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    Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

    Published 2011
    “…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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    Conference or Workshop Item
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    Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

    Published 2013
    “…This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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    Thesis
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    Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

    Published 2021
    “…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. …”
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    Article
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    A study of graduate on time (GOT) for Ph.D students using decision tree model by Chin, Wan Yung, Ch’ng, Chee Keong, Mohd Jamil, Jastini

    Published 2019
    “…Therefore, this study aims to classify the Ph.D students into the group of “GOT achiever” and “non-GOT achiever” by using decision tree models. Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
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    Article
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    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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    Student Project
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    C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education by Erlan, Darmawan

    Published 2018
    “…To find out the prediction retirement prospective students, this paper uses C.45 algorithm. The method can change the a very large fact into a decision tree that represents the rule. …”
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    Journal
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    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

    Published 2023
    “…The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. …”
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    Article
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    Decision tree optimization for sukuk rating prediction by Kartiwi, Mira, Gunawan, Teddy Surya, Arundina, Tika, Omar, Mohd. Azmi

    Published 2018
    “…The results indicate that the decision tree model with Gini index as the criterion performs significantly better than the model produced using decision tree algorithm.…”
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    Article
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    Prospects for basal stem rot disease based on soil apparent electrical conductivity in oil palm plantation by Mohd Husin, Ezrin

    Published 2020
    “…The soil series for both Jenderata and Seberang Perak was in the Jawa series with the age of nine years of the oil palm tree. Meanwhile, Kluang had Melaka soil series with the age of 25 years of the oil palm tree. …”
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    Thesis
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    Prediction of employee promotion using hybrid sampling method with machine learning architecture / Shahidan Shafie, Soek Peng Ooi and Khai Wah Khaw by Shafie, Shahidan, Soek, Peng Ooi, Khai, Wah Khaw

    Published 2023
    “…In conclusion, the top five rank feature importance methods with the Extra Classifier Tree model are region, department, previous year rating, KPIs met and above 80%, and award won. …”
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    Article
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    Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction by Jumin E., Zaini N., Ahmed A.N., Abdullah S., Ismail M., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…Different Machine Learning algorithms have been investigated, viz. Linear Regression, Neural Network and Boosted Decision Tree. …”
    Article