Year: 2024
Type: article
Abstract: Data mining is the process of using statistics, mathematics, artificial intelligence and machine learning to identify problems that exist in data so as to produce useful information. Based on its function, data mining is grouped into description, estimation, classification, clustering, and association. K-NN is one of the best data mining methods and is widely used in research. K-NN algorithm was introduced by Fix and Hodges in 1951. K-NN algorithm is a simple algorithm and is often used to cluster supervised data. Feature selection attribute selection is a data mining technique used in the pre-processing stage. This technique works by reducing complex attributes that will be managed at the processing and analysis stage. In this study, the most effective feature selection to improve the accuracy of the K-NN algorithm by increasing accuracy by 95.12% on the breast cancer dataset and 88.75% on the prostate cancer dataset.
Source: JURNAL TEKNIK INFORMATIKA
Authors: Fina Indri Silfana, Mula Agung Barata
Institution: Universitas Nahdlatul Ulama Sunan Giri
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403428015