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  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  2. 2

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  3. 3

    Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.] by Hui, Shan Hon, Khai, Wah Khaw, XinYing, Chew, Wai, Peng Wong

    Published 2023
    “…Customer churn is defined as the tendency of customers to cease doing business with a company in a given period. ABC Multistate Bank faces the challenges to hold clients. The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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    Article
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    The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework by Normi Sham Awang, Abu Bakar, Norzariyah, Yahya, Norbik Bashah, Idris, Engku Rabiah Adawiah, Engku Ali, Jasni, Mohamad Zain, Erni Eliana, Khairuddin, Ahmad Firdaus, Zainal Abidin, Murtaj, Sheikh Mohammad Tahsin, Siti Sarah, Maidin

    Published 2024
    “…The overall CentralBank Digital Currency Project Index (CBDCPI) was selected as a target variable,while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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    Article
  6. 6

    The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework by Awang Abu Bakar, Normi Sham, Yahya, Norzariyah, Idris, Norbik Bashah, Engku Ali, Engku Rabiah Adawiah, Mohamad Zain, Jasni, Khairuddin, Erni Eliana, Zainal Abidin, Ahmad Firdaus, Murtaj, Sheikh Mohammad Tahsin, Maidin, Siti Sarah

    Published 2024
    “…The overall Central Bank Digital Currency Project Index (CBDCPI) was selected as a target variable, while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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    Article
  7. 7

    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…This research explores the application of unsupervised learning, a subset of Artificial Intelligence (AI), to analyze customer behavior in accepting personal loans within the banking sector. …”
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    Article
  8. 8

    Evaluating Machine Learning Algorithms for Fake Currency Detection by Keerthana, S.N, Chitra, K.

    Published 2024
    “…In this study, we evaluate the effectiveness of six supervised machine learning algorithms—K-Nearest Neighbor, Decision Trees, Support Vector Machine, Random Forests, Logistic Regression, and Naive Bayes—in detecting the authenticity of banknotes. …”
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  9. 9

    Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network by Francis, Adam

    Published 2005
    “…The third objective is to perform Vertical Splitting Algorithm technique for digit segmentation. And lastly, to develop an Artificial Neural Network for digit recognition. …”
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    Student Project
  10. 10

    Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023 by Soomro, Anam, Zakariyah, Habeebullah, Aftab, S.M.A., Muflehi, Mohamad, Shah, Asadullah, Meraj, Syeda

    Published 2024
    “…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. It critically examines the transition from traditional statistical models to advanced ML techniques in assessing credit risk, with a focus on the banking sector's need for reliable default prediction methods. …”
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    Article
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    Machine learning based return prediction for digital financial portfolios by LinXi Shi, Thien Sang Lim, Jin Yan, Pengcheng Qi, Tao Li

    Published 2025
    “…The machine learning algorithm is introduced to optimize the digital financial portfolio investment return prediction system. …”
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    Article
  13. 13

    Hybrid BLEU Algorithm For Structured Exam Management System by Zulhana, Zulkifle

    Published 2008
    “…Due to this problem, "Hybrid BLEU algorithm for Structured Exam Management System " is develop to aid the lecturers during assessment in the construction of quiz and test. …”
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  14. 14

    Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE by Abbas Alhadeethy, Najwa Fadhil, Khedher, Akram M Z M, Shah, Asadullah

    Published 2012
    “…The use of this learning technique has been increased in various domains such as e-commerce, banking and finance, as well as for speech and feature recognition to learn and classify intricate information. …”
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    Article
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    Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

    Published 2025
    “…To solve money laundering, more effective techniques for detecting suspicious transactions must be developed. Machine learning is able to learn complex relationships within large datasets then identify anomalies that deviate from well-defined patterns. …”
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    Final Year Project / Dissertation / Thesis
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    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…PCA is employed for learning multistage filter banks. Binary hashing and block histograms are the steps for indexing and pooling. …”
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    Monograph
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    Indonesian Stock Price Prediction Using Neural Basis Expansion Analysis for Interpretable Time Series Method by Zein, Muhamad Harun, Yudistira, Novanto, Adikara, Putra Pandu

    Published 2024
    “…New state-of-the-art deep learning architectures for time series forecasting are being developed yearly, making them more accurate than ever. …”
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  20. 20

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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    Thesis