DEPARTMENT OF COMPUTER SCIENCE

The absence of a structured and secure channel for student expression at the University of Benin (UNIBEN) has left many important issues overlooked or unheard. Existing options, such as social media platforms, are often unsafe, unorganized, and unable to provide anonymity or encourage honest expression without fear of judgment or ridicule. This project (Design and Implementation of UNIBEN Students Engagement/Expression Platform) seeks to address these challenges by creating a dedicated, moderated, and student-centered platform that empowers the UNIBEN community to share experiences and highlight everyday student concerns. The platform will be designed and developed using Figma, WordPress, and other essential web tools to ensure a responsive, user-friendly, and scalable interface. Core features will include anonymous story submissions, categorized topics such as academics, housing, finance, and safety, as well as interaction options like comments and feedback under strict moderation. Security and visibility will remain top priorities through features such as anti-bot protection, content approval workflows, and privacy safeguards that encourage open participation. By providing a safe and structured space for expression, the project not only amplifies underrepresented student voices but also sets the foundation for future growth, including AI-driven content moderation, story highlights, and also more development for broader accessibility.

Sharenting, the practice of parents sharing their children's images, videos, and personal information online, has become an integral aspect of digital parenting in the social media age. This study explores sharenting behaviours among Christian parents, focusing on how their faith, privacy concerns and social influences shape their decisions to share their children's lives online. The rapid expansion of social media has made sharenting a common practice, yet concerns regarding child privacy, digital footprints and ethical considerations remain relevant. This research aimed to understand the extent to which Christian values influence sharenting practices, the motivations behind parents' sharing decisions, and the perceived risks and benefits associated with online sharing. The study employed descriptive statistics, including frequencies, percentages, means, and standard deviations, to analyse responses from Christian parents at Foursquare Gospel Church. The findings indicate that older parents are more privacy-conscious than younger parents. Strong religious commitment was linked to less frequent sharenting, emphasizing values like modesty, discretion, and stewardship. However, many parents acknowledged the benefits of online sharing, such as strengthening family bonds and fostering Christian community ties. Despite this, privacy concerns and potential risks, such as cybersecurity threats and loss of child autonomy, influenced their decisions. The study concludes that Christian parents navigate a balance between faith, social connection, and digital responsibility. It recommends faith-based digital literacy programs to help parents make ethical, informed decisions about sharenting.

The rapid growth of digital technology and e-commerce has transformed the way goods and services are exchanged, creating new opportunities for businesses and consumers. Despite these advancements, many small businesses within the University of Benin (UNIBEN) community still rely on traditional advertising methods such as word-of-mouth referrals and printed flyers, which limit their visibility and growth potential. The absence of a centralized platform also makes it difficult for students, staff, and faculty to easily discover and access available services within the university environment.

This project proposes the development of an online marketplace specifically designed for the University of Benin community. The platform aims to provide a digital space where small business owners can showcase their products and services, while enabling users to conveniently search, compare, and engage with service providers. The proposed system integrates features such as business listings, service categorization, customer reviews and ratings, communication tools, and performance analytics to improve user experience and business management.

The online marketplace is expected to enhance the visibility of campus-based businesses, increase customer engagement, and promote economic activities within the university community. Furthermore, it will provide a structured and accessible platform that connects buyers and sellers efficiently, fostering convenience, transparency, and trust. The study concludes that implementing a dedicated online marketplace for UNIBEN can significantly contribute to the digital transformation of campus commerce and support the growth and sustainability of small businesses within the institution.

This research addresses critical challenges in Nigerian e-commerce through the development of a web-based Competitive Analysis System (CAS). The system tackles persistent issues of product authenticity verification, inaccurate descriptions, and limited competitive intelligence that undermine consumer trust and vendor competitiveness. Built on a Django REST Framework and React.js architecture with MySQL database management, the system integrates computer vision technology using Convolutional Neural Networks and FAISS similarity search, achieving 97% accuracy in product image verification. Natural Language Processing pipelines validate description accuracy against visual content, while automated web scraping modules provide real-time competitor intelligence across major e-commerce platforms. The research successfully delivered a fully functional platform that enables multi-vendor product comparison, automated verification, and competitive analysis. The system's theoretical framework combines Technology Acceptance Model with trust theory, specifically addressing the unique socio-technical challenges of emerging e-commerce markets. Practical implementation provides SMEs with accessible competitive intelligence tools while establishing new standards for transparency in digital commerce. The CAS platform demonstrates that integrating artificial intelligence and real-time analytics can effectively address core e-commerce challenges in developing economies, offering a scalable solution for enhancing market transparency and consumer confidence through verified product listings and data-driven vendor insights.

The rapid digital transformation across global industries has intensified the demand for modern technical skills, exposing significant skill gaps within African labour markets. Traditional labour forecasting methods, which rely on surveys and static reports, struggle to capture evolving workforce trends and often fail to provide timely, data-driven insights. This limitation motivates the adoption of machine learning-based analytical models capable of identifying emerging skill patterns from historical job market data. This study aims to develop and evaluate a predictive system for forecasting skill demand using structured datasets collected from African job portals. Specifically, the research applies Linear Regression as the core forecasting model to estimate future demand trends for key digital skills. The methodology involves a complete data preprocessing pipeline consisting of cleaning, normalization, and restructuring job-skill frequency data into model-readable formats. A curated dataset covering multiple skills across four years was used, and the system was implemented using Python and Streamlit for interactive visualization. Model performance was assessed using accuracy, trend-direction consistency, and graphical evaluation metrics derived from observed versus predicted values. Results show that the Linear Regression model accurately captured general growth patterns for high-demand digital skills such as Python and Data Analysis, achieving strong alignment between historical trajectories and forecasted values. The deployed system demonstrated stability, fast response time, and ease of use, enabling real-time skill trend visualization and one-step-ahead forecasting. The study confirms the potential of machine learning approaches for supporting labour market analysis in Africa. However, limitations include restricted dataset size, reliance on numerical trend features, and absence of deep learning models such as LSTM, which may better capture complex temporal dependencies. Future research should incorporate larger datasets, integrate natural language processing for extracting skills from job descriptions, and extend the forecasting engine to more advanced time-series models for improved prediction accuracy and adaptability.

The Ugbowo-Ekenwan residential rental market is recognized for its severe fragmentation, lack of transparency, and an exposure to fraudulent activities. Renters frequently grapple with a disconnected, inefficient search process, encountering outdated property listings and a risk of scams. This project directly addresses this critical issue by focusing on the trust deficit and the absence of a reliable, centralized platform that can guarantee the authenticity of both the property and the landlord, which is the key gap in the current ecosystem. To overcome these challenges, this project proposes and develops a comprehensive, web-based platform dedicated to apartment search and rental management. It is designed to establish a single, trusted source for property listings by directly connecting verified landlords with prospective renters. The solution centralizes the rental process, providing a transparent alternative that minimizes the reliance on untrusted intermediaries and directly attacks the root cause of rental fraud. The platform was developed using a mixed-methods approach. This involved a detailed user requirements analysis to understand market gaps. Key technical features include an interactive Map-Based Search Interface for hyper-local filtering, a secure user and listing verification system managed by an Admin Portal, and a direct communication channel to ensure zero agent interference. This robust development process ensures the platform is not only functional but resilient to typical market risks. The successful implementation of the prototype demonstrates its ability to streamline the apartment search. The platform's core Trust System, which tracks property verification status from landlord submission through Admin inspection, verifying the listing's authenticity. In conclusion, the web-based apartment search platform provides a more efficient, transparent, and significantly more secure alternative to traditional rental processes, paving the way for a more reliable and trustworthy real estate ecosystem.

This study investigates the impact of digital technology in teaching and learning computer science in secondary school. The study adopted the survey design on the basis of which data was sourced using questionnaire on a sample of 250 students in Benin Metropolis. The data was analysed using chi-square statistical tool. The result revealed that there is significant difference in the computer science teachers’ attitude towards the use of technology Tools. Secondly, the result shows that there is significant difference in the computer science students’ attitude towards the use of Technology Tools in learning. Similarly, the result indicated that there is no significant difference of self-efficacy in the use of Technology Tools in teaching of computer science. The result also shows that there is significant difference of self-efficacy in the use of Technology Tools in learning of computer science. The study recommends that since Technology Tools depends on power supply, the entire erratic power supply needs to be improved upon throughout the country. Also, school authority should improvise for alternative source of power supply such as generator set in case of power failure. More time should be allocated to the teaching of computer science on the time-table in our secondary schools so that there will be enough time for the teaching of computer science. Also, computer science teachers should not be too overwhelmed with too many assignments so that they will have time to plan technology enhanced classes. Teachers must be aware that for meaningful learning to take place, teacher- student interaction is an essential factor that must be strictly considered. It is therefore admonished that when integrating Technology Tools in computer science teaching, teachers should interact with the students while computer science teaching is going on.

Online Food Ordering System is database program that keeps record of all transaction carried out in the restaurant on daily bases. The aim of the study is to design and implement an Online Food Ordering System. In achieving this aim, the following objectives were laid out to determine how computerized management information system has facilitated increase productivity, decrease paperwork, and ability to analyze trouble spots. The motivation that led to the implementation of the proposed system is that the use of manual method in keeping information in the system. So among the numerous problems associated with the existing system are; staff are spending far too much time chasing mistakes instead of tending to customers, sales going unrecorded, inventory doesn’t match your tallies and other. 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 programming language used is HTML, CSS, JAVASCRIPT, PHP, SQL and JQUERY. The reason why web programming languages was used is because, it is platform independent and it is a web based application. This study is significance because its conclusions would be useful to: Human Resources Managers in the hotel and restaurants business, the Federal, State and Local Government, scholars in the field of hotel and restaurant management. The expected result is an Online Food Ordering System that will focus on food ordering, food menu, and payment on food delivery.

In most educational institutions, the process of taking student attendance is often done manually, which makes it time-consuming, error-prone, and susceptible to manipulation. This project focuses on the design and implementation of a web-based attendance management system that uses QR (Quick Response) codes to automate the attendance process. The system enables lecturers to generate a unique, time-limited QR code for each class session, while students scan the code through a web interface to mark their attendance. The backend is built using Node.js and Express.js, with a local JSON file (data.json) serving as the data storage layer using the Node.js fs module. The frontend utilizes HTML, CSS, and JavaScript for interaction and visualization. The system’s design emphasizes simplicity, real-time verification, and accessibility through any modern browser. Testing showed that the system minimizes human error, improves accuracy, and enhances the efficiency of attendance record management. The developed prototype provides a practical, secure, and user-friendly solution for both lecturers and students.

The increasing demand for secure, transparent, and efficient electoral processes has led to the adoption of online voting systems in universities. This project presents a PHP-based online voting system designed to provide a secure, user-friendly, and tamper-proof election platform for universities. The system enables student authentication, candidate registration, real-time vote
tallying, and automatic result generation after a set period. Security measures such as one-time voting enforcement and database encryption ensure election integrity. By leveraging web technologies, this system enhances electoral accessibility while minimizing fraud and administrative overhead, offering a scalable solution for university elections.