https://eurogeojournal.eu/ https://jurnal.pendidikanbiologiukaw.ac.id/
https://e-kerja.bnpp.go.id/bkp/https://journal.dkpp.go.id/wow/https://ppid.dkpp.go.id/_fungsi/dana/https://jurnal.pendidikanbiologiukaw.ac.id/https://e-kerja.bnpp.go.id/Pengawas/demo/https://jos.unsoed.ac.id/stats/2024/https://journal.umkendari.ac.id/dm/https://jurnal.radenfatah.ac.id/demo/https://journal.ar-raniry.ac.id/lap/https://sipeg.ui.ac.id/dm/https://e-kerja.bnpp.go.id/Pengawas/dana/
slot gacor 2025slot gacor 2025slot gacor 2025slot gacor 2025slot gacor 2025slot gacor
Analisis Metode Ensemble Pada Klasifikasi Penyakit Jantung Berbasis Decision Tree | Aziz | JURNAL MEDIA INFORMATIKA BUDIDARMA

Analisis Metode Ensemble Pada Klasifikasi Penyakit Jantung Berbasis Decision Tree

Mochammad Ilham Aziz, Ahmad Zainul Fanani, Affandy Affandy

Abstract


Heart disease is one disease that is not easy to predict early on and maybe some people are not aware that they have the disease. Data obtained by WHO More than 17 million people worldwide died of heart attacks in 2016. If thesymptoms of heart disease or heart attack are known, prevention of heart disease can be anticipated and even minimized mortality. Analysis of heart disease aims to reduce mortality from the disease. In writing this research, a decision tree algorithm method is used, the algorithm still has weaknesses in making prediction accuracy. So we need a way to improve the accuracy of the classification learning outcomes. This study aims to improve the learning outcomes of heart disease classification by using ensemble learning methods, namely Boostrap Aggregating (Bagging) and Adaptive Boosting (Adaboost). Both methods were tested by predicting deaths caused by heart disease.

Keywords


Decision Tree; Heart Disease; Death; Bagging; Adaboost

Full Text:

PDF

References


Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart disease and stroke statistics. 2021 update: a report from the American Heart Associationexternal icon. Circulation. 2021;143:e254–e743.

enter for disease control and prevention. 2021, https://www.cdc.gov/heartdisease/facts.htm. Diakses pada 2 Januari 2022 pukul 23.12.

Cheryl D. Fryar, M.S.P.H.; Te-Ching Chen, Ph.D.; and Xianfen Li, M.S. Prevalence of Uncontrolled Risk Factors for Cardiovascular Disease: United States, 1999–2010, NCHS Data Brief, No. 103, August 2012.

A. Chauhan, A. Jain, P. Sharma, V. Deep, prediksi penyakit jantung menggunakan pembelajaran aturan evolusioner, dalam: Konferensi Internasional ke-4 2018 Kecerdasan Komputasi & Teknologi Komunikasi (CICT), Ghaziabad ,2018, hlm. 1-4.

Larose, Daniel T. 2005. Discovering Knowledge in Data: An Introduction to Data Mining. John Willey & Sons, Inc.

Dai Qin-yun,. Zang Chun-Ping., Wu Hao. 2016. Research of Decision tree Classification Algorithm in Data Mining. Dept. of Electric and Electronic Engineering, Shijiazhuang Vocational and Technology Institute. China

Sharma, R., Purushottam, Saxena, K. 2016. Efficient Heart Disease Prediction System using Decision Tree. International Conference on Computing, Communication and Automation (ICCCA), Noida, India, 15-16 May. 72-77. DOI: 10.1109/CCAA.2015.7148346

Zhang, S. (2012). Decision tree classifiers sensitive to heterogeneous costs. Journal of Systems and Software, 85(4), 771–779. doi:10.1016/j.jss.2011.10.007

Hou, S., Hou, R., Shi, X., Wang, J., & Yuan, C. 2014. Research on C5.0 Algorithm Improvement and the Test in Lightning Disaster Statistics.International Journal of Control and Automation, 7(1), 181-190.

Kavitha, R., Kannan, E. 2016. An Efficient Framework for Heart Disease Classification using Feature Extraction and Feature Selection Technique in Data Mining. International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS), pp. 1-5.

Pristyanto, Yoga. 2019. “Penerapan Metode Ensemble Untuk Meningkatkan Kinerja Algoritme Klasifikasi Pada Imbalanced Dataset.†Jurnal TEKNOINFO 13 (1): 11–16.

Puspitawuri, Annisa, Edy Santoso, and Candra Dewi. 2019. “Diagnosis Tingkat Risiko Penyakit Stroke Menggunakan Metode K-Nearest Neighbor Dan Naïve Bayes.†Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer 3 (4): 3319–24. https://j-ptiik.ub.ac.id/index.php/jptiik/article/view/4916.

Adelina, Vina, Dian Eka Ratnawati, and M. Ali Fauzi. 2018. “Klasifikasi Tingkat Risiko Penyakit Stroke Menggunakan Metode GA-Fuzzy.†Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer 2 (September): 3015–21. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/2513.

Amini, Leila, Reza Azarpazhouh, Mohammad Taghi Farzadfar, Sayed Ali Mousavi, and Farahnaz Jazaieri. 2013. “Prediction and Control of Stroke by Data Mining.†International Journal of Preventive Medicine 4 (May): 245–49.

Bisri, Achmad. 2015. “Penerapan Adaboost Untuk Penyelesaian Ketidakseimbangan Kelas Pada Penentuan Kelulusan Mahasiswa Dengan Metode Decision Tree.†Journal of Inteligent System 1 (1):27-32.

Kansadub, Teerapat, and Sotarat Thammaboosadee. 2015. “Stroke Risk Prediction Model Based on Demographic Data.†2015 8th Biomedical Engineering International Conference (BMEiCON),3-5.

Byna, Agus, and Muhammad Basit. 2020. “Penerapan Metode Adaboost Untuk Mengoptimasi Prediksi Penyakit Stroke Dengan Algoritma Naïve Bayes.†Jurnal Sisfokom (Sistem Informasi Dan Komputer) 09 (November): 407–11.

D.Senthil Kumar , G.Sathyadevi and S.Sivanesh. (2016). Decision Support System for Medical Diagnosis Using Data Mining. IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 1.

Tayeb, Shahab., Pirouz, Matin., Sun, Johann., Hall, Kaylee., Chang, Andrew., Li, Jessica., Song, Connor., Chauhan, Apoorva., Ferra, Michael., Sager, Theresa., Zhan, Justin & Latifi, Shahram. 2018. Toward Predicting Medical Conditions Using K-Nearest Neighbors. IEEE International Conference on Big Data 3897– 3903.

Muslim, Much Aziz, Aldi Nurzahputra, and Budi Prasetiyo. 2018. “Improving Accuracy of C4 . 5 Algorithm Using Split Feature Reduction Model and Bagging Ensemble for Credit Card Risk Prediction.†2018 International Conference on Information and Communications Technology (ICOIACT), no.1996: 141–45.

Hana Rasheid Esmaeel (2020). Analysis of classification learning algorithms. Indonesian Journal of Electrical Engineering and Computer Science Vol. 17, No. 2, February 2020, pp. 1029~1039

Hand, David J. 2007. Principles of Data Mining. Springer:London.

Gorunescu, F. 2011. Data Mining Concepts, Models, and Techniques. Springer: Berlin.

Alpaydin, E. 2016. Machine Learning: the New AI. MIT Press.

Carlos J. Mantas, Joaquín Abellán, Javier G. Castellano (2016). Analysis of Credal-C4.5 for classification in noisy domains. Express System With Applications 61 314-326 Elsevier.

Latha, C Beulah Christalin, and S Carolin Jeeva. 2019. “Improving the Accuracy of Prediction of Heart Disease Risk Based on Ensemble Classification Techniques.†Informatics in Medicine Unlocked 16 (June): 100203. https://doi.org/10.1016/j.imu.2019.100203.

Tran, Cao Truong, Mengjie Zhang, Peter Andreae, and Bing Xue. 2017a. “Bagging and Feature Selection for Classification with Incomplete Data.†European Conference on the Applications of Evolutionary 10199 (April): 471–86.

Schapire, R. E., & Freund, Y. (1997). A Decision-Theoretic Generalization of On-Line Learning and an Aplication to Boosting. Journal of Computer and System Sciences, 55, 119-139. https://doi.org/10.1088/00344885/55/7/004.

Rokach, L. (2010). Ensemble-based classifiers. Artificial Intelligence Review. 33, 1-39. https://doi.org/10.1007/s10462-009-9124-7.

Ramdhani, Lis Saumi. 2016. “Penerapan Particle Swarm Optmization (PSO) Untuk Seleksi Atribut Dalam Meningkatkan Akurasi Prediksi Diagnosis Penyakit Hepatitis Dengan Metode Algoritma C4 . 5.†Jurnal Ilmu Komputer, Manajemen Dan Sosial (SWABUMI) IV (1): 1-5.




DOI: https://doi.org/10.30865/mib.v7i1.5169

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 JURNAL MEDIA INFORMATIKA BUDIDARMA

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.


JURNAL MEDIA INFORMATIKA BUDIDARMA
Universitas Budi Darma
Secretariat: Sisingamangaraja No. 338 Telp 061-7875998
Email: mib.stmikbd@gmail.com

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.