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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Syntax Jurnal Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Conference on Innovation and Application of Science and Technology (CIASTECH) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi TIN: TERAPAN INFORMATIKA NUSANTARA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Scientific Student Journal for Information, Technology and Science Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Buana Pengabdian Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Nasional Inovasi Gagasan Abdimas & Kuliah Kerja Nyata Scientific Journal of Informatics Green Engineering: Journal of Engineering and Applied Science
Baihaqi, Kiki Ahmad
Universitas Buana Perjuangan Karawang
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Journal : Scientific Journal of Informatics

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Comparison Model Optimal Machine Learning Model With Feature Extraction for Heart Attack Disease Classification Salsa Desmalia; Amril Mutoi Siregar; Kiki Ahmad Baihaqi; Tatang Rohana
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.4561

Abstract

Purpose: The purpose of this study is to classify the number of people affected by heart disease and those not affected by heart disease based on various categories of heart attack causes. This study aims to urge people to take better care of their health and to serve as a reference for doctors to educate patients about the dangers of heart attacks. Methods: The model will be constructed via a machine learning methodology. The algorithms utilized in its development encompass the Support Vector Machine (SVM) algorithm, the K-Nearest Neighbor (k-NN) algorithm, and the Random Forest (RF) algorithm.  This study utilizes principal component analysis (PCA) as a means of extracting optimized features from the dataset, employing techniques for dimension reduction prior to modeling the data. Result: Cumulative explication of the concept of variance constitutes a foundational aspect of PCA (principal component analysis) within the scope of the current research, namely a dimensionality reduction technique employed in multivariate data analysis to facilitate model development, thereby enabling the creation of more optimal and comprehensive models. In this research, the dimensions of training data are incorporated during the process of model creation.   The results show KNN model exhibits the highest performance, with an accuracy of 86%, precision of 86%, recall of 91%, and F1-score of 88%. Furthermore, evaluation using the ROC metric also provides a relatively favorable value, 0.85. Novelty: Researchers used 1190 patient data sourced from Kaggle. Before modeling the algorithm, researchers conducted EDA & Preprocessing which includes missing values to find data that does not have information, then duplicate data to find duplicated data, there are 270 duplicated data, then the duplicated data is deleted so that the data becomes 737, then PCA implementation is carried out.  PCA is reducing features automatically without changing the data.
Co-Authors Adi Rizky Pratama Adinata, Abdul Rohim Aditya Zatnika Agung Susilo Yuda Irawan Agusti, Anggi Renata Agustin, Rachmayanti Tri Ahmad Fauzi Ahmad Fauzi April Lia Hananto Awal, Elsa Elvira Azhari Ali Ridha Azhari, Febrian Akbar Bagja Nugraha Bagus Setiawan Bambang Sukowo Billy Ibrahim Hasbi Candra Zonyfar Candra Zonyfar Danny Manongga Deden Wahiddin Dendi Prana Yudha Deny Adi Faldano Devi Fitrianah Didi Juardi Direja, Azhar Ferbista Eko Purwirawansyah Erick Fernando Faisal, Sutan Fariz Duta Nugraha Fauzi Ahmad Muda Fitria, Denisa Gozali, Gozali Habib Abdullah Hanny Hikmayanti Handayani Hardjianto, Mardi Hendry Herfandi Herfandi Heryana, Nono Hilda Yulia Novita Iman Permana Indah Listiyowati Indra, Jamaludin Iwan Setyawan Juardi, Didi Krisna Perdana Jaya Sitompul Krisna Widi Nugraha Kusumaningrum, Dwi Sulistya Lestari, Santi Arum Puspita M. Naufal Faqih Madani, Puja Milenia Sriwildan Mayasari, Rini Muhammad Raja Nurhusen Narwan Nahrudin Nisa Utami, Nisa Nofie Prasetiyo Nurdin, Cherry Januar Nurlaelasari, Euis Pertiwi, Anggun Purnomo, Hendryanto Dwi Rafikoh, Zahra Anggun Rahmat Rahmat Reza Avrizal Reza Maulana Rian Ardianto Rini Mayasari Rini Mayasari Riza Phahlevi Marwanto Rizki Septian Akbar Rohana, Tatang Rosyid Ridlo Al-Hakim Salsa Desmalia Saruni Dwiasnati Siregar, Amril Mutoi suhliyyah Suja Priyanto Sukmawati, Cici Emilia Sulistya, Dwi Sutan Faisal Tatang Rohana Ulfatus Soleha Vandelweiss, Dita Aura Wahiddin, Deden Waiddin, Deden Wardi Karto Destian Yana Cahyana Yudo Devianto Zonyfar, Candra