Visualisasi Data Pemetaan Daerah Hipertensi Menggunakan Algoritma K-Means

Penulis

  • Haris Andika Arbi Universitas Islam Negeri Sumatera Utara
  • Raissa Amanda Putri Universitas Islam Negeri Sumatera Utara

Kata Kunci:

Data Visualization, Hypertension, K-Means Clustering, Tableau, Rapidminer

Abstrak

According to data from the Ministry of Health in 2019, the number of hypertension patients continues to rise and is projected to reach approximately 1.5 billion by 2025. Additionally, an estimated 9.4 million people die each year due to hypertension and its complications. The current challenge is the difficulty faced by the public in understanding the information contained in the data, leading to a decrease in awareness of the importance of maintaining health to prevent and control hypertension. This research proposes the use of the K-Means clustering algorithm with spatial data visualization techniques to communicate information from the data more effectively to the public. The proposed method allows the K-Means clustering algorithm to group regions based on hypertension characteristics such as prevalence and risk factors, while spatial data visualization techniques are used to display the data in the form of a geographic map of hypertension areas. The results of applying this method show that the K-Means clustering algorithm produces five clusters that reflect different characteristics of hypertension, and spatial data visualization techniques generate a geographic map of hypertension areas with five different colors representing the highest to lowest characteristic groups of hypertension. This research provides a clear and easily understandable way to communicate information from the data, thereby assisting the public in efforts to prevent and control hypertension and its risk factors.

Referensi

Dewi, D. A. I. C., & Pramita, D. A. K. (2019). Analisis Perbandingan Metode Elbow dan Silhouette pada Algoritma Clustering K-Medoids dalam Pengelompokan Produksi Kerajinan Bali. Matrix : Jurnal Manajemen Teknologi Dan Informatika, 9(3), 102–109. https://doi.org/10.31940/matrix.v9i3.1662

Faujia, R. A., & Subarkah, M. Z. (2022). Analisis Klaster K-Means Dan Visualisasi Data Spasial Berdasarkan Karakteristik Persebaran Covid-19 Dan Pelanggaran Protokol Kesehatan Di Jawa Tengah. Seminar Nasional Official Statistics, 2022(1), 813–822. https://doi.org/10.34123/semnasoffstat.v2022i1.1222

Irawan, D., Siwi, A. S., & Susanto, A. (2020). Analisis Faktor-Faktor yang Memengaruhi Kejadian Hipertensi. Journal of Bionursing, 2(3), 164–166. https://doi.org/10.20884/1.bion.2020.2.3.70

Mulyani, A., & Kartini. (2023). VISUALISASI DATA TICKETING SERVICEDESK DENGAN DASHBOARD PADA PT BRANTAS ABIPRAYA (PERSERO). 7(2), 289–300. https://doi.org/10.52362/jisamar.v7i2.1074

Purwoko, S., Cahyati, W. H., & Farida, E. (2020). Pemanfaatan Sistem Informasi Geografis ( SIG ) dalam Analisis Sebaran Penyakit Menular TB BTA Positif Di Jawa Tengah Tahun.

Siregar, H. D., Marlindawani, J., Harefa, K., Ketaren, O., & Rohana, T. (2021). FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN HIPERTENSI DI PUSKESMAS TELADAN KOTA MEDAN TAHUN 2021. 7(2), 985–1001.

Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 4 Oktober 2023

Unduhan

Diterbitkan

2023-10-30

Cara Mengutip

Arbi, H. A., & Putri, R. A. (2023). Visualisasi Data Pemetaan Daerah Hipertensi Menggunakan Algoritma K-Means. Jurnal Teknologi Sistem Informasi Dan Aplikasi, 6(4), 631–638. Diambil dari https://openjournal.unpam.ac.id/index.php/JTSI/article/view/33923

Terbitan

Vol 6 No 4 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi

Bagian

Article

Lisensi

Hak Cipta (c) 2023 Haris Andika Arbi, Raissa Amanda Putri

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