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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Ilmiah Teknologi dan Rekayasa ELECTRANS JTERA (Jurnal Teknologi Rekayasa) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Elektronika dan Telekomunikasi Jurnal ULTIMA Computing Jurnal Teknologi Terpadu Indonesian Journal of Electrical Engineering and Computer Science TECHNO-SOCIO EKONOMIKA Jurnal Dharma Bhakti Ekuitas Journal La Multiapp EPSILON: Journal of Electrical Engineering and Information Technology
Nurul Fahmi Arief Hakim
Universitas Pendidikan Indonesia
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : Jurnal Teknologi Terpadu

 1 
Hybrid Machine Learning Model untuk memprediksi Penyakit Jantung dengan Metode Logistic Regression dan Random Forest Silmi Ath Thahirah Al Azhima; Dwicky Darmawan; Nurul Fahmi Arief Hakim; Iwan Kustiawan; Mariya Al Qibtiya; Nendi Suhendi Syafei
Jurnal Teknologi Terpadu Vol. 8 No. 1: July, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.539

Abstract

The heart is the main organ that must work properly and regularly. If there is interference, it will be fatal, namely the onset of a heart attack. Heart attack is included in the 10 diseases with a high risk of death. This is caused by stress factors, blood pressure, excessive work, blood sugar, and others. The purpose of this study is to predict heart disease using Machine Learning (ML) algorithms as an early preventive measure on desktop-based information systems. With Machine Learning models, the hybrid model can increase the accuracy value of an ML method that is added to other ML methods. The accuracy value obtained from the Hybrid Model Machine Learning using the Random Forest and Logistic Regression methods is 84.48%, which is an increase of 1.32%.  
Hybrid Machine Learning Model untuk memprediksi Penyakit Jantung dengan Metode Logistic Regression dan Random Forest Al Azhima, Silmi Ath Thahirah; Darmawan, Dwicky; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtiya, Mariya; Syafei, Nendi Suhendi
Jurnal Teknologi Terpadu Vol 8 No 1: Juli, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.539

Abstract

The heart is the main organ that must work properly and regularly. If there is interference, it will be fatal, namely the onset of a heart attack. Heart attack is included in the 10 diseases with a high risk of death. This is caused by stress factors, blood pressure, excessive work, blood sugar, and others. The purpose of this study is to predict heart disease using Machine Learning (ML) algorithms as an early preventive measure on desktop-based information systems. With Machine Learning models, the hybrid model can increase the accuracy value of an ML method that is added to other ML methods. The accuracy value obtained from the Hybrid Model Machine Learning using the Random Forest and Logistic Regression methods is 84.48%, which is an increase of 1.32%.  
Co-Authors Aip Saripudin Al Azhima, Silmi Ath Thahirah Al Qibtiya, Mariya Al Qibtya, Mariya Anandayutya, Bagaskara Ardiansyah, Yogi Arjuni Budi Pantjawati Ath Thahirah Al Azhima, Silmi Azhima, Silmi Ath Thahirah Al Dadang Lukman Hakim Darmawan, Alvin Dzaki Pratama Darmawan, Dwicky Dwicky Darmawan Fauzan, Mochamad Rizal Fredianto, Riko Iwan Kustiawan Juanda, Enjang Akmad Kaniarudi, Neneng Puspita Karostiani, Novia Khairi, Saiqa Fatur Mariya Al Qibtiya Mariya Al Qibtiya Mariya Al Qibtiya Mariya Al Qibtiya Moechammad Sarosa Muhammad Adli Rizqulloh Muhammad Randi Alwi Nawawi, Aif Umar Nawawi, Imam Khushthon Nendi Suhendi Syafei Nurhidayatulloh, Nurhidayatulloh Permadi, Tesya Prio Aji Widiantoro Resa Pramudita Riko Fredianto Robby Ikhfa Nulfatwa Roer Eka Pawinanto, Roer Eka Saputra, Dede Irawan Silmi Ath Thahirah Al Azhima Silmi Ath Thahirah Al Azhima Siscka Elvyanti, Siscka Tommi Haryadi Widiantoro, Prio Aji