Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal JOIV : International Journal on Informatics Visualization
Nurul Aswa Omar
Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Patient’s Cancer Categorization Based On Jaccard and Venn Techniques Nurul Aswa Omar; Riswan Efendi; Norfaradilla Wahid; Afiq Luqman Mohd Yasin
JOIV : International Journal on Informatics Visualization Vol 2, No 3-2 (2018): The Diversity in Information Systems
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (937.424 KB) | DOI: 10.30630/joiv.2.3-2.135

Abstract

Under some circumstances, hospitals and clinics need to know the preliminary patient’s disease categorization, such as H1N1, Dengue, HIV/AIDS and others. However, categorizing patients will be useful in the future if the hospitals  properly recorded their patient criteria and crucial details such as patient’s name, symptoms, temperature and others. There are many benefits by grouping the patients together such as the hospitals will know how to provide an appropriate medicine to the patient, which patient will get the highest priority and should be quarantined.  It is very important to know how to group the patients by using their symptoms detected. This study will focus on patients with cancer problems using Jaccard index and Venn diagram techniques. Their data will be collected from a hospital and the patients are selected randomly. Patients with lungs, brain and breast cancer will be selected in this study.
X-Similarity Comparison by using Wordnet Shahreen Kasim; Nurul Aswa Omar; Nurul Suhaida Mohammad Akbar; Rohayanti Hassan; Masrah Azrifah Azmi Murad
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (956.137 KB) | DOI: 10.30630/joiv.1.4-2.79

Abstract

Semantic web is an addition of the previous one that represents information more significantly for humans and computers. It enables the description of contents and services in machine readable form. It also enables annotating, discovering, publishing, advertising and composing services to be programmed. Semantic web was developed based on Ontology which is measured as the backbone of the semantic web. Machine-readable is transformed to machine-understandable in the current web. Moreover, Ontology provides a common vocabulary, a grammar for publishing data and can provide a semantic description of data which can be used to conserve the Ontology and keep them ready for implication. There are many that used in feature based in semantic similarity. This research presents a single ontology of X-Similarity feature based method.
Co-Authors Afiq Luqman Mohd Yasin Masrah Azrifah Azmi Murad Norfaradilla Wahid Nurul Suhaida Mohammad Akbar Riswan Efendi Rohayanti Hassan Shahreen Kasim