Search Results - (( risk classification based algorithm ) OR ( java application optimisation algorithm ))

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  1. 1

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

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Article
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    Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

    Published 2006
    “…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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    Conference or Workshop Item
  3. 3

    Early diabetes risk prediction using Ant Colony Optimization algorithm / Nur Aisyatul Husna Ahmad Yusri and Rizauddin Saian by Ahmad Yusri, Nur Aisyatul Husna, Saian, Rizauddin

    Published 2023
    “…Therefore, this study has developed a classification model for predicting early diabetes risk using an Ant Colony Optimization (ACO) algorithm. …”
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    Book Section
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    Risk management credit scoring prediction using sentiment analysis by Chew, Chun Phang

    Published 2024
    “…In changing dynamic financial risk management, this project seeks to advance credit scoring predictions through the sentiment analysis into the data science framework, with a specific focus on Natural Language Processing (NLP) and classification algorithms. …”
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    Final Year Project / Dissertation / Thesis
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    Analysis and comparison of classification algorithms for credit approval in Islamic banks by Pebrianti, Dwi, Wijanarko, Whena, Bayuaji, Luhur, Toha, Siti Fauziah

    Published 2025
    “…This study evaluates the performance of various classification algorithms, including C4.5, Random Forest, Decision Tree, K-Nearest Neighbors, and Naïve Bayes, in predicting credit approval decisions based on factors such as character, capacity, capital, collateral, and economic conditions. …”
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    Article
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    Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

    Published 2025
    “…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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    Student Project
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    An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

    Published 2018
    “…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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    Thesis
  12. 12

    Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan by Shahron Nizan, Muhammad Shahmi

    Published 2023
    “…This project aims to develop a web-based application utilizing the Random Forest Classification Algorithm to aid concerned parents in detecting potential Autism Spectrum Disorder (ASD) symptoms in their children aged 1-6 years in Malaysia. …”
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    Thesis
  13. 13

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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    Thesis
  14. 14

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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    Article
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    Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

    Published 2024
    “…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. …”
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    Conference or Workshop Item
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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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    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Thesis
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    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…An automatic and accurate system for detection DR signs can significantly help ophthalmologists to make best decision for early treatment thus reducing risk of vision loss. In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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    Thesis