3 10 3494 https://omeka.ibu.edu.ba/files/original/0665ed1fb44ff350bd1d82a178683d15.pdf f47137cacfec9d2e2790acc8b232937d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Student Information System Author Author Faris Allouch Abstract A summary of the resource. This project presents the development of a Student Information System (SIS), a web-based application designed to improve and simplify the management of student-related data in educational institutions. The main problem addressed in this work is the inefficiency, inconsistency, and time consumption associated with traditional, paper-based methods of tracking student records, grades, and enrollment information. Such outdated processes often result in human error, data loss, and limited access to academic information for both students and faculty. The development of the Student Information System followed a step-by-step, practical approach. The project began with the design and implementation of the frontend using HTML, CSS, and JavaScript. The goal was to first create a functional and user-friendly interface for core pages such as login, dashboard, student list, course enrollment, and grade overview. Special attention was given to layout, usability, and responsiveness to ensure that the interface would meet the needs of different user roles. Once the frontend was in place, backend logic was implemented using PHP. This phase involved connecting the visual components to a MySQL database and enabling dynamic data handling. Each feature created in the frontend — such as forms for registration, login, and grade entry — was connected to PHP scripts that processed the data, performed validations, and communicated with the database. A relational database structure was created to support the application’s core entities: users, students, courses, and grades. SQL queries were used within PHP to retrieve, insert, update, and delete records, depending on the user’s actions. Session-based authentication was used to control access and ensure that each user could only interact with the system according to their assigned role (admin, professor, or student). The system was developed iteratively, starting with smaller components and gradually building up to more complex functionality. Each step was tested using sample data to verify that both the frontend and backend behaved as expected. This phased approach helped identify and fix issues early, while also making it easier to expand the system with additional features. The results of the project indicate that the proposed system significantly improves the accessibility and organization of student data, reduces the potential for errors, and simplifies administrative tasks. Faculty members can easily enter and update grades, while students have real-time access to their academic progress. The system provides a more transparent and efficient way of managing academic information, ultimately enhancing the communication between all parties involved. In conclusion, this Student Information System demonstrates how digital solutions can modernize and optimize traditional academic processes in an effective and scalable manner. Keywords Keywords. Student Information System, web application, php, academic management, student data, grade tracking, user roles. sdp web application https://omeka.ibu.edu.ba/files/original/401b23bacba31f81475f84599cd1b40d.pdf dec8fc753e1cab41462a8cafb8aed7cd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Radesso: Connecting Clients and Specialists Platform Author Author Andrei Baranov Abstract A summary of the resource. Radesso is a location-aware job-seeking platform that enables clients to publish on-site or online orders and allows workers to discover, filter, and apply to them with high geographic precision. The platform addresses the persistent struggle of finding a suitable specialist “for any life scenario” within a single environment by combining modern web UX with a rigorously engineered geospatial backend. The front end is built with React and Leaflet (Leaflet.draw over OpenStreetMap tiles), allowing workers to define one or more work areas by drawing circles, rectangles, and polygons. On the server, a NestJS, TypeORM, PostgreSQL/PostGIS stack normalizes incoming GeoJSON to SRID 4326 (WGS84) and consolidates all shapes into a canonical MultiPolygon with GiST indexing for efficient spatial queries [1]. Security is managed through a production-grade authentication subsystem, including OTP email verification, Google OAuth, and short-lived JWT access tokens (RS256/ES256) carrying a kid header mapped to a database Keystore and Signing Key tables. Refresh tokens are device-scoped, hashed, and rotated on use, while a public JWKS route exposes verification keys for third-party consumers. Role-scoped access is enforced via modular guards, with session-based authentication planned for first-party web sessions. The matching system blends relevance and fairness by combining distance containment, price fit, category/competency match, listing freshness, and Bayesian worker rating into a configurable score. The query builder pre-filters by geometry and competencies before ranking, targeting sub-500 ms feed latency under spatial indexing. A focused test suite with Jest unit tests validates token/key rotation, keystore lifecycle, query-builder filters, and geospatial utilities. Operational deployment is packaged for Dokploy (API, database, secrets) with optional Tailscale access, while OpenAPI/Swagger documentation ensures discoverability. Radesso contributes a cohesive blueprint—and a working core—for a localized job-seeking platform where workers proactively seek orders. The near-term roadmap includes reviews and appeals, enhanced admin moderation, and telemetry, positioning Radesso to evolve into a trusted, geospatially precise hub for local work. Keywords Keywords. Nest, PostgresQL, PostGIS, JWKS, React, Leaflet, job-seeking platform job-seeking platform sdp https://omeka.ibu.edu.ba/files/original/b18defd59fa1a22b6d0661be94120b81.pdf 093c25d7f5a0dba3e6e0e005eca2c452 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TRIP TICKET RESERVATION SYSTEM Author Author Rijad Ismailović Abstract A summary of the resource. More and more people refer to digital means when doing their day to day life, whether it be making haircut appointments, paying bills, or even shopping for groceries. Despite the fast pace of technology, elderly people seem to not be able to catch up and are left having to physically get errands done, when they are the ones that can benefit the most from doing chores digitally. That’s where Global comes in, an easy to use trip ticket reservation web-app with a simple and intuitive UI that everyone can understand. The platform's user-friendly design was created using React, powered by Vite.js, while the process going on behind the scenes were developed using Spring-boot and protected using Spring-security. The two sides communicate through RESTful API and the data is stored in a MySQL database. Key functionalities include searching for, filtering and booking tickets. When the trip is completed users can leave a review, and of course they cancel their reservation if they wish. Ultimately, this project showcases how digital tools can simplify everyday tasks, offering an accessible solution for trip reservation that has the potential to improve the travel experience for all age groups. Keywords Keywords. React, Spring-boot, user-friendly, accessibility reservation system sdp web application https://omeka.ibu.edu.ba/files/original/fab59f362453417fcd70601de9b6d64e.pdf 826eaf523d0cebc8ae5d1c1d51b7f619 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource MOJE ZDRAVLJE Author Author Eman Hrustemović Abstract A summary of the resource. The increasing need for digital transformation in healthcare has driven the development of modern web-based solutions that facilitate communication between patients and healthcare providers. This thesis presents the design and implementation of "Moje Zdravlje", a secure and user-friendly web application that enables patients to schedule medical appointments, view their health records, laboratory results, and prescriptions, while allowing doctors to manage patient data, diagnoses, and treatment plans. The problem addressed in this project is the lack of centralized, real-time access to personal medical information for patients, and inefficient manual processes in health institutions. To solve this, the application was developed using a modular architecture consisting of a frontend interface built with HTML, CSS, and JavaScript, and a backend implemented in PHP following the RESTful API principles. The backend is organized into DAO, service, and route layers, and communicates with a MySQL database. Advanced features include two-factor authentication (OTP via email or SMS), Google OAuth login, hCaptcha bot protection, and secure password checks using the HaveIBeenPwned API. Role-based access control (RBAC) was implemented to ensure that patients and doctors access only the data relevant to their role. The application also includes validation of phone numbers and email domains (TLD and MX records), and follows modern web security practices. The result is a responsive and secure web application that streamlines interaction between patients and healthcare providers, improves the organization of medical data, and enhances user experience. Testing has confirmed that the system performs reliably across different scenarios, and offers a foundation for potential integration with official e-health systems Keywords Keywords. health web application, patient management, PHP backend, REST API, OTP verification, role-based access control, medicine sdp web application https://omeka.ibu.edu.ba/files/original/2c428581cfdc05ce202f12b106dc91c7.pdf 3f925e4f252f924ce18cefc9645499ef Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Impact of Sentiment Analysis Models on Financial Market Predictions Author Author Hazrin Redžepi Abstract A summary of the resource. Financial markets are influenced not only by numerical indicators but also by public sentiment, which is often expressed through news, reports, and social media platforms. Traditional forecasting models typically rely on historical financial data, ignoring this important textual dimension. This research examines how sentiment analysis models can enhance the accuracy of financial market predictions. The research focuses on evaluating various classical machine learning algorithms for sentiment classification in financial texts. A publicly available dataset combining FIQA and Financial PhraseBank sources was used, containing over 5,800 labeled financial sentences. Data preprocessing steps included cleaning, tokenization, stopword removal, and lemmatization. Exploratory data analysis was conducted to understand sentiment distribution, text length patterns, and word frequencies. Sentiment labels were encoded numerically to serve as target variables in classification models. A range of traditional machine learning algorithms was implemented and assessed to explore their suitability for sentiment analysis in the financial domain. Evaluation metrics including accuracy, precision, recall, and F1-score were used to assess model performance. Preliminary results indicate that traditional machine learning models can effectively classify sentiment in financial texts, especially when supported by proper text preprocessing. Furthermore, integrating sentiment analysis with financial data shows potential for improving market forecasting accuracy. This work contributes to the growing field of financial data science by demonstrating the effectiveness of NLP-driven sentiment analysis and offering a framework for building predictive systems that combine textual and numerical financial indicators. Keywords Keywords. senior design project, sentiment analysis, machine learning, natural language processing, financial data science, stock market prediction, financial forecasting data science machine learning NLP sdp https://omeka.ibu.edu.ba/files/original/d4a06240ce96fab43f263cd22d42b9c0.pdf ca1d620b80bf88d267f654a1995666b1 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource NBA Players Comparison and Prediction Author Author Edin Duraković Abstract A summary of the resource. Basketball scouting and player evaluation have traditionally relied on subjective assessments by coaches, scouts, and analysts. With the advancement of data-driven decision-making, machine learning (ML) and natural language processing (NLP) provide new opportunities to quantify scouting reports and predict player performance in a structured way. This project aims to predict the statistical performance of college basketball players upon entering the NBA by integrating structured data (rookie-year statistics) with unstructured data (text-based scouting reports). The proposed system applies NLP techniques to extract features from scouting narratives, focusing on player strengths, weaknesses, and comparisons. These textual features are combined with quantitative performance metrics to develop predictive models for key statistical categories such as points, assists, rebounds, blocks, and steals. Clustering methods are further applied to group players with similar scouting profiles. Instead of labeling clusters as fixed archetypes, the approach emphasizes identifying the most comparable NBA players for each prospect. This similarity-based framework provides interpretability for scouting evaluations and a practical foundation for projecting performance. The predictive component then leverages historical outcomes of comparable players to generate forecasts for new prospects. The results demonstrate that clustering can organize players into meaningful groups based on textual analysis, while the predictive framework produces reasonable estimates of rookie-year performance. Together, these findings highlight the potential of integrating NLP and ML into scouting workflows to complement traditional evaluation methods, reduce bias, and enhance the accuracy of performance projections. Keywords Keywords. NBA scouting, player evaluation, natural language processing, clustering, prediction, machine learning https://omeka.ibu.edu.ba/files/original/405711553b574d8fdbc957a5deff9ac7.pdf 0c19e7ad5b81c69f372bca28387779a5 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource CINEMA TICKET BOOKING - QUIKYTIX Author Author Adnan Brkić Abstract A summary of the resource. In a world where leisure time is precious, finding a hassle-free way to book cinema tickets can often be a challenge, leading to inefficiency and inconvenience. To address this issue, we introduce Quiky Tix, a user-centric platform designed to streamline the cinema ticket booking experience. Quiky Tix leverages modern web technologies such as Next.js, React, and TypeScript for robust development and utilizes Prisma and PostgreSQL for database management. The application offers a comprehensive movie list with titles, descriptions, and trailers, empowering users to make informed decisions. Through an intuitive interface, users can easily select seats and personalize their cinema experience. The implementation of Quiky Tix results in a seamless and efficient ticket booking process. Users can register effortlessly, accessing features like storing tickets with scannable barcodes. Timely notifications keep users informed about purchases and upcoming releases, enhancing their overall experience. Quiky Tix redefines the cinema ticket booking landscape, providing a user-friendly solution to inefficiencies in traditional methods. By combining ease of use with modern technology, the application revolutionizes the way people enjoy movies. Through its streamlined approach, Quiky Tix ensures a seamless and enjoyable movie experience for all users. booking management system https://omeka.ibu.edu.ba/files/original/a466804a307f87da1bb51a73262bfb42.pdf 59ae545e6cbe6c4a7a18808ee06a14cf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource TOURISTBOT: AI-POWERED MULTILINGUAL TRAVEL COMPANION FOR SEAMLESS TRAVEL ASSISTANCE IN BOSNIA AND HERZEGOVINA Author Author Selma Đozić Abstract A summary of the resource. Tourists visiting Bosnia and Herzegovina often encounter language barriers and difficulties in accessing relevant travel information in real-time, hindering their overall travel experience. Existing solutions are either limited in multilingual support or fail to deliver seamless, contextually appropriate assistance. This project represents a practical solution, namely, a TouristBot, an AI-powered, multilingual virtual travel assistant, designed to enhance the travel experience for visitors of Bosnia and Herzegovina. The system employs Natural Language Processing (NLP), and trained models, to process the user queries in English, and uses Google Cloud’s Translation API for enabling multilingual support, thus returning the answer in the user's original language. The backend, built in Python, using Flask framework, follows three-layered architecture, thus firstly searching for the answer directly from the custom dataset, then using pretrained models for prediction if the threshold for the first layer is not achieved, and finally mBert model is being used for deep semantic understanding if the first two layers fail. Also the frontend is built in JS’s framework, React-Native, for cross-platform functionality. That modular development methodology ensures higher reliability of the TouristBot, and eliminates the problem of the single point of failure. Ultimately, the outcome is a fully functional cross-platform mobile app, which aims to contribute to the tourism industry by offering an innovative, user-friendly solution that bridges language gaps and streamlines the travel experience in Bosnia and Herzegovina. Keywords Keywords. Natural Language Processing (NLP), virtual travel assistant, multilingual chatbot, cross-platform app, pretrained models, tourism in Bosnia and Herzegovina chatbot NLP https://omeka.ibu.edu.ba/files/original/db9cd6c74851eb266934d449e0e18e06.pdf a0af5d2b4a29f065a9ebd035e72278e5 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource DEVELOPMENT OF A BUSINESS MANAGEMENT APPLICATION: DOCUBOOK Author Author Faris Selimović Abstract A summary of the resource. This paper presents the design, implementation, and validation of DocuBook, a web-based business management application developed to reduce the administrative burden on small and medium-sized enterprises (SMEs) in Bosnia and Herzegovina. The system addresses critical challenges related to regulatory compliance, document management, and financial record-keeping by replacing error-prone, paper-based processes with a structured and secure digital platform. Developed using the Django framework, DocuBook provides centralized management for outgoing (KIF) and incoming (KUF) invoices, protocol-registered documents, and daily cash flow (DP) entries. Its modular architecture ensures maintainability and supports future expansion. The application has been successfully deployed in a live business environment, where it has demonstrated effectiveness in reducing administrative overhead, minimizing human error, and streamlining compliance procedures. The project confirms that a tailored, lightweight solution can significantly modernize operations for local businesses without the complexity and cost of large-scale enterprise systems. Keywords Keywords. business management, regulatory compliance, documentation system, Django, digital transformation business management Django https://omeka.ibu.edu.ba/files/original/771867435fe045d85b4bbfd55e69edaf.pdf d080d8a24752c37de4cf039f0c0dd1aa Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IT Senior Design Projects Description An account of the resource The IT Senior Design Projects (SDPs) category showcases innovative and practical final-year capstone projects developed by undergraduate and graduate students in the field of Information Technology. These projects represent the culmination of students' academic and technical expertise, demonstrating their ability to solve real-world problems through software and hardware solutions. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource GITHUB PROFILE ANALYZER Author Author ALI MARAT Abstract A summary of the resource. The GitHub Profile Analyzer was developed to assess developers' technical abilities by looking into the structure and meaning of their public repositories. Rather than just focusing on basic metrics like stars or forks, this project uses a combination of semantic embeddings (CodeBERT), structural analysis (ASTMiner), and rule-based heuristics for a more thorough understanding of coding practices. The analyzer has gone through several updates: CRAv2 set the foundation with Random Forest classifiers, CRAv3 took a semantic-first approach, and CRAv4 introduced a mixed strategy that fuses rules, semantic pattern analysis, and weighted confidence scoring. There was also an experimental Smart Repository Classifier (SRC) that tried to combine rule-based and machine-learning techniques, plus a side project that looked into detecting design patterns using AST embeddings and Code Property Graphs. The system was trained on 122 repositories and tested on 47 others across seven different categories. The results were impressive: CRAv3 hit an overall accuracy of 26.4%, while CRAv4 shot up to 70%, with big improvements in web applications (+133%) and CLI tools (+45%). Even though Random Forest tests only maxed out at about 35% in some categories, CRAv4's hybrid method turned out to be both more accurate and easier to understand. Some key hurdles included the lack of comprehensive datasets, issues with ASTMiner's dependencies, and the author's initial unfamiliarity with machine learning. Tackling these challenges taught valuable lessons in building datasets, feature engineering, and evaluating model In summary, this project highlights the benefits of blending semantic, structural, and rule-based strategies to gauge developer skills. Looking ahead, plans involve expanding datasets, diving into deep learning for design pattern detection, and enhancing the analyzer into a more general code intelligence tool. Keywords Keywords. GitHub analysis, semantic embeddings, ASTMiner, CRAv, machine learning, rule-based classification, design pattern detection