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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

“…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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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

“…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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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

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

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

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

“…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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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

“…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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Loss minimization in load flow simulation in power system by Mohamad Firdaus, Mat Hussin

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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

“…The machine learning algorithm is introduced to optimize the digital financial portfolio investment return prediction system. …”
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Hybrid BLEU Algorithm For Structured Exam Management System by Zulhana, Zulkifle

“…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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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

“…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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Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

“…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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Review of the machine learning methods in the classification of phishing attack by Jupin, John Arthur, Sutikno, Tole, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Deris, Stiawan

“…There are several algorithms that can be used in the machine learning method to prevent these attacks. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

“…PCA is employed for learning multistage filter banks. Binary hashing and block histograms are the steps for indexing and pooling. …”
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A comparative analysis of machine learning approaches in sukuk price estimation across global regions by Islam, Gazi Taufiq, Malakar, Surajit, Hassan, Khondekar Lutful, Dey, Rajesh, Mahajan, Rupali A, Kassim, Salina

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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

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

“…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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Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Dynamic android malware category classification using semi-supervised deep learning by Mahdavifar, Samaneh, Kadir, Andi Fitriah Abdul, Fatemi, Rasool, Alhadidi, Dima, Ghorbani, Ali A

“…We evaluate our proposed model on CICMalDroid2020 and conduct a comparison with Label Propagation (LP), a well-known semi-supervised machine learning technique, and other common machine learning algorithms. …”
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