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Authors: Irmawati Carolina 1 ; Baginda Oloan Lubis 1 ; Adi Supriyatna 1 and Rachman Komarudin 2

Affiliations: 1 Universitas Bina Sarana Informatika, Jakarta, Indonesia ; 2 Universitas Nusa Mandiri, Jakarta, Indonesia

Keyword(s): K-Nearest Neighbor Method, Particle Swarm Optimization, Classification of Heart Disease.

Abstract: Heart disease is a condition in which there is dysfunction in the work of the heart. Diseases of the heart are of many types such as cardiovascular, coronary heart disease and heart attack. Cardiac groaning is one of the deadliest diseases in the world with mortality reaching 12.90% of all heart diseases. This lack of access to find information about heart disease leads to an increase in mortality rates in each case. Therefore, a classification system is needed that can provide information about heart attack disease and can check the classification early about heart attack disease experienced by a person. The application of the K Nearest Neighbor algorithm model and the K Nearest Neighbor (K-NN) algorithm based on Particle Swarm Optimization (PSO) was carried out to find out which model provided the best results in detecting chronic kidney disease. The selection of both models is considered because the K Nearest Neighbor algorithm is one of the best data mining algorithms, but it ten ds to have weaknesses in overlapping data, classes and many attributes. Therefore, the Particle Swarm Optimization (PSO) optimization technique. From the results of the study, it was obtained that the PSO-based K-NN algorithm model was able to select attributes so that it could increase a better accuracy value with a result of 9 2.98% with an AUS value of 0.961 compared to the individual model of the K-NN algorithm which produced an accuracy value of 92.32% and an AUC value of 0.956%. (More)

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Paper citation in several formats:
Carolina, I.; Oloan Lubis, B.; Supriyatna, A. and Komarudin, R. (2024). Application K-Nearest Neighbor Method with Particle Swarm Optimization for Classification of Heart Disease. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 181-186. DOI: 10.5220/0012446200003848

@conference{icaisd24,
author={Irmawati Carolina. and Baginda {Oloan Lubis}. and Adi Supriyatna. and Rachman Komarudin.},
title={Application K-Nearest Neighbor Method with Particle Swarm Optimization for Classification of Heart Disease},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD},
year={2024},
pages={181-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012446200003848},
isbn={978-989-758-678-1},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD
TI - Application K-Nearest Neighbor Method with Particle Swarm Optimization for Classification of Heart Disease
SN - 978-989-758-678-1
AU - Carolina, I.
AU - Oloan Lubis, B.
AU - Supriyatna, A.
AU - Komarudin, R.
PY - 2024
SP - 181
EP - 186
DO - 10.5220/0012446200003848
PB - SciTePress

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