Penerapan Support Vector Machine Untuk Jalur Peminatan Program Studi

Authors

  • Dion Krisnadi Universitas Pelita Harapan
  • Nadya D. Bachtiar Universitas Pelita Harapan
  • Samuel Lukas Universitas Pelita Harapan
  • Pujianto Yugopuspito Universitas Pelita Harapan
  • Petrus Widjaja Universitas Pelita Harapan

Keywords:

Major study, Informatics department, Support Vector Machines, Curriculum

Abstract

It is common that in a curriculum of field of study provides some electives subjects to be selected by their students. Some electives subjects are grouped into a major study. Universitas Pelita Harapan Informatics department offers three major studies. They are Software Engineering, Medical Informatics and Intelligent & Interactive Media. These majors are provided in order to fit interest of the students. Students must choose one major for persuing their degree after they finished the first two years studies. This paper discusses on how to implement the Support Vector machines technology for helping students in determining their major based on their academic records. The inputs of the system ere grades of the subjects of the first two years studied and the outputs is the GPA of the electives subjects for each major.

References

Samuel Lukas, Meiliayana, William Simson, 2009. Penerapan Logika Fuzzy dalam pengambilan Keputusan untuk Jalur Peminatan Mahasiswa. Kampus Renon, STMIK STIKOM Bali, Konferensi Nasional Sistem & Informatika 2009, 14 November, 2009, Bali, Indonesia.

Kecman V., 2014. Support Vector Machines – An Introduction. The University of Auckland, School of Engineering, Auckland, New Zealand.

Veropoulos K., Cristianini N., and Campbell C., 1999. The Application of Support Vector Machines to Medical Decision Support: A Case Study, Department of Engineering Mathematics, Bristol University, Bristol BS8 1TR, United Kingdom.

Fernandez R., 1999. Predicting Time Series with a Local Support Vector Regression Machine. Institut Galilee, Paris, Prancis.regresi

Arif Pratama, Randy Cahya Wihandika, Dian Eka Ratnawati, 2018. Implementasi Algoritma Support Vector Machine (SVM) untuk Prediksi Ketepatan Waktu Kelulusan Mahasiswa, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, Vol. 2, No. 4. April 2018, pp. 1704-1708

Yugopuspito P., Samuel Lukas, I Made Murwantara, Steven Albert, Hery, 2019. A Novel Fishing Finder Technique Based on VMS Data in Indonesia. ACM Conference Proceedings The 3rd International Conference on Advances in Artificial Intelligence (ICAAI 2019, Bahcesehir University, Istanbul, Turkey. pp. 107-111

Lukas S., Dina Stefani, Petrus W., 2019. Comparing SVM and GLM in Calculating Insurance Premium for Flight Delay. ACM Conference Proceedings The 3rd International Conference on Advances in Artificial Intelligence (ICAAI 2019, Bahcesehir University, Istanbul, Turkey. pp. 141-145

Downloads

Published

2020-08-19

How to Cite

Dion Krisnadi, Nadya D. Bachtiar, Samuel Lukas, Pujianto Yugopuspito, & Petrus Widjaja. (2020). Penerapan Support Vector Machine Untuk Jalur Peminatan Program Studi. Prosiding SISFOTEK, 4(1), 287 - 290. Retrieved from http://seminar.iaii.or.id/index.php/SISFOTEK/article/view/235

Issue

Section

2. Rekayasa Sistem Informasi