayes, using academic records, interest tests, and questionnaires for data collection. The data was processed and analyzed to train and test the algorithm. The findings of this study indicate that the Random Forest algorithm achieved the best performance among the models, with an accuracy of 85%, a precision of 82%, a recall of 88%, and an AUC score of 0.92. The factors that affected the prediction of major selection were Grade XII Mathematics scores and Science Interest Test results. The research implications suggest that Random Forest technology within Machine Learning (ML) enhances major selection accuracy while promoting fairness, providing superior educational choices and increased student satisfaction. Future studies should investigate additional factors that influence this phenomenon.
Pengenalan Energi Baru Terbarukan melalui Media Pembelajaran Interaktif pada Tingkat Pendidikan Dasar Chairat, Arief Suardi Nur; Ridwan, Muhammad; Prayudi, Prayudi; Sany, Nasril; Dody, Dody; Kusumastuti, Dyah Pratiwi; Vaza, Hery; Asnul, Nur Shania
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 6, No 1 (2026): Abdira
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v6i1.1216

Abstract

Global warming has become a major concern due to its impacts on the environment and human life. One way to reduce these impacts is by increasing the use of renewable energy. Introducing the concept of renewable energy at the elementary school level is expected to foster students’ awareness and understanding of the importance of using clean energy. This Community Service (PkM) program aims to enhance the knowledge and understanding of students and teachers at SD Islam Al Azhar 5, West Jakarta, regarding solar-based renewable energy through an interactive learning approach. The activities were carried out in several stages, including survey, socialization, training, evaluation, and sustainability. The socialization session was delivered through material presentations supported by engaging visual media, while the training involved assembling toys powered by solar energy. The results showed strong enthusiasm, improved understanding of renewable energy among students and teachers, and enhanced teacher skills in implementing interactive learning. This program also encouraged greater awareness of the importance of adopting renewable energy in daily life.
Co-Authors AA Sudharmawan, AA Alfalah, Win Andi Saputra Asnul, Nur Shania Berlinton, Budi Chairat, Arief Suardi Nur Dedy Iskandar Dedy Iskandar Dian Sugiarto Dody Dody Dody, Dody Dony Saputra Eka Indriani Emilia Emilia Firmansyah Apryadhi Hanum, Gilang Kartika Haryanto Haryanto Hendri Hendri Kusumastuti, Dyah Pratiwi Muchlis, Esa Firmansyah Muhamad Kurniawan, Muhamad Muhammad Ridwan Mulyati Mulyati N Harefa, Anggie Grace Nur Hikmah Nur Hikmah Palupiningsih, Pritasari Prayudi Prayudi Putra, Dimas Ariwibowo Putra, Rizki Pratama Rusjdi, Halim S, Achmad Rachmat Sugiarto, Dian Sutrisno, Sigit Suwarto Suwarto Utami Wahyuningsih Vaza, Hery