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Journal : "Journal of Data Science

Rapid Miner Testing With The Knn Algorithm Noferianto Sitompul
Journal Of Data Science Vol. 1 No. 02 (2023): Journal Of Data Science, September 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v1i02.2834

Abstract

In the modern era of computers and the internet, the need for effective data analysis tools is increasing. In the data mining industry, RapidMiner has developed into an essential tool for using simple but effective classification methods such as k-Nearest Neighbors (KNN). The purpose of this study is to evaluate RapidMiner's ability to implement KNN and evaluate its performance on various datasets derived from various characteristics. Test results show that RapidMiner can implement KNN with satisfactory accuracy for most datasets; The methodology used measures classification performance through metrics such as accuracy, recall, precision, and F1 score. In conclusion, RapidMiner has a lot of potential for practical application of KNN, but it has limitations when working with large datasets.