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Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

“…The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…SVM is a classification technique developed by Vapnik [1] but a practical difficulty of using SVM is the selection of parameters such as C and kernel parameter, � in Gaussian RBF kernel. …”

A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions by Syaripudin, Undang

“…Lecturer competency measurement is carried out by first checking employee status using the SVM algorithm with an accuracy value of 72.28%, then using a hybrid SVM and PSO algorithm with an accuracy value of 100%. …”
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm by Salim, Nur Saadah, Saad, Shahadan

“…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. The objective of this study is to develop an accurate and efficient model capable of recognizing the presence of children in cars based on sound data. …”
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Classification of heart disease with machine learning: a comparison of grid search, random search, and Bayesian Optimization by Andi, Tri, Ismail, Amelia Ritahani, Pranolo, Andri, Kusuma, Candra Juni Cahyo

“…The main contribution of this research is to provide practical guidance for machine learning practitioners on selecting optimization techniques that align with algorithm characteristics. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis by Bala, Yahaya Zakariyau, Samat, Pathiah Abdul, Sharif, Khaironi Yatim, Manshor, Noridayu

“…The nuanced examination of algorithmic efficacy provides practical insights for developers and practitioners navigating the challenges of cross-project defect prediction. …”
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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

“…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The SVM Classifier is used to find a cluster of tumors development in an MR slice, identify tumor cells, and assess the size of the tumor that appears to be present in order to diagnose brain tumors. …”
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Smart attendance system with Iot based face recognition using deep learning approach by Seah, You

“…Nowadays, technological developments propagate the practical utilisation of face recognition approach for a more efficient attendance management system. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

“…This thesis aimed to investigate and develop a novel parameterized architecture design for SENSE algorithm. …”
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Automated classification of celestial objects using machine learning by Muhamad Suwaid, Muhammad Aiman Haris, Ab Karim, Muhammad ‘Ilyas Amierrullah, Hassan, Raini, Abdul Aziz, Azni

“…The results add towards the development of astrophysics while simultaneously meeting Sustainable Development Goal 9 on fostering innovation through the need for infrastructure…”
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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…This research paper focuses on the development of a cardiovascular disease prediction system particularly a heart disease, by developing machine learning classifiers, for instance, Support Vector Machine (SVM), Decision Tree, and XGBoost Classifiers. …”
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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…This research paper focuses on the development of a cardiovascular disease prediction system particularly a heart disease, by developing machine learning classifiers, for instance, Support Vector Machine (SVM), Decision Tree, and XGBoost Classifiers. …”
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Appliance level stand-by burst forecast modelling using machine learning techniques by Mustafa, Abid

“…The electrical appliances and equipment are developed in a way that optimize the use of energy. …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

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Development of machine learning sentiment analyzer and quality classifier (MLSAQC) and its application in analysing hospital patient satisfaction from Facebook reviews in Malaysia by A Rahim, Afiq Izzudin

“…Conclusion: Using data acquired from FB reviews and machine learning algorithms, a pragmatic and practical strategy for eliciting patient perceptions of service quality and supplementing standard patient satisfaction surveys has been created. …”
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