Penerapan Algoritma C4.5 Dalam Prediksi Resiko Diabetes Tahap Awal (Early Stage Diabetes)

Wina Yusnaeni, Widiarina Widiarina

Abstract


Diabetes is a disease that is often encountered in all circles of society. From the data in the can even occur annually an increase in people with diabetes in the world. Many of the symptoms of the early stages that can be used as a reference to a person in the prediction of symptoms of diabetes or not. Hence the importance of prevention so that the increase going to health and could be spared from the disease diabetes. Based on those reasons here. researchers conducted the study by using the method of decision tree (C4.5) with the aid of rapid miner. The Data obtained is the data classification of the early stages of diabetic patients. To test the training and trials with a ratio of 90:10 using the split data on the application of rapid miner and process the decision tree method in addition add performance to calculate the accuracy. The results can be in the form of a decision tree that can be made a role in the testing dataset. In addition, the results of the evaluation data in the can the level of accuracy of 88.46 % where the amount of the percentage is said to be in the category of good classification.


Keywords


Diabetes, Decision tree. accuracy

Full Text:

PDF

References


Aris, F. (2019). Penerapan Data Mining untuk Identifikasi Penyakit Diabetes Melitus dengan Menggunakan Metode Klasifikasi. 1(1), 1–6.

Darmawan, E. (2018). C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education. Jurnal Online Informatika, 3(1), 22. https://doi.org/10.15575/join.v3i1.171

dr. Apriliana Adyaksari, Sp. PD, M. K. (2020). Waspada! Inilah Tanda-Tanda Gejala Diabetes. Https://Www.Emc.Id/Id/Care-plus/Waspada-Inilah-Tanda-Tanda-Gejala-Diabetes, 1.

Elisa, E. (2017). Analisa dan Penerapan Algoritma C4.5 Dalam Data Mining Untuk Mengidentifikasi Faktor-Faktor Penyebab Kecelakaan Kerja Kontruksi PT.Arupadhatu Adisesanti. Jurnal Online Informatika, 2(1), 36. https://doi.org/10.15575/join.v2i1.71

Fauzi, A., Saraswati, N. M., Cipta, R., & Hariyono, S. (2020). PENERAPAN ALGORITMA K-MODES DAN C4.5 UNTUK PREDIKSI PEMILIHAN JURUSAN DI UNIVERSITAS PERADABAN PADA SISWA SMA (Studi Kasus: SMA Islam Ta’allumul Huda Bumiayu). 1(2), 57–64.

Fiarni, C., Sipayung, E. M., & Maemunah, S. (2019). Analysis and prediction of diabetes complication disease using data mining algorithm. Procedia Computer Science, 161, 449–457. https://doi.org/10.1016/j.procs.2019.11.144

Gifu, D. (2021). The Use of Decision Trees for Analysis of the Epilepsy. Procedia Computer Science, 192, 2844–2853. https://doi.org/10.1016/j.procs.2021.09.055

Gorunescu, F. (2011). Data Mining Concepts, Models and Techniques. Springer Berlin Heidelberg. https://doi.org/DOI 10.1007

Much Aziz Muslim, Budi Prasetiyo, Eva Lalily Hamum M, Anisa Juli H, Mirqotussa’adah, Siti Hardiyanti R, A. N. Z. (2019). Data Mining Algoritma C4.5. In N. C. Eka Listiana (Ed.), Data Mining Algoritma C4.5. CV. Harian Jateng Network.

Noviandi. (2018). Implementasi Algoritma Decision Tree C4.5 Untuk Prediksi Penyakit Diabetes. Jurnal INOHIM, 6(1), 1–5. https://inohim.esaunggul.ac.id/index.php/INO/article/view/142

Putri, sanni ucha, Irawan, E., & Rizky, F. (2021). Implementasi Data Mining Untuk Prediksi Penyakit Diabetes. KESATRIA( Jurnal Penerapan Sistem Informasi Dan Manajemen, 2(1), 39–46.

Yusnaeni, W., & Widiarina. (2021). laporan Akhir: Penerapan Algoritma C4.5 Dalam Prediksi Resiko Diabetes Tahap Awal (Early Stage Diabetes).




DOI: https://doi.org/10.31294/jtk.v8i1.11566

Copyright (c) 2022 Wina Yusnaeni, Widiarina Widiarina

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

ISSN: 2442-2436 (print), and 2550-0120


 dipublikasikan oleh LPPM Universitas Bina Sarana Informatika Jakarta

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License