Analyses of Methods for Prediction of Elections Using Software Systems

The primary objective of this research study is to review and analyze the published literature regarding the possibilities of forecasting and predicting the result of elections using software systems. The factors motivating research institutions and individuals to consider research impact on prediction of elections are manifold. Understanding the impact of different software tools, algorithms and social networking software applications on prediction of elections is a vital, and often overlooked, element of forecasting the election results. The literature review was conducted to examine methods and current software applications and practices as well as projects on election predictions. The review focused in particular on social media applications and different methods on accessing the opinion of the potential voters. The review draws on an international literature, although it is limited to English language publications. The findings identify the different methods used, the advantages and disadvantages of different approaches and the methods that are used currently and that have shown most effective results and recommendations are provided

Survey Analyses of The Specific Impacting Factors in Devising a Machine Learning Prediction model for The General Election Process in Kosovo

The focus of the research study was analyses of impacting factors and later to incorporate those insights into variables to be measured for devising a machine learning predictive model for prognosis and prediction of the general election turnout in Kosovo. We have developed a novel method for recognizing the main impacting factors in elections. Our method shows that finding out whether different ways of collecting different data of election voters can lead to much better prediction and understanding of the election process. In order to do that we needed to analyze the specific impacting factors in the election process in Kosovo are investigated during the study. The data has derived from an originally collected survey dataset that contains the impacting factors previously identified and assessed regarding the general parliamentary elections in Kosovo  has been realized. Insights and recommendation has been discussed and argumented

Computational Data Analysis - Classification

The research discusses Computational Data Analysis Classification, a short summary of the classification models (regression, classification and clustering), the particular focus is on classification. For a case study, for data analysis, it has been selected classification method. The comparisons were made by classifying and analyzing the processes from the datasets between algorithms: Naïve Bayes, Support Vector Machine (SVM), J48 Decision Tree, and KStar

Assessing the Impacting Factors in Prediction of Parliamentary Elections Turnout Using Heuristics and Devising MIP Algorithmic Model

The research focus is on identifying and assessing the impacting factors to be measured in order to realize prediction of parliamentary elections outcome using the (MIP) algorithmic model. We have developed a novel method for recognizing the main impacting factors in elections using the (MIP) algorithmic model. We have firstly used adaptive heuristics. In order to devise and asses the impacting factors we have devised most-important-problem (MIP) algorithmic model to predict the outcome of Kosovo parliamentary elections and grounded it on the TTB (take-the-best) strategy. An analysis of forecasting approach to elections and the performance metrics (variance) using the (MIP) algorithmic model has been used. provided are all the main variables we have measured. We have provided posterior binomial proportion. This method is very popular when modelling geopolitical situations with complex dynamics in the system. The data has derived from an originally collected survey dataset that contains the impacting factors previously identified and assessed regarding the parliamentary elections in Kosovo has been realized

Devising an Algorithm for Election Prediction Using Survey of Voters Opinions

The purpose of this research study is to analyze how we use voter polls to predict elections and to design an algorithm to predict elections. We propose a method of prediction based on learning algorithm to determine the political profile of a voter group by obtaining a linear hierarchy on the attributes that weights the number of instances that are more relevant. Our process starts with opinion survey collected directly from the target group of voter

Survey Analyses of The Specific Impacting Factors in Devising a Machine Learning Prediction model for The General Election Process in Kosovo

The focus of the research study was analyses of impacting factors and later to incorporate those insights into variables to be measured for devising a machine learning predictive model for prognosis and prediction of the general election turnout in Kosovo. We have developed a novel method for recognizing the main impacting factors in elections

Development of the application for cinema management with .net technology

The research discusses an internet platform dedicated to cinema management. The platform is built upon two key components: the user-facing part and the backend operations. The visual part, also known as the Frontend in the programming world, is developed using technologies such as HTML, CSS, and JavaScript, offering a simple and user-friendly interface. On the other hand, the server or backend where modifications and updates are made is built using ASP MVC Core and the C# programming language. For data management, SQL Server is used, which facilitates the staff\u27s work in storing and accessing cinema-related information. Overall, this system allows the administration to have complete control over all cinema functions. Responsibilities are divided among the main administrator, manager, and receptionist, making interaction with customers easier and more efficient. The platform primarily focuses on managing movie titles, screening rooms, movie schedules, reservations, ticket sales, and user management, providing a comprehensive solution for all these needs. This online interface offers easy and quick access for both staff and customers to obtain the desired information. Another important advantage is that it helps minimize errors that can occur during various processes while significantly reducing operational costs. This platform is designed to be accessible by all team members, from the super-administrator who configures all system parameters to the customers who want to watch a movie, making the cinema available online 24/7

Computational Data Analysis - Classification

The research discusses Computational Data Analysis Classification, a short summary of the classification models (regression, classification and clustering), the particular focus is on classification. For a case study, for data analysis, it has been selected classification method. The comparisons were made by classifying and analyzing the processes from the datasets between algorithms: Naïve Bayes, Support Vector Machine (SMO), J48 Decision Tree, and KStar

The Evolution of Computer Network Automation

The evolution of computer network automation represents a significant development that has had a profound impact on enhancing efficiency, advancing technology, and transforming the functioning of computer networks in the modern era. In this study, we have examined the history of computer networks and network automation and analyzed how technology has evolved from manual and direct approaches into an automated and innovative interface. This research identifies the challenges and opportunities brought about by computer network automation, including enhanced security, network efficiency, and flexibility. Furthermore, we will focus on network automation, identifying the key strategies and technologies that have been used to make networks more advanced and easier to manage. Our findings will demonstrate that computer network automation is a pivotal evolution that has influenced various aspects of computer networking, including the development of advanced infrastructure, rapid and accurate decision-making, and overall network security. These changes hold particular significance in today\u27s world of information and communication technology, where computer networks serve as the foundation for ensuring the efficient and secure transmission and utilization of information. Finally, we will examine the advantages and challenges of computer network automation and their impact on information security and business efficiency. In conclusion, this study will provide a comprehensive overview of the development of network automation and offer suggestions and recommendations for the future of computer networking

Application of Machine Learning in Software Engineering

The purpose of the software manufacturing industry is to produce high-quality applications that meet the requirements of customers and users who live long, that are easy to use and have as few errors as possible. Building such an ideal software is a relatively difficult process. To be successful in this industry, a specific discipline is needed when designing and developing software. There is therefore an engineering perspective on the whole process. Many companies and individuals still develop software chaotic, based on a poor analysis, which leads to unsuccessful outcomes such as software failures that fail to meet the expected requirements. Software Engineering applies to optimize these phenomena