cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Wayan Ordiyasa
Contact Email
wayanordi@gmail.com
Phone
+6281226465721
Journal Mail Official
ijicom@respati.ac.id
Editorial Address
Department of Informatics, University of Respati Yogyakarta
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Informatics and Computation
Published by Universitas Respati Yogyakarta
ISSN : 26858711     EISSN : 27145263     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Informatics and Computation (IJICOM) is an international, peer-reviewed, open-access journal, which publishes original theoretical and empirical work on the science of informatics and its application in multiple fields. Our concept of Informatics includes technologies of information and communication as well as the social, linguistic and cultural changes that initiate, accompany and complicate their development. IJICOM aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices. Scope of this journal including IoT, 5G, Artificial Intelligence, sensor networks, and high-resolution imaging techniques. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 4 Documents
 1 
Search results for , issue "Vol 3 No 2 (2021): International Journal of Informatics and Computation" : 4 Documents clear
Weather Forecasting Analysis using Bayesian Regularization Algorithms Indo Intan
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.35

Abstract

Weather forecasting has become very urgent in various fields of human life, including in big cities. The need for weather forecasting accuracy will be effective and efficient in managing the quality of civilization flexibly. Bayesian regularization is one of the techniques used to obtain accurate results and development of artificial neural networks. The training process achieves the smallest epoch using a general processing unit to solve big data and high resolution. Scenarios performed via dataset partitioning and MSE enhancement. The addition of training data will improve system performance which indicates a significant increasing accuracy. Likewise, the decrease in MSE can increase the system accuracy to achieve a convergence stability point. Weather forecasting can recommend work units within the city and its surroundings, even between provinces or countries.
Pooling Comparison in CNN Architecture for Javanese Script Classification Mujastia Feliati Muhdalifah
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.30

Abstract

Javanese script is evidence of the past culture, which contains various current language learning, including script recognition. However, learning traditional scripts becomes less attractive to the students. Thus, we propose a learning method to enable character recognition among students to deal with the issues. We offer a novel CNN architecture and compare different pooling layers for Javanese script classification. We calculate the separate pooling layer to reduce extensive feature extraction of the image. We present the model comparison results in Javanese character classification to convince our development.
Modern Privacy-Preserving and Security Schemes in Social Networks: A Review Putra Wanda
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.39

Abstract

Online Social Network (OSN) is a popular application to exchange messages over the internet. However, millions of users are still under threat because of protection drawbacks. Many papers have proposed security methods, including firewalls, protocols, cryptography, statistical analysis, even learning algorithms. This paper provides an overview of privacy and security issues and describes multiple OSN protection techniques. We present various security schemes in OSNs and outline existing solutions to mitigate those attacks. This paper also discusses future research directions regarding OSN security problems and techniques.
DeepSkin: Robust Skin Cancer Classification Using Convolutional Neural Network Algorithm Marselina Endah H.
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.40

Abstract

Classification of skin cancer is a growing research topic with significant challenges in the image processing. Learning algorithms for classifying a kind of skin cancer have been presented in recent articles to accelerate the diagnosis process with a rapid and accurate diagnosis. However, effective detection of skin cancer requires extensive graphical data. Inspired by deep learning successful results in computer vision, A Convolutional Neural Network (CNN) is proposed in this study to build a skin cancer classification model. We conduct this experiment by collecting massive skin cancer datasets, conducting pre-processing, training models, and evaluating the performance. Based on the experiment result, the benign and malignant classification model can obtain a good accuracy with a slight loss. Therefore, the results obtained reached an accuracy of 54%.

Page 1 of 1 | Total Record : 4

 1 

Filter by Year

2021 2021


Reset
Filter By Issues
All Issue Vol 3 No 2 (2021): International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation Vol 2 No 2 (2020): International Journal of Informatics and Computation Vol 2 No 1 (2020): International Journal of Informatics and Computation Vol 1 No 2 (2019): International Journal of Informatics and Computation Vol.1, No.2, 2019 Vol 1 No 2 (2019): International Journal of Informatics and Computation Vol 1 No 1 (2019): International Journal of Informatics and Computation