ANALISIS RISIKO KESEHATAN TERHADAP PENYAKIT DIABETES MENGGUNAKAN ALGORITMA C4.5

  • Wida Prima Mustika Universitas Bina Sarana Informatika, Jakarta
  • Reggy Helva Rezal Universitas Bina Sarana Informatika, Jakarta
  • Andi Diah Kuswanto Universitas Bina Sarana Informatik, Jakarta
  • Febri Windianti Ekatami Universitas Bina Sarana Informatika, Jakarta
  • Indah Gita Cahyani Universitas Bina Sarana Informatika, Jakarta
  • Ilham Agustian Universitas Bina Sarana Informatika, Jakarta
  • Syahputra Ibrahim Universitas Bina Sarana Informatika, Jakarta
DOI: https://doi.org/10.52362/jmijayakarta.v6i2.2183

Abstract

India is the country with the second highest number of diabetes cases in the world after Tiongkok with more than 77 millions cases in 2021. This study aims to analyze the risk of developing diabetes using the C4.5 algorithm based on public health data in India. The dataset used in this study was obtained from Kaggle under the title “Pima Indians Diabetes Dataset” which was updated in September 2025. Data processing was performed using the RapidMiner application with a data mining method based on the C4.5 algorithm to classify data based on variables such as age, number of pregnancies, body mass index (BMI), blood pressure, blood sugar levels, and insulin levels. The results of the study show that the C4.5 algorithm is capable of identifying diabetes risk patterns with a fairly good level of accuracy so that it can be used as a tool to assist in decision making for early detection of diabetes risk.

References

[1] E. Handayani, N. Maesaroh, N. Azizah, and A. H. Mukaromah, “Sosialisasi Penyakit Diabetes Melitus Pada Kelompok Dasawisma Sendangguwo Kelurahan Gemah Kecamatan Pedurungan Kota Semarang,” Pros. Semin. Nas. Unimus, vol. 4, pp. 2565–2572, 2021.
[2] K. R. Widiasari, I. Made, K. Wijaya, and P. A. Suputra, “Tatalaksana Diabetes Melitus Tipe II,” Ganesha Med. J., vol. 1, no. 2, pp. 114–120, 2021, [Online].
[3] W. P. Sakul and H. Andriani, “Prevalensi Global Diabetes Mellitus : Tinjauan Sistematis Negara-Negara Dengan Beban Tinggi Dan Strategi,” vol. 9, no. 1, pp. 5150–5158, 2025.
[4] A. Fauzi, “Aplikasi Sistem Pakar Dengan Metode Naive Bayes untuk Mendeteksi Penyakit Diabetes Expert System Application Using the Naive Bayes Method to Detect Diabetes,” vol. 15, no. April, pp. 17–31, 2025.
[5] Chandra, David, and Hendri, “Implementasi Algoritma C4.5 Untuk Deteksi Dini Penyakit Diabetes Mellitus Pada Manusia,” Bull. Comput. Sci. Res., vol. 4, no. 2, pp. 241–248, 2024, doi: 10.47065/bulletincsr.v4i2.337.
[6] R. A. Siallagan and Fitriyani, “Prediksi Penyakit Diabetes Mellitus Menggunakan Algoritma C4.5,” J. Responsif Ris. Sains dan Inform., vol. 3, no. 1, pp. 44–52, 2021, doi: 10.51977/jti.v3i1.407.
[7] R. P. Fadhillah, R. Rahma, A. Sepharni, R. Mufidah, B. N. Sari, and A. Pangestu, “Klasifikasi penyakit diabetes mellitus berdasarkan faktor-faktor penyebab diabetes menggunakan algoritma c4.5,” vol. 07, pp. 1265–1270, 2022.
[8] F. M. Hana, “Klasifikasi Penderita Penyakit Diabetes Menggunakan Algoritma Decision Tree
C4 . 5,” 2020.
Published
2026-04-07
How to Cite
MUSTIKA, Wida Prima et al. ANALISIS RISIKO KESEHATAN TERHADAP PENYAKIT DIABETES MENGGUNAKAN ALGORITMA C4.5. Jurnal Manajamen Informatika Jayakarta, [S.l.], v. 6, n. 2, p. 89-101, apr. 2026. ISSN 2797-0930. Available at: <https://journal.stmikjayakarta.ac.id/index.php/JMIJayakarta/article/view/2183>. Date accessed: 10 apr. 2026. doi: https://doi.org/10.52362/jmijayakarta.v6i2.2183.
Citation Formats
Issue
Vol 6 No 2 (2026): JMI Jayakarta (April 2026)
Section
Articles
Creative Commons License

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

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.