Implementasi Algoritma K-Nearest Neighbor (KNN) Untuk Prediksi Penyakit Diabetes Berbasis Web

Heri Setiawan Fauzi; Khanif Faozi

doi:10.69693/jesa.v3i2.103

Authors

Heri Setiawan Fauzi Universitas Pamulang
Khanif Faozi Universitas Pamulang

DOI:

https://doi.org/10.69693/jesa.v3i2.103

Keywords:

K-Nearest Neighbor, Diabetes Mellitus, Web-Based Prediction, Early Detection, Machine Learning

Abstract

Diabetes mellitus is a chronic metabolic disease that requires early detection to reduce the risk of serious complications. Limited access to practical screening tools encourages the development of a web-based prediction system that can be accessed independently. This study develops a web application for predicting diabetes risk using the K-Nearest Neighbor (KNN) classification algorithm. The system processes health parameters consisting of glucose level, blood pressure, body mass index (BMI), age, and gender. System development applies the Software Development Life Cycle (SDLC) Waterfall model, covering requirements analysis, system design, development, testing, and maintenance. The developed application provides data management, K-value configuration, prediction, and prediction-history features. Black Box testing shows that the implemented functions operate according to the expected scenarios. Accuracy testing using 10 test data produced 10 correct predictions and no incorrect predictions, resulting in an accuracy of 100%. The results indicate that the developed application can support early diabetes-risk screening and demonstrate that KNN can be integrated into a web-based prediction system.

Downloads

Download data is not yet available.

References

[1] A. K. Putra, “Rancang Bangun Sistem Monitoring Efisiensi Pada Mesin Boiler DBU Berbasis Web,” Jurnal Instrumentasi dan Teknologi Informatika (JITI), 2021.

[2] A. Saputra et al., “Tinjauan Sistematis Sistem Informasi Kesehatan Berbasis Web Untuk Transformasi Manajemen Penyakit Kronis,” JTBC: Jurnal Teknologi dan Bisnis Cerdas, pp. 48–56, 2026.

[3] E. Effendy et al., “Mengenal Sistem Informasi Manajemen Dakwah (Pengertian Sistem, Karakteristik Sistem),” Jurnal Pendidikan dan Konseling (JPDK), vol. 5, no. 2, pp. 4343–4349, 2023.

[4] F. Ruziq and M. R. Wayahdi, “Web-Based Diabetes Risk Prediction System Using K-NN on Kaggle Early Stage Diabetes Dataset,” JUTIF (Jurnal Informatika), pp. 3217–3229, 2025.

[5] Fathirma'ruf and B. M. Said, “Pengembangan Perangkat Pembelajaran Konstruktivistik Model Teaching with Analogies (TWA) pada Mata Kuliah Database Management System (DBMS) untuk Meningkatkan Kemampuan Berpikir Kreatif Mahasiswa,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 7, no. 5, pp. 1051–1060, 2021.

[6] Indrawan, 2024.

[7] J. Parhusip and G. Stevans, “Analisis Perbandingan Akurasi Algoritma K-Nearest Neighbor (KNN), Decision Tree, dan Random Forest dalam Klasifikasi Penyakit Diabetes,” JURNAL MEDIA INFORMATIKA (JUMIN), pp. 26–32, 2026.

[8] Laila, F. and N. A. Hasibuan, “Pemilihan Pengangkatan Karyawan Tetap Menerapkan Metode Multi-Attributive Border Approximation Area Comparison,” Journal of Informatics Management and Information Technology, pp. 5–12, 2021.

[9] M. A. A. Candra and I. A. Wulandari, “Sistem Informasi Berprestasi Berbasis Web Pada SMP Negeri 7 Kota Metro,” Jurnal Mahasiswa Ilmu Komputer (JMIK), pp. 175–189, 2021.

[10] Meiyanti, “Rancang Bangun Sistem Informasi Reservasi Kamar Hotel Menggunakan Java NetBeans,” Sisfo: Jurnal Ilmiah Sistem Informasi, vol. 5, no. 2, 2021.

[11] M. P. Daulay, R. E. C. Malau, and N. A. Hasibuan, “Sistem Pendukung Keputusan Penentuan Karyawan Terbaik Berdasarkan Kinerja Menggunakan Metode TOPSIS,” TIN: Terapan Informatika Nusantara, pp. 80–87, 2022.

[12] Mukhlis, I. Ramadhani, and R. Santoso, “Perancangan Basis Data Perpustakaan Universitas Menggunakan MySQL dengan Physical Data Model dan Entity Relationship Diagram,” Journal of Technology and Informatics (JoTI), pp. 81–87, 2023.

[13] N. Ikhsan, “Klasifikasi Penyakit Diabetes Menggunakan Metode K-Nearest Neighbors (KNN) Berdasarkan Data Klinis,” INFOTECH: Jurnal Informatika & Teknologi, pp. 19–26, 2026.

[14] Nuristiqomah, 2021.

[15] Prahasti, 2022.

[16] R. Riansyah and A. Syahputra, “Sistem Klasifikasi Diabetes Mellitus Menggunakan Algoritma K-Nearest Neighbor (KNN) Berbasis Web,” JUIKTI (Jurnal Ilmu Komputer dan Teknik Informatika), pp. 119–130, 2026.

[17] Saifudin, 2024.

[18] Santoso, 2023.

[19] Setiyani and Lila, “Desain Sistem: Use Case Diagram,” Prosiding Seminar Nasional Inovasi dan Adopsi Teknologi (INOTEK), vol. 1, no. 1, 2021.

[20] S. Narulita, A. Nugroho, and M. Z. Abdillah, “Diagram Unified Modelling Language (UML) untuk Perancangan Sistem Informasi Manajemen Penelitian dan Pengabdian Masyarakat (SIMLITABMAS),” Jurnal Publikasi Sistem Informasi dan Telekomunikasi, vol. 2, no. 3, 2024.

[21] S. Cholarika and F. A. Zahro, “Konsep Dasar Dalam Sistem Informasi Manajemen Dalam Pendidikan,” Al-Bahjah Journal of Islamic Education Management, pp. 51–60, 2023.

[22] S. Arfiah, F. Wajid, and N. Nur, “Optimasi Algoritma K-Nearest Neighbors pada Prediksi Penyakit Diabetes,” JURIKOM (Jurnal Riset Komputer), pp. 230–240, 2025.

[23] T. Sutabri and M. T. Sadewa, “Perancangan Sistem Informasi Pendataan Inventory Aset pada Depot Kayu Kusen Laris III,” Jurnal Sains dan Teknologi Informasi, vol. 3, no. 1, pp. 11–17, 2025.

[24] Tjoe, “Metode Waterfall,” 2020.

[25] Y. Rahmawati and M. Syukri, “Faktor Risiko Diabetes Melitus Tipe 2 pada Kelompok Umur ≥ 15 Tahun di Provinsi DKI Jakarta: Analisis Data SKI 2023,” Jurnal Penelitian Sains dan Kesehatan Avicenna, pp. 257–267, 2026.