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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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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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Green building factor in machine learning based condominium price prediction by Masrom, S., Mohd, T., Rahman, A.S.A.

“…To predict a housing price, a robust approach is crucial, which can be effectively gained from the machine learning technique. As research on green building with machine learning techniques is rarely reported in the literature, this paper presents the fundamental design and the comparison results of three machine learning algorithms namely deep learning (DL), decision tree (DT), and random forest (RF). …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

“…The model development employs five machine learning algorithms namely decision tree, Naive Bayes, Neural network, Support Vector Machines, Nearest Neighbour. …”
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Implementation And Performance Analysis Of Machine Learning Models For Detecting Phishing Attacks On Websites by Liong, Kah Pong

“…With the scholarly review of techniques employed by phishing websites, it is decided that they can be identified by their URLs and their SSL certificate information. Then, a machine learning tool is selected to build machine learning models that use three different machine learning algorithms, which are Support Vector Machine, Random Forest, and XGBoost. …”
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Big data approach to sentiment analysis in machine learning-based microblogs: Perspectives of religious moderation public policy in Indonesia by Mhd., Furqan, Ahmad Fakhri, Ab Nasir

“…Sentiment analysis was conducted on three primary microblogs such as Twitter, Instagram and YouTube using six machine learning algorithms. These include Naïve Bayes, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Bagging Classifier, Random Forest, and Gradient Boosting Classifier. …”
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Exploring classification for sentiment analysis from halal based tweets by Setik, Roziyani, Raja Lope Ahmad, Raja Mohd Tariqi, Marjudi, Suziyanti

“…It usually assigns a polarity of “positive”, “negative” or “neutral”. It uses an algorithmic technique to capture people's thoughts, sentiments, and emotions by incorporating Natural Language Processing and Machine Learning technology. …”
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Impact of Computational Thinking and Computer Science (CTCS) Teaching Technique at Seleceted Schools in Sarawak : A Qualitative Analysis by Nor Iqbal, Mohd Sait, Noor'ain, Aini, Kartinah, Zen

“…This paper aimed to explore the impact of the implementation of CTCS in the teaching-learning process by obtaining descriptive information through interviews with selected teachers and students. …”
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EstiCal: food calorie image recognition mobile application by using feature descriptor technique / Muhammad Asyraf Suhaimi by Suhaimi, Muhammad Asyraf

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An investigation into influence factor of student programming grade using association rule mining by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy, Zaiyadi, Mohd Fairuz, Hibadullah, Cik Fazilah

“…This finding can be a guideline to the faculty to plan a teaching and learning program for new registered student.…”
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Developing students' mathematical thinking: how far have we came? by Md. Yunus, Aida Suraya

“…To provide support for learning school textbooks need to be greatly improved as the current contents, contexts and examples do not stimulate students' thinking. …”
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