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                <text>Internships are a crucial part of studies at IBU, yet there is not a centralised system for internship searching and daily report completion. To tackle this issue, a solution is a web application used to streamline the internship process, from finding an internship to filling out the daily report and finally receiving the final grade. It efficiently coordinates all actors involved in the internship process: intern, company representative, internship manager and administrator. &#13;
&#13;
The system is a full-stack application, leveraging technologies such as React.js for the client, Express.js on the server and MySQL as the relational database. It includes role-based authentication using Google’s OAuth2 strategy, form submissions and status tracking.&#13;
&#13;
The resulting system allows students to apply for internships and fill out daily reports. It further allows company representatives to create listings and choose interns, approve and reject daily reports and fill out final reports. The system further allows internship managers to enter final grades and the administrator to modify company records and choose the current internship manager.&#13;
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In the increasingly competitive higher education landscape, digital marketing plays a crucial role in attracting prospective students. However, institutions often face major challenges in tracking cross-channel performance and accurately attributing student applications to specific campaigns. Marketing platforms like Meta Ads and Google Ads often exaggerate campaign effectiveness by counting impressions, clicks, and superficial conversions that may not result in actual applications or enrollments. &#13;
This senior design project addresses that issue by developing a Business Intelligence Platform for PPC and Organic Marketing, aimed at providing real-time, actionable insights for the International Burch University (IBU) Marketing Team. The system enables end-to-end campaign tracking by integrating digital ad performance data with actual application data, using a unique medium URL parameter embedded in campaign links and captured during the application process to bridge external and internal data sources.&#13;
The platform uses Windsor.ai connectors to fetch ad data into Google Sheets, where a Google Apps Script automates data cleaning and merging. This data is combined with student application records from a MySQL database and visualized in real-time through Looker Studio dashboards.&#13;
Results demonstrate the system’s ability to provide clear, actionable insights, enabling the marketing team to compare channels, calculate cost per application, and evaluate the full applicant funnel across departments and academic cycles. In doing so, the platform empowers the team to optimize campaigns based on verified outcomes.&#13;
The project highlights the importance of reliable tracking infrastructure, disciplined use of URL parameters, and automation in marketing analytics. It represents a scalable, low-cost solution for improving data-driven decision-making in higher education marketing.&#13;
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                <text>The goal of this project is to provide tourists and visitors with a more efficient and personalized experience in the city of Sarajevo. The idea of GuideMeSarajevo is an easy-to-use and centralized platform, both for providers and users. The problem addressed is the lack of information provided to guests upon their arrival. Enabling visitors to choose their own preferences instead of predefining their whole stay is the main goal.&#13;
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Results show a useful platform that simplifies tourism and navigation in Sarajevo. Using interactive elements like maps and categorized utilities, the application increases user engagement. Enables providers to manage offerings quickly and attract more consumers to their businesses.&#13;
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                <text>Sentiment analysis could be a powerful tool in evolving psychotherapy. There is a rapid increase in patients seeking mental health help, and NLP could help make their experience more accessible and efficient. A sentiment analysis-based journal could help users track their thought patterns, their severity, and progress over time. This paper investigates the effectiveness of Naive Bayes, Random Forest, Support Vector Machine, XGBoost and BERT algorithms paired with TF-IDF, Bag of Words, One-Hot Encoding and Word2Vec feature extraction algorithms in emotion classification of text for future journal use. Comparative analysis helps understand which algorithms could be best suited for this type of multi-label classification, and broadens current research by testing several algorithms, which can show what should be further worked upon in the field, and which algorithms are best to avoid. Many studies test only one or two algorithms, leaving less room for comparison on the same dataset and under the same conditions, so it is unclear if the accuracy differences in different studies are derived from a better model or a better dataset. Furthermore, other studies do not provide a comparative analysis of feature extraction models. The four machine learning algorithms were trained on a dataset of 17.449 emotion-annotated sentences after preprocessing steps including tokenization, lemmatization, and vectorization for feature extraction. Out of classical models, Naive Bayes performed the worst with a 76% accuracy, and XGBoost performed the best with a 0.88 accuracy. Furthermore, BERT accomplished 93% accuracy, making it the best performing model in the study. Each algorithm performed better with a different vectorization method. This shows improvement over other research in the field, and the potential of sentiment analysis in aiding psychotherapy needs.</text>
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                <text>The objective of this project is to develop a booking platform, crafted for the needs of Bosnia and Herzegovina, that is designed to help its users to rent and book properties. Technologies that are used to make this platform are React.js for frontend side along with Node.js powered with Express framework on the backend side, while utilizing PostgreSQL for database. The problem addressed is the absence of a booking platform specialised and tailored for the needs of the country Bosnia and Herzegovina. A technique that can be used is the creation of a web application that provides its users with seamless and free access to a booking system. On this web application, users can search for properties to book, publish their own properties and make profit from it, save properties for future booking, and much more. The results include a fully functional web application with a simple UI and a great UX, that attracts foreign and local tourists to use the application. The conclusion drawn is that the proposed BnBosnia booking platform, effectively helps their users to book accommodation and rent their own accommodation, allowing them to make profit.</text>
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                <text>The TireShop project addresses the need for a modern, efficient online platform for buying and managing tire purchases. Customers often struggle with outdated websites, lack of product filtering options, and inefficient checkout processes. TireShop aims to solve these issues by offering a user-friendly experience with product listing, sorting, filtering, cart functionality, checkout, and personalized AI-based product recommendations. The project leverages a powerful technology stack, combining Angular for the frontend and .NET 8 for the backend, with MS SQL Server for data persistence. Key features include user authentication with password hashing, a fully functional shopping cart, admin dashboards for product management, and integration with SendGrid for real-time email notifications. Additionally, AI recommendations powered by Groq API enhance user experience by suggesting similar products. The result is a responsive, scalable, and secure e-commerce application tailored to the tire retail market.</text>
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                <text>Every day, a large number of media is shared on social media websites, as well as others sharing their opinions and sentiments on said posts. In this project, the main goal was to examine to what degree traditional machine learning algorithms can be used to classify and examine the sentiment of YouTube comments—are they positive, negative, or neutral? Because comments are generally brief, full of slang terms, emojis, and even misspellings on some occasions, this type of assignment can be difficult.&#13;
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Overall, the project helped demonstrate that with proper precautions in place, even some of the older machine learning algorithms can be effective at determining sentiment in random real-world text like YouTube comments. It also allowed for a better understanding of how important preprocessing really is when working with text data.&#13;
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                <text>Cinema management involves handling reservations, scheduling screenings, and maintaining effective communication with customers. This project presents a Cinema Management System designed to automate these processes, reducing administrative workload and enhancing user experience. The system streamlines reservations, sends automated notifications for confirmations and reminders, and provides an intuitive interface for both customers and administrators. Developed using Spring Boot [6] for the backend and React [7] for the frontend, the system ensures scalability and maintainability.&#13;
The development process followed a structured approach, starting with requirement analysis to identify challenges in manual cinema operations. The system was designed using a three-tier architecture, with a Spring Boot [6] backend handling authentication, reservations, and notifications, a React [7] frontend providing an intuitive interface, and a PostgreSQL [4] database for efficient data storage. Automated email and in-app notifications were integrated to keep users informed about their bookings.&#13;
The Cinema Management System successfully automates key aspects of cinema operations, reducing manual workload and improving user experience. Testing confirmed the platform's efficiency, user-friendliness, and scalability, with responsive performance across different devices. By integrating automation and a modern technology stack, the system significantly improves operational efficiency for cinemas.&#13;
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                <text>The Sunglasses E-commerce Webshop project addresses the need for a modern online platform to sell eyewear products, specifically sunglasses, to a wide customer base. &#13;
Problem Statement - Traditional brick-and-mortar sunglasses retailers are limited by geography and operating hours, whereas an e-commerce solution can provide 24/7 access and a broader reach. This project’s objective was to design and implement a secure, user-friendly web application for browsing and purchasing sunglasses online. &#13;
Methods - The development followed a structured approach including requirement analysis, system design with UML diagrams, iterative implementation, and rigorous testing. Key technologies used include Angular for the frontend, ASP.NET Core Web API for the backend, and MSSQL for data storage. The system integrates the Stripe API in sandbox mode to handle payments safely, avoiding actual charges during development. Modern development practices such as responsive design, RESTful APIs, and MVC architecture were employed to ensure scalability and maintainability. &#13;
Results - The resulting application allows users to register and log in, browse products with filtering options, add items to a shopping cart, and checkout securely using test credit card data. An administrative module enables product and order management. System testing indicates that all major use cases - from account creation to order placement - perform as expected, and the Stripe integration successfully simulates payment transactions without processing real money. Conclusion - The project demonstrates the successful creation of a specialized e-commerce platform for sunglasses. It offers a convenient shopping experience for users and an effective sales channel for the business. Future improvements, such as integrating augmented reality “virtual try-on” features and expanding product recommendations, are suggested to further enhance user engagement. Overall, the project showcases how a full-stack web application can meet real-world requirements for online retail, and it highlights lessons in web security, payment integration, and user experience design.</text>
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                <text>Many domestic hotels do not have a nice solution for the hotel reservation system. Some hotels do not have web applications at all, while others are purely designed and hard to use. This presents a huge problem and customers are not satisfied. In the twenty-first century almost everything is available online and if your business is not reachable you are likely losing out to your competitors. On the other hand, having a nice web application may only help you grow your business. &#13;
&#13;
The main intention of this application is to make room reservations simpler, less time-consuming and easier for managing.&#13;
&#13;
Hotel Reservation System is a web-based system that enables users all over the world to make room reservations. This system supports two types of users which are employees and guests. Guests should be able to quickly make a reservation request for a specified date and room. On the other hand, employees can easily interact with the database and fetch the details of the reservation request and customer that created it. Also, they can approve, reject and update reservation details. Functionalities of this application will help to keep track of the available rooms and the customers that are staying in the hotel. It is designed to be very intuitive, easy to use and navigate around, but under the hood it has some relatively complex logic. &#13;
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