Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Informatics and Communication Technology (IJ-ICT) Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) INFORMAL: Informatics Journal Creative Information Technology Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Indonesian Journal of Electrical Engineering and Computer Science Kaunia: Integration and Interconnection of Islam and Science Journal
MHD. Reza M.I. Pulungan
Department Of Computer Science And Electronics, FMIPA UGM, Yogyakarta
Religion Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Library & Information Science Mathematics Mechanical Engineering Physics Transportation

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : International Journal of Advances in Intelligent Informatics

 1 
A coarse-grained parallelization of genetic algorithms Muhamad Radzi Rathomi; Reza Pulungan
International Journal of Advances in Intelligent Informatics Vol 4, No 1 (2018): March 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i1.137

Abstract

Genetic algorithms are frequently used to solve optimization problems. However, the problems become increasingly complex and time consuming. One solution to speed up the genetic algorithm processing is to use parallelization. The proposed parallelization method is coarse-grained and employs two levels of parallelization: message passing with MPI and Single Instruction Multiple Threads with GPU. Experimental results show that the accuracy of the proposed approach is similar to the sequential genetic algorithm. Parallelization with coarse-grained method, however, can improve the processing and convergence speed of genetic algorithms.
Improving learning vector quantization using data reduction Pande Nyoman Ariyuda Semadi; Reza Pulungan
International Journal of Advances in Intelligent Informatics Vol 5, No 3 (2019): November 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v5i3.330

Abstract

Learning Vector Quantization (LVQ) is a supervised learning algorithm commonly used for statistical classification and pattern recognition. The competitive layer in LVQ studies the input vectors and classifies them into the correct classes. The amount of data involved in the learning process can be reduced by using data reduction methods. In this paper, we propose a data reduction method that uses geometrical proximity of the data. The basic idea is to drop sets of data that have many similarities and keep one representation for each set. By certain adjustments, the data reduction methods can decrease the amount of data involved in the learning process while still maintain the existing accuracy. The amount of data involved in the learning process can be reduced down to 33.22% for the abalone dataset and 55.02% for the bank marketing dataset, respectively.
Co-Authors A Afiahayati Abas Setiawan Agfianto Eko Putra Agus Halid Aji Purwinarko, Aji Anindita Suryarasmi Ardhi Wiratama Baskara Yudha Aslan Alwi Dian Tjondronegoro Dian Tri Wiyanti Gede Saindra Santyadi Gede Sukadarmika Helmi Kurniawan Hermawan Syahputra I Dewa I Dewa Md. Bayu A. Darmawan I Dewa Made Bayu Atmaja Darmawan I Nym Saputra Wahyu Wijaya Ika Oktavia Suzanti Jazi Eko Istiyanto La Surimi Linawati Lutfan Lazuardi Mardhani Riasetiawan Moh Edi Wibowo Muhamad Radzi Rathomi Muhammad Asghar Nazal Muhammad Ihsan Munirah M Ni Made Ary Esta Dewi Wirastuti Nila Feby Puspitasari Nova El Maidah Pande Nyoman Ariyuda Semadi Pramudita, Yoga Dwitya Putu Indah Ciptayani Rachmat Wahid Saleh Insani Radjabaycolle, Jefri Siti Mutmainah Sri Hartati Subanar . Tri Bowo Atmojo Triyono, Gandung Vinod Chandran Wiwin Sulistyo