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All Journal Jurnal Sains dan Seni ITS Jurnal Neutrino : jurnal fisika dan aplikasinya Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal SOLMA Jusikom : Jurnal Sistem Komputer Musirawas Jurnal ULTIMA Computing Jurnal Telematika Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Pendidikan Fisika dan Teknologi Al-Khidmat : Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Sistem informasi dan informatika (SIMIKA) Generation Journal Attanwir : Jurnal Keislaman dan Pendidikan Jurnal Pendidikan dan Teknologi Indonesia Inovasi Fisika Indonesia (IFI) Indonesian Community Journal Almantiq
Roihatur Rohmah
Universitas Nahdlatul Ulama Sunan Giri
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Journal : Jurnal Sistem informasi dan informatika (SIMIKA)

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KOMPARASI ALGORITMA DECISION TREE DAN SUPPORT VECTOR MACHINE (SVM) DALAM KLASIFIKASI SERANGAN JANTUNG Laili, Elok Fathiyatul; Alawi, Zakki; Rohmah, Roihatur; Barata, Mula Agung
Jurnal Sistem Informasi dan Informatika (Simika) Vol 8 No 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3683

Abstract

The heart is one of the most important organs in the human body. According to the WHO, heart attacks are the most common cause of sudden death worldwide, with more than 17.8 million people dying from heart attacks. A heart attack occurs when blood flow to the coronary arteries stops, depriving the heart muscle of oxygen, and causing a heart attack. Detecting a heart attack is very difficult due to the various symptoms. The purpose of this research is to compare the performance of the accuracy values of two algorithms, namely Decision Tree and Support Vector Machine (SVM) in classifying heart attacks. The results of this study show that the Decision Tree algorithm achieves the highest accuracy results compared to the SVM algorithm. The accuracy of the Decision Tree algorithm using a 60:40 ratio data splitting is 98.11% with a negative precision of 98.01% and positive of 98.17% and a negative recall of 97.04% and positive of 98.77%. Meanwhile, the SVM algorithm using data splitting with the same ratio produces an accuracy value of 92.80% with a negative precision of 90.24% and a positive of 94.43% and a negative recall of 91.13% and a positive of 93.85%.
Co-Authors Al-Hakim, Achmad Fatichul Aralia, Shafa Kirana Azizirrohim, Ahmad Bassalam, Ahmad Nasih Ulwan Burhanatut Dyana Dwi Syafi'i, Ahmad Erlangga Dwi Aprila Vibianto Farikhah, Ainun Nurul Hambali, Ridlwan Hilmi, Allif Rosyidy Irsyada, Rahmat Jauhar Vikri, Muhammad Khoirul Faizin Kurniawan, Ananda Romy Laili, Elok Fathiyatul Levia, Zachdyna Aurelya M. Ridlwan Hambali Mauluddin, Rizqi Nanda Mochamad Zainuri Moh. Mu'id Efendi Moh. Muhajir Mukaromah, Lisa Aminatul Mukti Fatimah Mukti Fatimah Mula Agung Barata Mundzar Fahman Nikmah, Siti Mauidhotun Nugraha, Krisna Wahyu Oktavio Bima Saputra Pelangi Eka Yuwita Prayoga Dewa Pangestu Putri Lian Putri Liana Rheyna Anggri Setyani Vita Dwi Rahmawati Zainuri (DOI: 10.12962/j24604682.v12i2.1331), Mochamad Zakki Alawi Zayn , Afta Ramadhan