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Hapnes Toba
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JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Published by Universitas Kristen Maranatha
ISSN : 24432210     EISSN : 24432229     DOI : https://doi.org/10.28932/jutisi
Core Subject : Science,
Computer Science & IT
Paper topics that can be included in JuTISI are as follows, but are not limited to: • Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Data Analytics • Datawarehouse & Datamining • Decision Support System • E-Systems (E-Gov, E-Health, E-Commerce, etc.) • Enterprise System (SCM, ERP, CRM) • Human-Computer Interaction • Image Processing • Information Retrieval • Information System • Information System Audit • Enterprise Architecture • Knowledge Management • Machine Learning • Mobile Computing & Application • Multimedia System • Open Source System & Technology • Semantic Web & Web 2.0
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 12 Documents
 1   2 
Search results for , issue "Vol 2 No 2 (2016): JuTISI" : 12 Documents clear
Pengembangan Sistem Informasi Website KPU Daerah Istimewa Yogyakarta Argo Wibowo; Budi Susanto
Jurnal Teknik Informatika dan Sistem Informasi Vol 2 No 2 (2016): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v2i2.626

Abstract

Nowadays information is a very important data. Disclosure of information is necessary so the information that  provided could be easily accessed by the public. We need a system where people can get access to information easily, and the system administrator can also process the data with valid information. The provided data must be quickly available to the public. Komisi Pemilihan Umum Daerah Istimewa Yogyakarta (KPU DIY) aware of the importance of the availability of information for the public. KPU DIY already have a website to provide information for public, but they still have access constraints in processing the information independently. So it is necessary to make a change of website management. This research aims to assist KPU DIY in building their website so it can be better used by the public and KPU DIY can independently manage their website content. Results of the questionnaire show that users are more interested, have more same viewpoint, as well as more motivated using the new website. The new website is also considered to be more efficient and new, thus users can use the system properly. Keywords— Content, Independent, Information, System.
Komparasi dan Analisis Kinerja Model Algoritma SVM dan PSO-SVM (Studi Kasus Klasifikasi Jalur Minat SMA) Theopilus Bayu Sasongko
Jurnal Teknik Informatika dan Sistem Informasi Vol 2 No 2 (2016): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v2i2.627

Abstract

Attribute Selection is very important for classification process. This research has been done by doing attribute selection using PSO method (Particle Swarm Optimization) on SVM algorithm (Support Vector Machine). The development of the classification model uses three parameters especially data attribute, influence of the transformation of various kernel function and penalty factor (C) toward the performance of SVM and PSO-SVM classification.  The analysis uses five kernels in mySVM library that existed in Rapidminer application namely dot, radial, polynomial, neural, and anova kernel. The training data used in the first model classification development is student interest data at ABC high school on 2013-2014 year academic.  The first model is evaluated using accuracy, precision, recall, and auc value test. The first result shows that the anova kernel on PSO-SVM is able to work with accuracy level 99.30% using penalty factor 0.1. The second model has been developed to predict student interest in XYZ high school. The second result shows that PSO-SVM with kernel anova is able to classify students interest with 99.29% accuracy level.  Keywords— Optimization, SVM, PSO-SVM, Student Interest. 

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