Search Results - (( developing teaching mining algorithm ) OR ( java application stemming algorithm ))

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  1. 1

    E4ML: Alat untuk pembelajaran perlombongan data by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2004
    “…However, most of the tool is complicated to be used by the beginner user especially to student.The absence of specific and easy tool was made the student unable to understand the use and applications in this field.This paper discusses the development of the teaching aid tool (software) that consist of several machine learning algorithms for the purpose of explaining data mining processes.With this tool, teaching and learning for such course can be enhanced in order to provide better understanding in data mining and machine learning.…”
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  2. 2

    Modeling Teacher's Integrity Using Data Mining by Mohd Latifi, Abdul Ghani

    Published 2010
    “…Thus, the aim of this study is to develop a model for teacher's integrity using data mining technique. …”
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  3. 3

    Predicting STEM academic performance in secondary schools: data mining approach by Termedi @Termiji, Mohammad Izzuan, Ab. Jalil, Habibah

    Published 2019
    “…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
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  4. 4

    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

    Published 2013
    “…In this study, sentiment classifier using clonal algorithm selection was developed to categorize sentiment in Malay newspaper (Berita Harian). …”
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    An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

    Published 2024
    “…For that, this study will perform a study of the current issues, factors, and solutions in education student’s data, determine the supervised machine learning algorithms, compare which model is the best predict the students’ performances, develop an early warning system for the educators to make an early decision in order to assist and consult the at-risk students, and finally conduct testing and evaluation of the system. …”
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