Blockchain, Metaverse & NFT are technologies that were booming during the Pandemic. As a derivative product of blockchain, the Non-Fungible Token (NFT) is one of the technologies that has attracted the most intere...
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The exponential growth of data is compelling organizations to employ data in decision-making. As one of the businesses with an ecosystem that contributes to data growth, banks have challenges in generating insight. A ...
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The problems that exist in the field of art and culture preservation experienced by the arts and culture community side are the limitations on physical facilities for disseminating works, exchanging information betwee...
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The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG e...
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A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect ...
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The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Soc...
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The rise of blockchain technology and smart contracts has brought widespread attention due to their capacity to transform multiple industrial sectors through decentralized, transparent, secure transactions. However, d...
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When processing datasets in diabetes classification, common problems included a large number of missing values, outliers, and dataset imbalance. To deal with those issues, this study analyzed 18 studies on diabetes cl...
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When processing datasets in diabetes classification, common problems included a large number of missing values, outliers, and dataset imbalance. To deal with those issues, this study analyzed 18 studies on diabetes classification with machine learning algorithms over the past 5 years. This revealed the important role of data pre-processing in creating effective classification models, as it was found that by using different data pre-processing techniques, the same model can provide different performance. The study identified K-Nearest Neighbor (KNN) and support vector machine (SVM) as superior methods for filling in missing values, achieving an accuracy of 98.49% and 94.89%, respectively. These approaches outperformed traditional methods such as median or mean replacement. However, the challenge of imbalanced data sets remains in all studies reviewed. The common evaluation metrics used to evaluate the created models in previous studies included accuracy, precision, specificity, sensitivity/recall, and F1 Score. Overall, this review showed that the role of data pre-processing is no less important than algorithm selection to improve the performance of machine learning models in diabetes classification.
This systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. The review includes 19 studies across various cancers, including breast, colore...
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Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among th...
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