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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Rahmat Ardila Dwi Yulianto
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Computer Science & IT Engineering

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Journal : RABIT: Jurnal Teknologi dan Sistem Informasi Univrab

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PERANCANGAN KLASIFIKASI PASIEN STROKE DENGAN METODE K-NEAREST NEIGHBOR Rahmat Ardila Dwi Yulianto; Imam Riadi; Rusydi Umar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 2 (2023): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i2.3454

Abstract

Stroke is a disease characterized by impaired brain function caused by a lack of oxygen supply and blood flow to the brain, affecting several brain functions that make sufferers experience difficulty in carrying out activities. the classification of stroke patients found is still in the form of medical records that have not been integrated so it takes longer time to detect. The K-NN algorithm is part of a machine learning algorithm that can be used to classify one of the cases, namely the classification of stroke patients. K-NN is used as a class determining algorithm to enter new data that is input according to the format. Based on the results obtained, this study leads to system design using the Unified Model Language (UML) and system user interface design.
Co-Authors Imam Riadi Rusydi Umar