Article Per Year (5 Year)
p-Index From 2020 - 2025
1.578
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pilar Nusa Mandiri INTI Nusa Mandiri Jurnal Informatika dan Rekayasa Elektronik Jurnal Teknik Informatika (JUTIF) Jurnal Sistem Informasi SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Teknologi Sistem Informasi Jurnal Aruna Mengabdi (ARMI)
Ganda Wijaya, Ganda
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Pilar Nusa Mandiri

 1 
HYBRID OPTIMIZATION METHOD BASED ON GENETIC ALGORITHM FOR GRADUATES STUDENTS Ridwansyah, Ridwansyah; Wijaya, Ganda; Purnama, Jajang Jaya
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (996.523 KB) | DOI: 10.33480/pilar.v16i1.1180

Abstract

Graduation is a target that must be achieved by students, especially graduating on time will be very important. To determine students who graduate on time or cannot be determined before students reach the final semester and hold a trial, many students who fail to graduate on time cause delays and affect the quality assurance of a tertiary institution. The problem in this research is how to optimize student graduation in order to graduate on time. Therefore, to determine this decision, we conducted a graduation data trial using the SVM method with GA optimization. SVM with accurate learning skills and good generalizations in classifying non-linear data, but SVM is weak in terms of parameter optimization it requires optimization using GA. GA is a method that has evolved to produce a more optimal data. From the results of processing using SVM and GA, we get more optimal results with 86.57%. Then from these results can help students to graduate on time.
Co-Authors Achmad Maezar Bayu Aji Adjat Sudradjat Agung Baitul Hikmah Ali Mustopa, Ali Arief Rusman Desvia, Yessica Fara Henny Destiana Herlina, Maria Jajang Jaya Purnama Kahfi, Ahmad Hafidzul Kholifah, Desiana Nur Mahmud Nawawi, Hendri Mochamad Wahyudi Olivia, Shinta Pratama, Febryawan Yuda Rachman Komarudin Ridwansyah Ridwansyah Ristiyani, Lina Ariska Rudianto, Biktra Sugiono, Sugiono Suhardjono S Sumanto, Sumanto Sumarna Suryadithia, Rachmat Tussyifa, Zaqia Verry Riyanto Wawan Setiawan WITRIANA ENDAH PANGESTI Yudhistira Yudhistira Yudhistira