PERBANDINGAN ALGORITMA C4.5 DAN SVM DALAM KLASIFIKASI PENYAKIT ANEMIA
Abstract
Anemia is a condition when the hemoglobin in the body cannot function properly. Anemia has a bad impact on health, one of which is on the immune system. To prevent the occurrence of anemia can be done early detection by utilizing a mathematical approach using data mining. Data mining has classification methods that can be used for early detection of anemia. Methods that can be used for classification include the Support Vector Machines (SVM) algorithm and the C4.5 algorithm. This study applies the SVM algorithm and the C4.5 algorithm for the classification of early detection of anemia. The purpose of this study was to obtain the most appropriate method between the SVM algorithm and the C4.5 algorithm in the classification of anemia. This study applies percentage split testing techniques and k-fold cross validation. In the percentage split, a split of 80% was chosen as the training data and 20% as the test data. In k-fold cross validation, the value of k is chosen to be 10. The results of applying the two methods show that k-fold cross validation works better than percentage split with the percentage values for accuracy, precision, and recall being higher for each algorithm. For the performance of the two algorithms, C4.5 in its application works better with accuracy, precision, and recall values respectively, namely 99.29%, 98.7%, and 99.69% compared to the SVM algorithm. From the results obtained, it can be concluded that the C4.5 algorithm with the k-fold cross validation testing technique produces the best performance value for anemia classification compared to other testing algorithms and techniques.
Downloads
References
https://doi.org/10.30598/pijmathvol1iss1pp33-42
Drajana, I. C. R. (2017). Metode Support Vector Machine Dan Forward Selection Prediksi Pembayaran Pembelian Bahan Baku Kopra. ILKOM Jurnal Ilmiah, 9(2), 116–123. https://doi.org/10.33096/ilkom.v9i2.134.116-123
Edsel Barito, E., Tji Beng, J., & Arisandi, D. (2022). Penerapan Algoritma C4.5 Untuk Klasifikasi Mahasiswa Penerima Bantuan Sosial Covid-19. Ilmu Komputer Dan Sistem Informasi, 10(1). https://doi.org/https://doi.org/10.24912/jiksi.v10i1.17819
El Morr, C., Jammal, M., Ali-Hassan, H., & El-Hallak, W. (2022). Machine Learning for Practical Decision. 385-411. International Series in Operations Research & Management Science.
Febriani, S., & Sulistiani, H. (2021). Analisis Data Hasil Diagnosa Untuk Klasifikasi Gangguan Kepribadian Menggunakan Algoritma C4.5. Jurnal Teknologi Dan Sistem Informasi (JTSI), 2(4), 89–95.
https://doi.org/10.33365/jtsi.v2i4.1373
Gina Sonia, & Indriyani, A. (2023). Analisis Penerapan Data Mining Dengan Metode Algoritma C4.5 Untuk Pendataan Karyawan Tetap Di Koni Sumatera Utara. Journal of Computer Science and Informatics Engineering (CoSIE), 02(1), 48–55.
https://doi.org/10.55537/cosie.v2i1.523
Ginting, V. S., Kusrini, K., & Taufiq, E. (2020). Implementasi Algoritma C4.5 untuk Memprediksi Keterlambatan Pembayaran Sumbangan Pembangunan Pendidikan Sekolah Menggunakan Python. Inspiration: Jurnal Teknologi Informasi Dan Komunikasi, 10(1), 36–44. https://doi.org/10.35585/inspir.v10i1.2535
Hastuty, Y. D., Khodijah, D., & Hasibuan, Y. (2021). Edukasi Dan Deteksi Dini Anemia Remaja Putri Di Pancur Batu Kabupaten Deli Serdang. GEMAKES Jurnal Pengabdian Kepada Masyarakat, 1(2), 70–82. https://doi.org/10.36082/gemakes.v1i2.384
Inan, O., & Uzer, M. S. (2021). A Method of Classification Performance Improvement Via a Strategy of Clustering-Based Data Elimination Integrated with k-Fold Cross-Validation. Arabian Journal for Science and Engineering, 46(2), 1199–1212.
https://doi.org/10.1007/s13369-020-04972-y
Mahendro, I., & Abimanto, D. (2022). Analisa Kepuasan Mahasiswa Terhadap E-Learning Menggunakan Algoritma Support Vector Machine. Jurnal Sains dan Teknologi Maritim (JSTM), 23(1), 97–108
http://dx.doi.org/10.33556/jstm.v23i1.333
Markoulidakis, I., Kopsiaftis, G., Rallis, I., & Georgoulas, I. (2021). Multi-Class Confusion Matrix Reduction method and its application on Net Promoter Score classification problem. Technologies, 9(4), 412–419.
https://doi.org/10.1145/3453892.3461323
Naufal, S. A., Adiwijaya, A., & Astuti, W. (2020). Analisis Perbandingan Klasifikasi Support Vector Machine (SVM) dan K-Nearest Neighbors (KNN) untuk Deteksi Kanker dengan Data Microarray. JURIKOM (Jurnal Riset Komputer), 7(1), 162.
https://doi.org/10.30865/jurikom.v7i1.2014
Nurmasani, A., & Pristyanto, Y. (2021). Algoritme Stacking Untuk Klasifikasi Penyakit Jantung Pada Dataset Imbalanced Class. Jurnal Pseudocode, 8(1), 21–26.
https://doi.org/10.33369/pseudocode.8.1.21-26
Prasetya, K. A. H., & Wihandani, D. M. (2019). Hubungan Antara Anemia Dengan Prestasi Belajar Pada Siswi Kelas Xi Di Sman I Abiansemal Badung. E-Jurnal Medika Udayana, 8(1), 46.
https://doi.org/10.24922/eum.v8i1.45757
Primajaya, A., Sari, B. N., & Khusaeri, A. (2020). Prediksi Potensi Kebakaran Hutan dengan Algoritma Klasifikasi C4.5 Studi Kasus Provinsi Kalimantan Barat. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 6(2), 188. https://doi.org/10.26418/jp.v6i2.37834
Priyanto, L. D. (2018). Hubungan Umur, Tingkat Pendidikan, dan Aktivitas Fisik Antriwati Husada Dengan Anemia. Jurnal Berkala Epidemiologi, 6(2), 139.
https://doi.org/10.20473/jbe.v6i22018.139-146
Rahayu, S., & Purnama, J. J. (2022). Klasifikasi Konsumsi Energi Industri Baja Menggunakan Teknik Data Mining. Jurnal Teknoinfo, 16(2), 395.
https://doi.org/10.33365/jti.v16i2.1984
Ramadhan, N. G., & Khoirunnisa, A. (2021). Klasifikasi Data Malaria Menggunakan Metode Support Vector Machine. Jurnal Media Informatika Budidarma, 5(4), 1580. https://doi.org/10.30865/mib.v5i4.3347
Siahaan, S. W., Sianipar, K. D. R., R.H Zer, P. P. P. A. N. . F. I., & Hartama, D. (2020). Penerapan Algoritma C4.5 Dalam Meningkatkan Kemampuan Bahasa Inggris Pada Mahasiswa. Petir, 13(2), 229–239.
https://doi.org/10.33322/petir.v13i2.1029
Stewart, T. G., Zeng, D., & Wu, M. C. (2018). Constructing support vector machines with missing data. WIREs Computational Statistics, 10(4), 1–27. https://doi.org/10.1002/wics.1430
Yahdin, S., Desiani, A., Amran, A., Rodiah, D., & Solehan. (2019). Pattern Recognation for Study Period of Student in Mathematics Department with C4.5 Algorithm Data Mining Technique at the Faculty of Mathematics and Natural Science Universitas Sriwijaya. Journal of Physics: Conference Series, 1282(1), 1–6. https://doi.org/10.1088/1742-6596/1282/1/012014
Copyright (c) 2023 Dina Elly Yanti, Lizah Framesti, Anita Desiani
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright for articles published in this journal is retained by the authors, with first publication rights granted to the journal. By virtue of their appearance in this open access journal, articles are free to use after initial publication under the International Creative Commons Attribution-NonCommercial 4.0 Creative Commons CC_BY_NC.
