Article Per Year (5 Year)
p-Index From 2021 - 2026
0.702
P-Index
This Author published in this journals
All Journal Fountain of Informatics Journal COMPETITIVE: Journal of Education The Indonesian Journal of Computer Science
Esan, Omobayo
Unknown Affiliation
Religion Computer Science & IT Education Electrical & Electronics Engineering Engineering Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Crime Link Prediction Across Geographical Location Through Multifaceted Analysis: A Classifier Chain Temporal Feature-Data Frame Joins Esan, Omobayo; Isaac Olusegun Osunmakinde; Bester Chimbo
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4627

Abstract

Crime link prediction across geographical locations is vital for law enforcement to uncover hidden connections between crime spanning different areas. Traditional methods often fails to capture the complexity and temporal dynamics of crime data, limiting g their predictive power. This research introduces a novel approach to enhance crime link prediction by leveraging multifaceted analysis that integrates multiple inputs and outputs. A classifier chain transformation is used for sequential multi-label classification, capturing interdependence between crime types across locations. The method facilitates a comphrensive understanding of crime patterns over time. Experiment conducted on South Africa Police Services (SAPS) crime dataset demonstrate the proposed model's superior performance compared to state-of-the-art methods, achieving precision, recall, F1-score, and accuracy of 0.98, 0.99,0.99, and 98.99%, respectively. This research aims to contribute to crime link prediction model's, offering a more nuanced and robust framework for forensic experts and law enforcement.
Student Acceptance of Whatsapp Social Media for Teaching and Learning – Case Study of One of Rural Universities in South Africa Esan, Omobayo; Esan, Dorcas Oladayo
COMPETITIVE: Journal of Education Vol. 4 No. 1 (2025): Transformative Education and Learning
Publisher : Perkumpulan Dosen Fakultas Agama Islam Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58355/competitive.v4i1.146

Abstract

This study explores the potential of WhatsApp as an effective knowledge-sharing platform in educational settings, focusing on students' perceptions. This study aims to evaluate WhatsApp acceptance through the UTAUT model by showing the contributing variables to the acceptance of WhatsApp in an undergraduate program at Walter Sisulu University, South Africa. This study was an ex post facto study with 120 samples distributed proportionally. The data were collected through a questionnaire that was developed from UTAUT model variables and based on the hypothesis test showed that facilitating conditions, behavioural intention, effort expectancy, performance expectancy, and social influence significantly and positively affected behavioural intention. Facilitating conditions and behavioural intention significantly and positively affected WhatsApp acceptance. Variables that greatly contributed to higher WhatsApp acceptance were facilitating conditions and behavioural intention. Facilitating conditions were strongly affected by the student knowledge and university assistance in assisting students to download the applications. Meanwhile, the behavioural intention was strongly influenced by the level of student’s belief in WhatsApp and students’ eagerness for WhatsApp to be integrated with their studies. Nevertheless, social influence variables and behavioural intention were also strongly affected by students' use the WhatsApp for learning.
Integration of Virtual Reality to Preserve Nigeria’s Cultural Heritage Using Technology Acceptance Model and Constructivism Learning Theory Esan, Omobayo
Fountain of Informatics Journal Vol. 10 No. 1 (2025): Mei
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v10i1.13821

Abstract

Abstract Nigeria's cultural heritage, encompassing rich traditions, historical landmarks, and intangible practices, faces threats from urbanization, globalization, and inadequate preservation efforts. Virtual Reality (VR) offers an innovative solution for documenting, preserving, and promoting this heritage by creating immersive and interactive experiences. This paper explores the application of VR in preserving Nigeria's tangible and intangible cultural heritage, including oral traditions, traditional festivals, and historical landmarks like the Sukur Cultural Landscape and Osun-Osogbo Sacred Grove. While VR has gained traction globally in cultural heritage preservation, its adoption in Nigeria remains limited due to challenges such as high costs, limited accessibility, and lack of localized content. By addressing these gaps, VR can enhance cultural awareness, engage younger generations, and boost cultural tourism. This study highlights existing works in VR applications for cultural preservation globally and identifies opportunities for tailored VR solutions in the Nigerian context. The findings emphasize the importance of collaborative approaches involving technologists, researchers, and cultural custodians to ensure effective VR integration. Ultimately, the study advocates for leveraging VR to safeguard Nigeria’s cultural legacy, offering innovative pathways to promote its heritage on a global scale while ensuring intergenerational continuity. Keywords: virtual reality (VR), technological acceptance model, constructivism learning theory, cultural heritage
Systematic Literature Review on Crime Prediction using Machine Learning Techniques Esan, Omobayo; Bester Chimbo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4881

Abstract

Abstract contains problem statement, approaches/problem solving method, objectives and resulTo lower the crime rate in the community, many governments around the world have made preventive security measures their top priority. Thus, a major and extensively studied field is the use of machine learning in crime prediction. To investigate crime prediction using machine learning approaches, this study carried out a systematic literature review. The review assesses performance evaluation criteria, forecast methods, present issues, and potential future directions. From 2018 to 2024, a total of 100 research papers covering machine learning techniques for crime prediction were reviewed. The supervised learning approach is the most often used crime prediction technology, according to the review. The evaluation and performance criteria, the tools used to construct the models, and the difficulties they face in predicting crime were also covered. Machine learning approaches for crime prediction are an interesting area of research, and academics have used a number of machine learning models.
Co-Authors Bester Chimbo Esan, Dorcas Oladayo Isaac Olusegun Osunmakinde