http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/54 Tue, 21 Apr 2026 10:49:03 GMT 2026-04-21T10:49:03Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/16818 Economic Transformation through Mobile Payment Advancements and Innovative Solutions Abdilahi, Abdiqadir Muse A new age of economic revolution has begun with the development of mobile payment technologies, which have completely changed the way that financial transactions and commercial exchanges take place. The broad effects of new developments in mobile payments and creative solutions on economic systems are examined in this thesis. Due to their ease of use, quickness, and wide accessibility, mobile payments have upended established financial processes, promoting financial inclusion and boosting the economy in a variety of industries. Mobile payment systems now have much improved security, dependability, and user confidence because to the incorporation of the digital currency and artificial intelligence and biometric identification. These technology developments have lowered transaction costs and expedited financial transactions, which has increased consumer spending and supported the expansion of small and medium-sized businesses (SMEs). This thesis offers a thorough examination of the financial gains resulting from improvements in mobile payments. It looks at case examples from different parts of the world to show how new technologies are changing both local and global economy. Through their potential to facilitate smooth financial transactions and enhance market efficiency, mobile payments have emerged as a powerful force for economic growth and stability. The study emphasizes how important mobile payment networks are to promoting equitable economic development, improving financial stability, and enabling effective market dynamics. As these technologies develop further, maximizing their economic potential and tackling the issues of financial exclusion will depend heavily on how strategically they are used. Thesis Sun, 14 Jul 2024 00:00:00 GMT http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/16818 2024-07-14T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14556 Improved Explainable Educational Data Mining System for Enhancing Programming Skills Mohamud, Mohamed Abdulle Forecasting student academic performance benefits from the extremely effective method known as educational data mining (EDM), which also helps to find important links within educational data. Evaluating and improving students' programming competency has been the main emphasis of many recent studies. Still, there are chances for constant development in this field. In this work, we provide an improved and understandable Educational Data Mining (EDM) approach for spotting and improving students' programming capacity. This proposed EDM system seeks to investigate a very effective feature engineering approach, a suitable classification technique, and the use of Explainable Artificial Intelligence (XAI) tools for model explanation. We do ablation study to find the best feature engineering method. The categorizing process decides students' current programming state. Six basic Machine Learning (ML) algorithms—decision tree, Support Vector Machine, Random Forest (RF), artificial neural network, Naive Bayes Classifier, k-Nearest Neighbor, and Ensemble method—are the main subjects of this module. Many criteria—including accuracy, precision, recall, f1-score, ROC curve, McNamar test, and others—are used to assess the performance of these algorithms. The experimental results show that among the many models, the Random Forest (RF) and the Stacking-SRDA ensemble technique can classify the students with more accuracy than others. To improve the interpretability of the model, we have finally used XAI technologies like Eli5, SHAPASH, and Local Interpretable Model Agnostic Explanations Thesis Thu, 18 Jul 2024 00:00:00 GMT http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14556 2024-07-18T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14503 Analysis of Reusability of Used Clothes Using Machine Learning Algorithms Rubel, Md. Salauddin With $45 billion in apparel exports in 2022, Bangladesh is the second-ranked country in the world for apparel exports also the second largest producer of textile waste. The Bangladeshi apparel sector is expected to generate US$10.15 billion in revenue by 2023. Purchasing power of Bangladeshi people have increased and expenses on apparel product has also increased. The habit of repeating clothes that worn once has decreased which makes our wardrobe filled with lots of rarely used clothes and after a certain time we throw them as a wastage. Our study is aimed to develop a machine learning algorithm to predict clothing reusability. For our model we use clothing type, fabric type, usage duration, damage, distortion and color information of a used cloths. We use Classification algorithms for constructing our predictive model. We have applied five classification machine learning algorithm which are Decision Tree, Random Forest, Naïve Bayes, Logistic Regression and SVM. With the given information of a used cloth our model can predict the reusability option for it, the options are: resale, reuse and turn into jhoot product. By reselling a used cloths one can earn save some money and on the other hand people having less money can get a good product. Reusing clothing items means using to create a new apparel item or using in home craft. The last option of reusing is turning into jhoot products, cloths which have used more than their average life cycle are used in jhoot. This research achieved model accuracy between 79% to 85% on predicting reusability of different apparel items. Future study will explore new machine learning approaches with larger dataset and also enable a system that will be useful for textile industry to achieve sustainability in clothing wastage. Thesis Sun, 28 Jan 2024 00:00:00 GMT http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14503 2024-01-28T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14502 Forecasting and Comparison of Economic Indicators for The Universal Pension Scheme in Bangladesh Hasan, Md. Warid Article 15 of the Bangladeshi constitution requires the state to guarantee "the right to social security." From birth to death, the Universal Pension Scheme aims to provide social security for all of its citizens and ensure that no one is left behind. This universal pension scheme is expected to provide sustainable and well-structured social security to the population of Bangladesh especially the growing elderly population due to the increase in average life expectancy. Bangladeshi citizens of all classes and professions can participate in this pension scheme between the ages of 18 to 50 years as per the national identity card or conditionally by making a minimum contribution of 10 years. The government is announcing a total of six pension schemes, but for now, four have been launched, namely PROBASH, PROGOTI, SHUROKKHA and SAMATA. Currently 62% of our total population is working. Although the current average life expectancy is 72.3 years, there is a possibility of further increase in the future, the increase in the average life expectancy and the increase in the number of single households will increase the dependency ratio in the future, so it is necessary to build a sustainable social security structure. As much as this pension scheme will benefit the people of the country, it can also harm them terribly if the government does not implement this system in a proper way. So, we will discuss a system that will most likely verify the feasibility of our pension system, as well as how much it will be acceptable to people and the possible transparency of the pension scheme. We can highlight some studies that can give us a better idea of the past and future of our economy. Among these, past data visualisation is a very significant method for reviewing the past. And I think data forecasting is the most appropriate decision for the future. We will do a good comparison of our own economic data with the data of other countries so that we can better understand the feasibility of introducing our pension system. And we will use the forecasting model so that we can see the possibility of the future of the data. In this way, we can get an idea of how the future development of the country's economy can affect our pension system. Our studies will surely help the financial sector of the government and also give a clear and proper understanding of this pension scheme among the people of the country. Thesis Sun, 28 Jan 2024 00:00:00 GMT http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14502 2024-01-28T00:00:00Z