cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tole Sutikno
Contact Email
-
Phone
-
Journal Mail Official
ij.aptikom@gmail.com
Editorial Address
9th Floor, 4th UAD Campus Lembaga Penerbitan dan Publikasi Ilmiah (LPPI) Universitas Ahmad Dahlan
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Computer Science and Information Technologies
Published by Institute of Advanced Engineering and Science
ISSN : 2722323X     EISSN : 27223221     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Computer Science and Information Technologies ISSN 2722-323X, e-ISSN 2722-3221 is an open access, peer-reviewed international journal that publish original research article, review papers, short communications that will have an immediate impact on the ongoing research in all areas of Computer Science/Informatics, Electronics, Communication and Information Technologies. Papers for publication in the journal are selected through rigorous peer review, to ensure originality, timeliness, relevance, and readability. The journal is published four-monthly (March, July and November).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol 2, No 3: November 2021" : 6 Documents clear
Hancitor malware recognition using swarm intelligent technique Ibrahim, Laheeb M.; Kamal, Maisirreem Atheeed; Al-Alusi, AbdulSattar A.
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p103-112

Abstract

Malware is a global risk rife designed to destroy computer systems without the owner's knowledge. It is still regarded as the most popular threat that attacks computer systems. Early recognition of unknown malware remains a problem. Swarm intelligence (SI), usually customer societies, communicate locally with their domain and with each other. Clients use very simple rules of behavior and the interactions between them lead to smart appearance, noticeable, individual behavior and optimized solution of problem and SI has been successfully applied in many fields, especially for malware ion tasks. SI also saves a considerable amount of time and enhances the precision of the malware recognition system. This paper introduces a malware recognition system for Hancitor malware using the gray wolf optimization algorithm (GWO) and artificial bee colony algorithm (ABC), which can effectively recognize Hancitor in networks.
Low power network on chip architectures: A survey Raza Naqvi, Muhammad
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p158-168

Abstract

Mostly communication now days is done through system on chip (SoC) models so, network on chip (NoC) architecture is most appropriate solution for better performance. However, one of major flaws in this architecture is power consumption. To gain high performance through this type of architecture it is necessary to confirm power consumption while designing this. Use of power should be diminished in every region of network chip architecture. Lasting power consumption can be lessened by reaching alterations in network routers and other devices used to form that network. This research mainly focusses on state-of-the-art methods for designing NoC architecture and techniques to reduce power consumption in those architectures like, network architecture, network links between nodes, network design, and routers.
Classification of mammograms based on features extraction techniques using support vector machine Hussein Saeed, Enas Mohammed; Saleh, Hayder Adnan; Khalel, Enam Azez
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p121-131

Abstract

Now mammography can be defined as the most reliable method for early breast cancer detection. The main goal of this study is to design a classifier model to help radiologists to provide a second view to diagnose mammograms. In the proposed system medium filter and binary image with a global threshold have been applied for removing the noise and small artifacts in the pre-processing stage. Secondly, in the segmentation phase, a hybrid bounding box and region growing (HBBRG) algorithm are utilizing to remove pectoral muscles, and then a geometric method has been applied to cut the largest possible square that can be obtained from a mammogram which represents the ROI. In the features extraction phase three method was used to prepare texture features to be a suitable introduction to the classification process are first order (statistical features), local binary patterns (LBP), and gray-level co-occurrence matrix (GLCM), finally, SVM has been applied in two-level to classify mammogram images in the first level to normal or abnormal, and then the classification of abnormal once in the second level to the benign or malignant image. The system was tested on the MAIS the Mammogram image analysis Society (MIAS) database, in addition to the image from the Teaching Oncology Hospital, Medical City in Baghdad, where the results showed achieving an accuracy of 95.454% for the first level and 97.260% for the second level, also, the results of applying the proposed system to the MIAS database alone were achieving an accuracy of 93.105% for the first level and 94.59 for the second level.
Visualisation for ontology sense-making: A tree-map based algorithmic approach Vidanage, Kaneeka; Mohamad Noor, Noor Maizura; Mohemad, Rosmayati; Bakar, Zuriana Abu
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p147-157

Abstract

Ontology sense-making or visual comprehension of the ontological schemata and structure are vital for cross-validation purposes of the ontology increment during the process of applied ontology construction. Also, it is important to query the ontology in order to verify the accuracy of the stored knowledge embeddings. This will boost the interactions between domain specialists and ontologists in applied ontology construction processes. Hence existing mechanisms have numerous of deficiencies (discussed in the paper), a new algorithm is proposed in this research to boost the efficiency of usage of tree-maps for effective ontology sense making. Proposed algorithm and prototype are quantitatively and qualitatively assessed for their accuracy and efficacy.
Virtual assistant upper respiratory tract infection education based natural language Suwarningsih, Wiwin
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p132-146

Abstract

The high incidence of upper respiratory tract infection (URTI) in Indonesia requires an efficient healthcare solution to maintain human wellbeing. The e-health education model proposed in this paper is a virtual assistant in the form of an interactive question and answer system assistant virtual interactive question answering (AVIQA) with a natural language approach. AVIQA is a form of problem-solving approach to design some aspects of education and consultation in helping parents to recognize symptoms and dealing with several preventive actions for toddlers when exposed to Upper Respiratory Tract Infection. The technologies proposed for the development of AVIQA include (i) Representation of sentence meanings to build an URTI knowledge base; (ii) Design of dialogue models for interactive consultation using a combination between information state and frame base model and (iii) Development of IQA based on casebase reasoning and semantic role labelling. The purpose of developing this technology is to achieve a system that is capable of assisting the users especially mothers in searching for information, reducing user time compared to reading a document, and providing a good advice for finding the right answers, which then can be constructed from a management model prototype information for the education and independent consultation for users. The final result of this study is e-health education system based Indonesian natural language that has an ability in terms of health consultations especially health of children under five in acute respiratory infection disease. This system is expected to have a significant impact on the ability of a mother to recognize symptoms and deal with children attacked by URTI.
Less computational approach to detect QRS complexes in ECG rhythms Younes, Tariq M.; Alkhedher, Mohammad; Al Khawaldeh, Mohamad; Nawash, Jalal; Al-Abbas, Ibrahim
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p113-120

Abstract

Electrocardiogram (ECG) signals are normally affected by artifacts that require manual assessment or use of other reference signals. Currently, Cardiographs are used to achieve basic necessary heart rate monitoring in real conditions. This work aims to study and identify main ECG features, QRS complexes, as one of the steps of a comprehensive ECG signal analysis. The proposed algorithm suggested an automatic recognition of QRS complexes in ECG rhythm. This method is designed based on several filter structure composes low pass, difference and summation filters. The filtered signal is fed to an adaptive threshold function to detect QRS complexes. The algorithm was validated and results were checked with experimental data based on sensitivity test.

Page 1 of 1 | Total Record : 6

 1 

Filter by Year

2021 2021


Reset
Filter By Issues
All Issue Vol 6, No 3: November 2025 Vol 6, No 2: July 2025 Vol 6, No 1: March 2025 Vol 5, No 3: November 2024 Vol 5, No 2: July 2024 Vol 5, No 1: March 2024 Vol 4, No 3: November 2023 Vol 4, No 2: July 2023 Vol 4, No 1: March 2023 Vol 3, No 3: November 2022 Vol 3, No 2: July 2022 Vol 3, No 1: March 2022 Vol 2, No 3: November 2021 Vol 2, No 2: July 2021 Vol 2, No 1: March 2021 Vol 1, No 3: November 2020 Vol 1, No 2: July 2020 Vol 1, No 1: May 2020 List of Accepted Papers (with minor revisions) More Issue