Article Per Year (5 Year)
p-Index From 2019 - 2024
2.303
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Jurnal Teknik Elektro Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Perfecting a Video Game with Game Metrics CommIT (Communication & Information Technology) Jurnal Infra International Journal of Industrial Research and Applied Engineering Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Teknik Elektro: Ilmu dan Teknologi
Indar Sugiarto
Petra Christian University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Perfecting a Video Game with Game Metrics

 1 
A NOVEL APPROACH FOR CONFIGURING THE STIMULATOR OF A BCI FRAMEWORK USING XML Indar Sugiarto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 7, No 2: August 2009
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v7i2.579

Abstract

In a working BCI framework, all aspects must be considered as an integral part that contributes to the successful operation of a BCI system. This also includes the development of robust but flexible stimulator, especially the one that closely related to the feedback of a BCI system. This paper describes a novel approach in providing flexible visual stimulator using XML which has been applied for a BCI (brain-computer interface) framework. Using XML file format for configuring the visual stimulator of a BCI system, we can develop BCI applications which can accommodate many experiment strategies in BCI research. The BCI framework and its configuration platform is developed using C++ programming language which incorporate Qt’s most powerful XML parser named QXmlStream. The implementation and experiment shows that the XML configuration file can be well executed within the proposed BCI framework. Beside its capability in presenting flexible flickering frequencies and text formatting for SSVEP-based BCI, the configuration platform also provides 3 shapes, 16 colors, and 5 distinct feedback bars. It is not necessary to increase the number of shapes nor colors since those parameters are less important for the BCI stimulator. The proposed method can then be extended to enhance the usability of currently existed BCI framework such as BF++ Toys and BCI 2000.
Fine-grained or coarse-grained? Strategies for implementing parallel genetic algorithms in a programmable neuromorphic platform Indar Sugiarto; Steve Furber
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15026

Abstract

Genetic Algorithm (GA) is one of popular heuristic-based optimization methods that attracts engineers and scientists for many years. With the advancement of multi- and many-core technologies, GAs are transformed into more powerful tools by parallelising their core processes. This paper describes a feasibility study of implementing parallel GAs (pGAs) on a SpiNNaker. As a many-core neuromorphic platform, SpiNNaker offers a possibility to scale-up a parallelised algorithm, such as a pGA, whilst offering low power consumption on its processing and communication overhead. However, due to its small packets distribution mechanism and constrained processing resources, parallelising processes of a GA in SpiNNaker is challenging. In this paper we show how a pGA can be implemented on SpiNNaker and analyse its performance. Due to inherently numerous parameter and classification of pGAs, we evaluate only the most common aspects of a pGA and use some artificial benchmarking test functions. The experiments produced some promising results that may lead to further developments of massively parallel GAs on SpiNNaker.
Co-Authors Agustinus Bimo Gumelar Alexander Setiawan Andreas Prasetyo Andy Susanto Astri Yogatama Cristian Axenie Derry Pramono Adi Djoni Haryadi Setiabudi Eric Tirtana Evert Oneil Felix Pasila Frismanda Frismanda Gregorio Diovani Wahanie Handy Wicaksono Jehezkiel Hardwin Tandijaya Jörg Conradt Justinus Andjarwirawan Kartika Gunadi Kartika Gunadi Kevin Koesoemo Lauw Lim Un Tung Liliana Liliana Michael Anggreawan Alexander Mohammad Ismail Rahman Mulia Rudy Petrus Santoso Resmana Lim Rudy Adipranata Samuel Febrian Tumewu Saravanakumar Natarajan Siti Halimah Baki Steve Furber Sugiarto Wibowo Suryadi Thiang Thiang Tience Debora Valentina Timothy Joy Siswanto Victor Christian Yohanes TDS Yoken Adinata