Implementation of C4.5 Algorithm for Disease Classification: Literature Review
Keywords:
C4.5 Algorithm, Disease ClassificationAbstract
Several studies have shown that the C4.5 algorithm is capable of achieving a high level of accuracy in diagnosing various diseases. For example, a study by Konstas et al. (2010) showed that the C4.5 algorithm was capable of achieving an accuracy level of 89% in diagnosing coronary heart disease. This study aims to discuss the application of the C4.5 Algorithm in disease classification as has been done by previous studies. This study is a literature review, which includes references related to the cases or problems identified. The author uses data from a literature study, a method used to collect data or sources related to the topic discussed in a study. The results of this Algorithm literature review can help doctors diagnose diseases more quickly, accurately, and efficiently. However, it is important to remember that the C4.5 algorithm is only a tool, and cannot replace the diagnosis of a professional doctor.
References
Faust, O., Acharya, U. R., Sudarshan, V. K., San Tan, R., Yeong, C. H., Molinari, F., & Ng, K. H. (2017). Computer aided diagnosis of coronary artery disease, myocardial infarction and carotid atherosclerosis using ultrasound images: a review. Physica Medica, 33, 1-15. https://www.sciencedirect.com/science/article/abs/pii/S1120179716311012
Al-Salihy, N. K., & Ibrikci, T. (2017, February). Classifying breast cancer by using decision tree algorithms. In Proceedings of the 6th international conference on software and computer applications (pp. 144-148). https://dl.acm.org/doi/abs/10.1145/3056662.3056716
Minton, S. (Ed.). (2014). Machine learning methods for planning. Morgan Kaufmann.
Munggaran, A. P., & Hidayatulloh, T. (2015). Penerapan Algoritma C4. 5 Untuk Diagnosa Penyakit Diare Pada Anak Balita Berbasis Mobile. Swabumi, 2(1), 47-58. https://ejournal.bsi.ac.id/ejurnal/index.php/swabumi/article/view/1960
Septiani, W. D. (2014). Penerapan Algoritma C4. 5 untuk prediksi penyakit Hepatitis. Jurnal Techno Nusa Mandiri, 11(1), 69-78. https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/172
Ente, D. R., Thamrin, S. A., Arifin, S., Kuswanto, H., & Andreza, A. (2020). Klasifikasi Faktor-Faktor Penyebab Penyakit Diabetes Melitus Di Rumah Sakit Unhas Menggunakan Algoritma C4. 5. Indonesian Journal of Statistics and Its Applications, 4(1), 80-88. https://journal-stats.ipb.ac.id/index.php/ijsa/article/view/330
Sepharni, A., Hendrawan, I. E., & Rozikin, C. (2022). Klasifikasi Penyakit Jantung dengan Menggunakan Algoritma C4. 5. STRING (Satuan Tulisan Riset dan Inovasi Teknologi), 7(2), 117-126. https://journal.lppmunindra.ac.id/index.php/STRING/article/view/12012
Rohman, A., Suhartono, V., & Supriyanto, C. (2017). Penerapan algoritma c4. 5 berbasis adaboost untuk prediksi penyakit jantung. Jurnal Cyberku, 13(1), 2-2.
Afifuddin, A., & Hakim, L. (2023). Deteksi Penyakit Diabetes Mellitus Menggunakan Algoritma Decision Tree Model Arsitektur C4. 5. Jurnal Krisnadana, 3(1), 25-33. https://ejournal.sidyanusa.org/index.php/jkdn/article/view/470
Hana, F. M. (2020). Klasifikasi Penderita Penyakit Diabetes Menggunakan Algoritma Decision Tree C4. 5. Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan), 4(1), 32-39. https://jurnal.tau.ac.id/index.php/siskom-kb/article/view/173
Maulana, R., Narasati, R., Herdiana, R., Hamonangan, R., & Anwar, S. (2023). KOMPARASI ALGORITMA DECISION TREE DAN NAIVE BAYES DALAM KLASIFIKASI PENYAKIT DIABETES. JATI (Jurnal Mahasiswa Teknik Informatika), 7(6), 3865-3870. https://ejournal.itn.ac.id/index.php/jati/article/view/8265
Sidiq, C. M., Faqih, A., & Dwilestari, G. (2024). ALGORITMA DECISION TREE C4. 5 DIGUNAKAN UNTUK MENGKLASIFIKASIKAN DATA STROKE. JATI (Jurnal Mahasiswa Teknik Informatika), 8(2), 1869-1874. https://ejournal.itn.ac.id/index.php/jati/article/view/8388
