DEPARTMENT OF COMPUTER SCIENCE

Attendance management is a key part of academic administration, yet many Nigerian universities
still rely on manual methods prone to errors and impersonation. This study, titled “An
Assessment of User Acceptance of Biometric Fingerprint Attendance Systems in Educational
Institutions,” examined how students of the University of Benin (UNIBEN) perceive and are
willing to adopt biometric fingerprint technology as a modern attendance tool. Using a
descriptive survey design, data were gathered from 85 students across different faculties. Guided
by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of
Technology (UTAUT), the study analyzed factors such as awareness, ease of use, trust, and data
security. Results showed high awareness and positive attitudes toward the technology, though
concerns about privacy and technical support persisted. The study recommends improved
infrastructure, training, and clear data protection measures to enhance user trust and successful
adoption of biometric systems in universities.

Farm produce marketing is the process of moving agricultural products from the farm gate to the final consumer through activities. The aim of this study is to develop an online platform for farm produce marketing that enhances efficiency, accessibility, and transparency in agricultural transactions. The motivation that led to the implementation of the proposed system is that there is lack of direct access to profitable markets for smallholder farmers. Also, farm produce consumers face challenges in accessing fresh farm produce directly from farmers without relying heavily on intermediaries. The research identified major challenges in farm produce marketing, including poor access to market information reported by 30% of farmers, high dependence on middlemen (20%), and poor transportation and logistics (15%). The methodology adopted in this study is the object-oriented analysis and design methodology (OOADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The web programming languages (HTML, CSS, JAVASCRIPT, and PHP) was used in the software development process because, it is platform independent and it is a web-based application. The proposed farm produce marketing system will enhance agricultural commercialization by linking farmers directly with consumers and wholesalers. The expected result is an online platform for farm produce marketing that will establish training and support programs within the platform to improve digital literacy and encourage adoption among farmers.

This study addresses the inefficiencies of manual food ordering systems commonly used by Nigerian restaurants, such as order errors, delayed service, limited accessibility, and poor record management. The objective of the study was to design and implement a secure, efficient, and user-friendly web-based online food ordering system to automate the ordering and management process. An iterative Software Development Life Cycle (SDLC) methodology was adopted, encompassing system analysis, design, implementation, and testing, using modern web technologies including HTML5, CSS3, JavaScript, React.js, and Tailwind CSS. The developed system enables user authentication, menu browsing, cart management, order placement, and administrative control, and evaluation results demonstrated high functional accuracy, good usability, and reliable performance. However, the study is limited to a web-based prototype with sandbox payment integration and does not include live payment gateways, delivery tracking, mobile application support, or large-scale deployment, which are recommended for future enhancement

Every business organization, institution requires data and good quality information to function effectively. It is not an over statement to say many organizations, institutions have been having some challenges in passing information to the public rather it's has to be in a more efficient way. The objective of the study is to find a suitable solution to the major challenges the society face in peer-2-peer payment system in a cashless society regarding the issue of fraud and lack of trust and for the society to curb this problem the society has to adopt Escrow services, a third-party agent system that serves as a middleman. According to the research carried out in the course of this project, our statistical result collated from questionnaire distributed to various respondent shows that over 60% of the population doesn't know about Escrow services. However, for the society to adopt this system the government or private organization has to create an awareness and training program to educate the people about escrow services, how it's operate and the reason why they should adopt it, this will help the society at large when dealing with peer to peer payment system in a cashless economy. Thereby curbing the negative effect of fraud and issue of trust in the society.

This study develops a web-based map application to enhance navigation within the University of Benin campus, helping users locate buildings, offices, classrooms, and other points of interest. Using Next.js, TypeScript, TailwindCSS, and third-party mapping APIs like Google Maps, the application provides an interactive, mobile-friendly experience. Users can search for locations, get directions, and access regularly updated map data. This tool improves accessibility, saves time, and enhances user experience. By leveraging modern web technologies and geospatial data, the application fosters a more navigable and welcoming campus environment.

Phishing attacks, which use phoney emails and misleading websites to target people and organisations, have emerged as one of the most common cybersecurity threats. These attacks cause serious security breaches by tricking users into divulging private information, including login credentials and financial information. This project offers a machine learning-based phishing detection tool for emails and web browsers that uses logistic regression to efficiently detect and stop phishing threats. To improve the accuracy of phishing detection, the study investigates different feature extraction methods, dataset preprocessing, and model training approaches. Python was used to develop the system, and the Scikit-learn library was used to implement the model. Both authentic and phishing URLs and emails made up the dataset, which was preprocessed using techniques like feature scaling and outlier removal. Key performance metrics, such as accuracy, precision, recall, F1-score, and a confusion matrix, were used to train and assess the model. The outcomes showed that the suggested model was successful in differentiating between phishing and authentic entities, as evidenced by its high classification accuracy. Notwithstanding its encouraging results, the system has certain drawbacks, including the difficulty of balancing false positives and false negatives and vulnerability to new phishing tactics. To further enhance detection capabilities, future studies could use ensemble approaches or sophisticated deep learning models. By offering users and organisations a reliable and effective detection mechanism, this project supports the continuous efforts to strengthen cybersecurity defences against phishing attacks.

The rapid growth of online food delivery platforms has introduced challenges in supporting multiple restaurants on a single system. This research proposes a multi-tenant backend system for food delivery platforms, enabling each restaurant to operate independently while sharing the same backend infrastructure. The system ensures that tenants maintain full control over orders, menus, and operational data, eliminating the risk of conflicts or data overlap. Unlike traditional single-tenant or loosely structured multi-vendor systems, this implementation ensures strong tenant isolation by design which means each restaurant experiences the system as if it were built specifically for them. All operations including order processing, background jobs, inventory updates, and notifications are executed in a tenant-aware context. This work contributes a practical approach for anyone building a multi-vendor platform and not just in food delivery but also in areas where clean isolation, predictable behavior, and efficient resource sharing are required.

The supervision of undergraduate final year projects constitutes a critical component of higher education, as it directly influences the quality of the student's capstone experience. So far the traditional methods adopted, such as physical meetings, email chains, and paper-based tracking, have proven to be inadequate, resulting in communication gaps, missed deadlines, and inefficient progress tracking. This project emphasizes the need to adopt a centralized, mobile-first solution over fragmented tools like general-purpose chat apps or complex Learning Management Systems (LMS). Taking into consideration the specific constraints and context of the University of Benin, Department of Computer Science, the method proposed by this project is a Mobile-Based Project Supervision System. However, this project focuses on only the design and high-fidelity prototyping of this automated system, providing the "output on mobile" as a "demo model." The design details a system where students can view their progress on a dashboard, track submission statuses, receive feedback, and communicate directly with their supervisor. This project makes use of a User-Centered Design (UCD) and Object-Oriented approach to system analysis and design; use case, class, and state machine diagrams were used to represent designs for the system architecture. These designs serve as the framework for a system that can handle the whole process of project supervision, from initial tracking to final feedback.

This study presents the design and implementation of an AI-Based Career Guidance Chatbot developed to support Nigerian secondary school leavers in making informed academic and career decisions. Motivated by the growing complexity of career choices and the shortage of trained counsellors in Nigeria, the system uses artificial intelligence (AI) and natural language processing (NLP) to deliver personalized, real-time guidance through a conversational interface. Using Yamane’s formula, 67 respondents were selected, and data were gathered through structured questionnaires and analyzed with descriptive statistics. Results showed that most students owned smartphones (94%) and had reliable internet access (80%), indicating strong readiness for AI-driven solutions. Users expressed high satisfaction with the chatbot’s ease of use, responsiveness, and personalized recommendations, reflected in mean perception scores of 4.1–4.6 on a 5-point scale. The study also identified persistent challenges in traditional counselling, including limited counsellor availability, high studentto-counsellor ratios, and inconsistent information. These findings highlight the potential of AI systems to complement existing counselling services by providing accessible, consistent, and data-driven support. The study recommends integrating AI chatbots into school counselling programs, maintaining updated academic data, and enforcing strong data privacy practices. Overall, the system shows promise for improving decision-making, boosting student confidence, and promoting equitable access to quality career guidance in Nigeria.

This study investigates the susceptibility of students at the University of Benin (UNIBEN) to phishing attacks and examines how to promote sustainable, safe email usage within the academic environment. Employing a mixed-methods research design, the study collected quantitative data through structured surveys and qualitative insights from interviews, focus group discussions, and document analysis. The findings reveal that while students have a basic awareness of phishing, their understanding is superficial and they often rely on visual cues, which increases their vulnerability. Additionally, the current email security measures at UNIBEN—such as basic spam filters and password-based authentication—prove insufficient against sophisticated phishing tactics. The qualitative data further indicate that a lack of practical, hands-on cybersecurity training contributes significantly to the risk, with many students calling for interactive training and simulated phishing exercises. Based on these insights, the study concludes that enhancing both technical security measures and cybersecurity education is essential to reduce phishing susceptibility. Recommendations include implementing comprehensive, practical training programs, upgrading security protocols with multi-factor authentication, establishing formal incident reporting systems, and fostering a proactive cybersecurity culture. These steps are expected to strengthen the overall security of UNIBEN’s email system and promote a resilient academic environment.