Search Results - (( using naive perceptions algorithm ) OR ( java implication based algorithm ))

Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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Sentiment analysis regarding childcare issues using Naive Bayes Algorithm / Alis Farhana Zulkipeli by Zulkipeli, Alis Farhana

“…This study applies the Naive Bayes algorithm for sentiment analysis to assess public perceptions of childcare issues, particularly child abandonment and accidents. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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Predicting Customer Behaviour on Buying Life Insurance using Machine Learning by Fabu Ayub A Ghafar, Norhana Abd Rahim, Yumn Suhaylah Yusoff

Twitter sentiment analysis of Malaysian fast food restaurant chains: a novel approach to understand customer perception using Naïve Bayes / Muhammad Hafeez Hakimi Muhd Zahidi Ridzu... by Muhd Zahidi Ridzuan, Muhammad Hafeez Hakimi, Abd Halim, hairul Nizam

“…It employs Naïve Bayes algorithm and Plotly library in Python to provide insights into customer perceptions, enhancing the fast food brand experience in Malaysia. …”
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Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data by Karmagatri, Mulyani, Aziz, Clarisa Fezia Amanda, Asih, Wini Rizki Purnama, Jumbri, Isma Addi

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Twitter sentiment analysis of Malaysian fast food restaurant chains: a novel approach to understand customer perception using Naïve Bayes / Muhammad Hafeez Hakimi Muhd Zahidi Ridzu... by Muhd Zahidi Ridzuan, Muhammad Hafeez Hakimi, Abd Halim, Khairul Nizam

“…It employs the Naïve Bayes algorithm and Plotly library in Python to provide insights into customer perceptions, enhancing the fast-food brand experience in Malaysia. …”
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Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

“…The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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Breast cancer prediction using machine learning by Serajee, Nasheed, Mannan, Saad, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Wani, Sharyar, Abubakar, Adamu, Olowolayemo, Akeem Koye

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Breast cancer prediction using machine learning by Seraje, Nasheed Hossain, Mannan, Saad, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Wani, Sharyar, Abubakar, Adamu, Olowolayemo, Akeem

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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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A literature review on text classification and sentiment analysis approaches by Wang Dawei, Rayner Alfred, Joe Henry Obit, Chin Kim On

“…In feature extraction, the IG, TF-IDF, Word2vec usually be used. Then, the SVM, Naive Bayes, KNN or Neural network algorithm usually be used in classifier. …”
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Cyber-Crime Detection: Experimental Techniques Comparison Analysis by Aljarboua E.F., Bte Md. Din M., Bakar A.A.

“…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. The key focus of the study is on the use of eight classifiers models which are Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Multiple layer perception (MLP). …”

Identifying and predicting Muslim’s community funeral funding protocols by Ibrahim, Izzul Ismail, M Ashhuri, Muhammad Hassan, Hassan, Raini

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

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

“…The classifiers were trained using logistic regression (LR), naïve Bayes (NB), support vector machine (SVM), and other approaches. …”
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