Search Results - (( develop smes using algorithm ) OR ( java implication based algorithm ))
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Aligning Malaysian SMEs with the megatrends: the roles of HPWPs and employee creativity in enhancing Malaysian SME performance
Published 2018“…The partial least squares algorithm and the bootstrapping technique were used for data analysis. …”
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Article -
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Strategic capabilities, innovation strategy and the performance of food and beverage small and medium enterprises
Published 2019“…Algorithm and bootstrapping techniques of Partial Least Squared Structural Equation Model (Smart PLS-3.0) was used to test the developed hypotheses of the study. …”
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Thesis -
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Effect of business social responsibility (BSR) on performance of SMEs in Nigeria
Published 2014“…This study used purposive sampling for sample selection. Partial Least Squares (PLS) algorithm and bootstrap techniques were used to test the study‘s hypotheses. …”
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Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization
Published 2025“…The application was implemented using React Native for mobile development and Firebase Firestore as the backend database to enable real-time data synchronization, while a binary tree bin packing algorithm was applied to generate efficient cargo loading arrangements. …”
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Final Year Project / Dissertation / Thesis -
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Predicting credit risk of the small medium enterprises using modified KMV model / Shakila Saad
Published 2022“…Hence, this study tried to predict the credit risk of SMEs in Malaysia by developing a credit scoring that combined financial and non-financial criteria. …”
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Thesis -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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Thesis -
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