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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. A secondary dataset that considered 635 households of Terengganu was used, and the following aspects were identified as important indicators of poverty: age, income, education, occupation, and health. …”
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Web-based marketing communication to develop brand image and brand equity of higher educational institutions: a structural equation modelling approach
Published 2019“…Higher education is not an exception. However, configuring the right mix in the age of social networking sites and various online displays and constantly changing algorithm in search engine optimization have become major challenges today. …”
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It’s that time of the month!: development of digital intervention for adolescent menstrual health education
Published 2025“…The platform integrates comprehensive, evidence-based educational content on menstrual health, hygiene, cycle irregularities, and emotional well-being, fostering menstrual literacy. …”
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ScholarsAid: a personalized scholarship web application based on web scraping/ Muhammad Nur Haqeem Sulaiman and Norhasliza Ahmad
Published 2023“…The application allows students to easily search and filter scholarships based on their specific needs or preferences, and utilizes a matching algorithm to provide the most relevant scholarship options. …”
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User-centric learning for multiple access selections
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Conclusion: The results obtained show that machine learning technology is efficient and relevant for predicting dental students’ performance based on their pre-admission results. Stakeholders can use the identified effective factors to improve education outcomes.…”
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Proceeding Paper -
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Artificial Intelligence (AI) to predict dental student academic performance based on pre university results
Published 2021“…The dataset input variables will include student’s gender, age during admission, scholarship, parents’ level of education, pre-university result, Professional Exams result, and final CGPA. …”
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Proceeding Paper -
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Academic Achievement Prediction Model Using Neural Networks
Published 2002“…The results also indicate that neural network has a potential to be used for education planning.…”
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Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023
Published 2026“…The XGBoost model demonstrated the highest discriminative ability, with a validation area under the receiver operating characteristic curve of 0.888, accuracy of 0.834, F1-score of 0.715, sensitivity of 0.577, and specificity of 0.979, surpassing the performance of the other algorithms evaluated. SHapley Additive exPlanations analysis revealed gender, poverty-to-income ratio, sleep duration, smoking status, educational levels, race, age, high cholesterol, hypertension, and insulin use as the most influential predictors. …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
Published 2019“…This method will make ease for the young researchers, educators and students to dive into the enormous real world social and biological network.…”
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StockMaster simulator / Nor Hamiza Mohd Noor ... [et al.]
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Book Section -
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Development Of The Readability Index Model For Young Adults With Reading Difficulties In Malay Language
Published 2019“…The motivation of this study is based on the fact that there are some young adults aged 18 years old and above who still cannot read properly and are having difficulties in reading and writing. …”
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Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam
Published 2023“…Towards being more prepared for retirement, pre-retirees are encouraged to move from heavily saving in current assets wealth category such as in fixed deposits (which has the highest predictive weightage on the tendency of thinking about retirement based on an ANN model with an accuracy rate of 65.80%) towards more savings in future income wealth category such as in Private Retirement Schemes (PRS). …”
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Thesis