Browsing by Author "Islam, Rafi"

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A Machine Learning Approach to Detecting Suicidal Tendencies in Adolescents
(Daffodil International University, 2024-07-13) Islam, Rafi; Sweety, Sultana Akter
Nowadays suicide has become a serious crime. People commit suicide for many reasons. Due to the advancement of social media, people post various types of posts before committing suicide. Understanding the environmental risk factors that affect suicide thoughts and behavior throughout time will be greatly aided by this study. We will collect various types of data from various online platforms and identify them with the help of machine learning models. We use some algorithms to find out the best accuracy. To find out the best accurate results we implement classifier such as Naive Bayes, Support Vector Machine (SVM), Logistic Regression, Decision Tree Classification, Random Forest and Gradient Boosting Classifier. The models were evaluated based on their accuracy, precision, recall and F-1 score. Naive Bayes had the lowest accuracy at 73%, while Support Vector Machine (SVM) secured the top positions with 92.32% accuracy. This research highlights the importance of integrating advanced machine learning techniques into mental health care to facilitate early intervention and support for at-risk adolescents. By leveraging technology, we can enhance the effectiveness of suicide prevention strategies and ultimately save lives.
An Investigation Into Passenger Satisfaction And Its Role In Community And Economic Growth: A Study On West-Zone Rail Services In Bangladesh
(Daffodil International University, 2025-01-06) Khan, Sumon; Islam, Rafi; Bhuyain, Md. Shawon
Attraction and dependency between various linking regions have increased along with the rate of urbanization and economic growth. Since the beginning, transportation has played a vital role in advancing the development and economic benefits of connectingcommunities. The railway industry has demonstrated its ability to generate economic and developmental advantages for several nations. But compared to road transportation, less focus has been placed on improving the railway industry, primarily in Bangladesh, which has prevented the sector from reaping the full economic benefit. This study investigates passenger satisfaction with Bangladesh Railways, focusing on key factors such as journey time, punctuality and service quality. The objective is to identify the main barriers to passenger satisfaction and evaluate how addressing these issues can contribute to economic and community development. At Kamalapur and Parbatipur Railway Station, survey questionnaires were utilized to assess passenger satisfaction with various services. Passenger and locomotive master surveys were conducted to gain a comprehensive understanding of operational and service delivery challenges. The study employs factor analysis to identify the primary elements that influence passenger satisfaction. Surveys were conducted with both travelers and locomotive masters to gather insights. The results were based on their responses to questions designed to measure satisfaction across Nineteen key areas. The findings indicate that journey duration, punctuality, food quality and cost, ticket services, restroom cleanliness, staff behavior and scheduling sanitation are significant factors that explain 84.527% of the variance in passenger satisfaction with railway services. This research provides actionable recommendations for policymakers and railway authorities to prioritize passenger-centric strategies, ultimately fostering a more efficient and inclusive transportation system.