Search Results - (( using allocation tree algorithm ) OR ( java application mining algorithm ))

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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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    Article
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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    Thesis
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    Shape assignment by genetic algorithm towards designing optimal areas by Md Badaruddin, Ismadi, Md Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mamat, Ali, Tengku Muda Mohamed, Mahmud

    Published 2010
    “…The proposed solution is vital for promoting an optimal planting area and eventually finds the optimal number of trees as the ultimate goal. Thus, the evolutionary algorithm by GA technique was performed to find the objective. …”
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    Enhancing a cluster-based TDMA MAC protocol for vehicle-to-vehicle communications / Abubakar Bello Tambawal by Abubakar Bello , Tambawal

    Published 2020
    “…A dynamic time slot allocation strategy using a binary tree algorithm has been proposed to prevent vehicles from the adjacent clusters to reserve the same time slot. …”
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    Thesis
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    Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization by Razali, Mohd Norhisham, Ibrahim, Norizuandi, Hanapi, Rozita, Mohd Zamri, Norfarahzila, Abdul Manaf, Syaifulnizam

    Published 2023
    “…Employee working productivity prediction is vital for effective resource allocation, increased productivity, and upholding a high-performance culture in organizations. …”
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    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

    Published 2025
    “…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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    Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz by Abdul Aziz, Azzatul Husna

    Published 2025
    “…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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    Thesis
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    Artificial Neural Network‑Based Prediction of Nipa Sugar Production in Sarawak, Malaysia by Muzamil, Ayoub, Ana Sakura, Zainal Abidin, Kasumawati, Lias, Imtiyaz Akbar, Najar, Rasli, Muslimen

    Published 2026
    “…The FFANN model incorporates key environmental variables, including temperature, humidity, wind speed, atmospheric pressure and sap yield, and is trained using the resilient backpropagation (RPROP+) algorithm. …”
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    Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

    Published 2023
    “…This study uses 3,067 responses which are then be coupled with a machine learning methodology (ranging from Naïve Bayesian, Generalised Linear Model, Logistic Regression, Artificial Neural Network, Decision Tree, Random Forest, and Gradient Boosted Trees) via RapidMiner Studio to expand the understanding of how categories of wealth and expenditures can affect retirement behaviour, given the increasingly important role of machine learning algorithms within the context of behavioural economics where it has been demonstrated to describe patterns and relationships in behavioural data better than standard statistical analysis. …”
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    Thesis