CLASSIFICATION OF LIVER DISEASE BY APPLYING RANDOM FOREST ALGORITHM AND BACKWARD ELIMINATION
Abstract
Cancer is a type of disease that is not realized by most people because most people associated with this disease lack understanding of cancer itself and are doing early detection of cancer, due to the majority of cancers found at an advanced stage and difficult to overcome to facilitate large expenditure to help cancer. Early detection of liver or liver cancer is very important to overcome the very high risk of death caused by liver or liver cancer. This study aims to help classify liver or liver cancer based on data from routine examination results of patients summarized in the Indian Liver Data Patient (ILDP) dataset. The method used in the classification process in this research is backward elimination modeling for testing optimization and Random Forest algorithm and split validation to validate the model. The results of this study yielded 76.00% and value of AUC 0.758 results. These results indicate that the results of this study are good enough to help classify breast cancer
Downloads
References
P. Handayani, E. Nurlelah, M. Raharjo, and P. M. Ramdani, “Prediksi Penyakit Liver Dengan Menggunakan Metode,” Pros. TAU SNAR-TEK Semin. Nas. Rekayasa dan Teknol., vol. 4, no. 1, pp. 75–80, 2019.
P. Widodo, “Rule-Based Classifier untuk Mendeteksi Penyakit Liver,” Bianglala Inform., vol. II, no. 1, pp. 71–80, 2014.
I. A. Medha and D. P. Hapsari, “Implementing Fuzzy Decision Tree for Predicting Liver Disease of Ilpd ( Indian Liver Patient Dataset ),” vol. 5, no. 2, 2019.
D. G. Kesuma, “a Women 51 Years With Decompensated Liver Cirrhosis With Gastritis Chronic and Kidney Chronic Disease,” vol. 3, no. September, pp. 151–159, 2014.
R. G. Rafsanjani, N. Hidayat, and R. K. Dewi, “Diagnosis Penyakit Hati Menggunakan Metode Naive Bayes Dan Certainty Factor,” vol. 2, no. 11, pp. 4478–4482, 2018.
N. D. Prayoga, N. Hidayat, and R. K. Dewi, “Sistem Diagnosis Penyakit Hati Menggunakan Metode Naïve Bayes,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 8, pp. 2666–2671, 2018.
A. P. Ayudhitama et al., “ANALISA 4 ALGORITMA DALAM KLASIFIKASI PENYAKIT LIVER,” pp. 1–9.
E. Nurlelah and M. S. Mardiyanto, “Pemilihan Atribut Pada Algoritma C4.5 Menggunakan Particle Swarm Optimization Untuk Meningkatkan Akurasi Prediksi Diagnosis Penyakit Liver,” J. Pilar Nusa Mandiri, vol. 15, no. 2, pp. 195–202, 2019.
E. Pusporani and S. Qomariyah, “Klasifikasi Pasien Penderita Penyakit Liver dengan Pendekatan Machine Learning,” vol. 2, no. March, 2019.
A. R. Safutra and D. W. Prabowo, “Diagnosis Penyakit Kanker Payudara Menggunakan Metode Naive Bayes Berbasis Desktop,” J. Penelit. Dosen FIKOM, vol. 6, no. 1, pp. 1–6, 2016.
E. Rahmawati, “Analisa Komparasi Algoritma Naive Bayes Dan C4.5 Untuk Prediksi Penyakit Liver,” None, vol. 12, no. 2, pp. 27–37, 2015.
E. V. I. Noviani, K. A. Sidarto, and Y. S. Putra, “PENGELOMPOKAN PASIEN KANKER LIVER BERDASARKAN DATA EKSPRESI GEN DENGAN,” pp. 1053–1062, 2012.
R. Annisa, “Analisis Komparasi Algoritma Klasifikasi Data Mining Untuk Prediksi Penderita Penyakit Jantung,” J. Tek. Inform. Kaputama, vol. 3, no. 1, pp. 22–28, 2019.
I. C. R. Drajana, “Metode Support Vector Machine Dan Forward Selection Prediksi Pembayaran Pembelian Bahan Baku Kopra,” Ilk. J. Ilm., vol. 9, no. 2, pp. 116–123, 2017.
Abstract viewed = 965 times
PDF downloaded = 473 times
-a.jpg)
-b.jpg)
