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Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

“…Therefore, this study undertakes a spatial hazard assessment of the air quality index using particulate matter with a diameter of 10 μm or lesser (PM10) in Selangor, Malaysia, by developing four machine learning models: eXtreme Gradient Boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), and Naive Bayes (NB). …”
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Engine fault diagnosis using probabilistic neural network by Sheng, Zhu, Min, Keng Tan, Ka, Renee Yin Chin, Bih, Lii Chua, Xiaoxi, Hao, Tze, Kenneth Kin Teo

“…A benchmarked engine fault model is developed and simulated in Maltab. The proposed algorithm is designed to detect 9 common engine faults based on the information extracted from exhaust gas, such as hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO2) and dioxygen (O2). …”
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An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…The Support Vector Machine algorithm resulted in the highest F-measure (0.906), followed closely by Logistic Regression (0.903), Random Forest (0.891), Naïve Bayes (0.880), K-Nearest Neighbour (0.831) and lastly, Decision Tree (0.778). …”
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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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Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz by Abdul Aziz, Azzatul Husna

“…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language by Siti Mujilahwati, Siti Mujilahwati, M. Safar, Noor Zuraidin, Supriyanto, Catur

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Evolving fuzzy grammar for crime texts categorization by Mohd Sharef, Nurfadhlina, Martin, Trevor

“…However, the developed models typically provide low expressivity and lacking in human-understandable representation. …”
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Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer by Mas Ira Syafila, Mohd Hilmi Tan

“…In classification, four different ML algorithms: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested to classify healthy and infected oil palm samples. …”
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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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