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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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    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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    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

    Published 2009
    “…Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). The Decision Tree rules were developed manually based on Normalized Difference Vegetation Index (NDVI) and Brightness Value (BV) variables. …”
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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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    Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

    Published 2019
    “…The overall accuracy of counting existing oil palm trees using the approach developed in this study is 93.3% while missing trees detection gives the detection accuracy of 89.2%. …”
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    Thesis
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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

    Published 2020
    “…The results show that the decision tree through J48 algorithm has produced the easiest rule to be interpreted. …”
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